{ "a4": { "Package": "a4", "Version": "1.22.0", "Depends": [ "a4Base", "a4Preproc", "a4Classif", "a4Core", "a4Reporting" ], "Suggests": [ "MLP", "nlcv", "ALL", "Cairo" ], "License": "GPL-3", "MD5sum": "c17ae72ad2115d0e5c80ca6d9c7b5cba", "NeedsCompilation": "no", "Title": "Automated Affymetrix Array Analysis Umbrella Package", "Description": "Automated Affymetrix Array Analysis Umbrella Package", "biocViews": [ "Microarray", "Software" ], "Author": "Willem Talloen, Tobias Verbeke", "Maintainer": "Tobias Verbeke , Willem Ligtenberg ", "source.ver": "src/contrib/a4_1.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/a4_1.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/a4_1.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/a4_1.22.0.tgz", "vignettes": [ "vignettes/a4/inst/doc/a4vignette.pdf" ], "vignetteTitles": [ "a4vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/a4/inst/doc/a4vignette.R" ] }, "a4Base": { "Package": "a4Base", "Version": "1.22.0", "Depends": [ "methods", "graphics", "grid", "Biobase", "AnnotationDbi", "annaffy", "mpm", "genefilter", "limma", "multtest", "glmnet", "a4Preproc", "a4Core", "gplots" ], "Suggests": [ "Cairo", "ALL" ], "Enhances": [ "gridSVG", "JavaGD" ], "License": "GPL-3", "MD5sum": "abb9cd7a79c892c8185314ae1112af1b", "NeedsCompilation": "no", "Title": "Automated Affymetrix Array Analysis Base Package", "Description": "Automated Affymetrix Array Analysis", "biocViews": [ "Microarray", "Software" ], "Author": "Willem Talloen, Tobias Verbeke, Tine Casneuf, An De Bondt, Steven Osselaer and Hinrich Goehlmann, Willem Ligtenberg", "Maintainer": "Tobias Verbeke , Willem Ligtenberg ", "source.ver": "src/contrib/a4Base_1.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/a4Base_1.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/a4Base_1.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/a4Base_1.22.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "dependsOnMe": [ "a4" ] }, "a4Classif": { "Package": "a4Classif", "Version": "1.22.0", "Depends": [ "methods", "a4Core", "a4Preproc", "MLInterfaces", "ROCR", "pamr", "glmnet", "varSelRF" ], "Imports": [ "a4Core" ], "Suggests": [ "ALL" ], "License": "GPL-3", "MD5sum": "d61fa0ce5023e28cc77232b9d432a78e", "NeedsCompilation": "no", "Title": "Automated Affymetrix Array Analysis Classification Package", "Description": "Automated Affymetrix Array Analysis Classification Package", "biocViews": [ "Microarray", "Software" ], "Author": "Willem Talloen, Tobias Verbeke", "Maintainer": "Tobias Verbeke , Willem Ligtenberg ", "source.ver": "src/contrib/a4Classif_1.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/a4Classif_1.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/a4Classif_1.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/a4Classif_1.22.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "dependsOnMe": [ "a4" ] }, "a4Core": { "Package": "a4Core", "Version": "1.22.0", "Depends": [ "methods", "Biobase", "glmnet" ], "License": "GPL-3", "MD5sum": "553294aafed8524bf5d749b5f9c2e801", "NeedsCompilation": "no", "Title": "Automated Affymetrix Array Analysis Core Package", "Description": "Automated Affymetrix Array Analysis Core Package", "biocViews": [ "Microarray", "Software" ], "Author": "Willem Talloen, Tobias Verbeke", "Maintainer": "Tobias Verbeke , Willem Ligtenberg ", "source.ver": "src/contrib/a4Core_1.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/a4Core_1.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/a4Core_1.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/a4Core_1.22.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "dependsOnMe": [ "a4", "a4Base", "a4Classif" ], "importsMe": [ "a4Classif" ] }, "a4Preproc": { "Package": "a4Preproc", "Version": "1.22.0", "Depends": [ "methods", "AnnotationDbi" ], "Suggests": [ "ALL", "hgu95av2.db" ], "License": "GPL-3", "MD5sum": "6be9da5f55b6e8a829d10da664d2c8cb", "NeedsCompilation": "no", "Title": "Automated Affymetrix Array Analysis Preprocessing Package", "Description": "Automated Affymetrix Array Analysis Preprocessing Package", "biocViews": [ "Microarray", "Software" ], "Author": "Willem Talloen, Tobias Verbeke", "Maintainer": "Tobias Verbeke , Willem Ligtenberg ", "source.ver": "src/contrib/a4Preproc_1.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/a4Preproc_1.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/a4Preproc_1.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/a4Preproc_1.22.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "dependsOnMe": [ "a4", "a4Base", "a4Classif" ] }, "a4Reporting": { "Package": "a4Reporting", "Version": "1.22.0", "Depends": [ "methods", "annaffy" ], "Imports": [ "xtable", "utils" ], "License": "GPL-3", "MD5sum": "2403cf04ac874a22e6040548fb458fc1", "NeedsCompilation": "no", "Title": "Automated Affymetrix Array Analysis Reporting Package", "Description": "Automated Affymetrix Array Analysis Reporting Package", "biocViews": [ "Microarray", "Software" ], "Author": "Tobias Verbeke", "Maintainer": "Tobias Verbeke , Willem Ligtenberg ", "source.ver": "src/contrib/a4Reporting_1.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/a4Reporting_1.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/a4Reporting_1.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/a4Reporting_1.22.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "dependsOnMe": [ "a4" ] }, "ABAEnrichment": { "Package": "ABAEnrichment", "Version": "1.4.0", "Depends": [ "R (>= 3.2)" ], "Imports": [ "Rcpp (>= 0.11.5)", "gplots (>= 2.14.2)", "ABAData (>= 0.99.2)" ], "LinkingTo": [ "Rcpp" ], "Suggests": [ "BiocStyle", "knitr", "testthat" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "b5fe5f284611eb595b088c8995d5f88e", "NeedsCompilation": "yes", "Title": "Gene expression enrichment in human brain regions", "Description": "The package ABAEnrichment is designed to test for enrichment of user defined candidate genes in the set of expressed genes in different human brain regions. The core function 'aba_enrich' integrates the expression of the candidate gene set (averaged across donors) and the structural information of the brain using an ontology, both provided by the Allen Brain Atlas project. 'aba_enrich' interfaces the ontology enrichment software FUNC to perform the statistical analyses. Additional functions provided in this package like 'get_expression' and 'plot_expression' facilitate exploring the expression data.", "biocViews": [ "GeneExpression", "GeneSetEnrichment", "Software" ], "Author": "Steffi Grote", "Maintainer": "Steffi Grote ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/ABAEnrichment_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ABAEnrichment_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ABAEnrichment_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ABAEnrichment_1.4.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ABAEnrichment/inst/doc/ABAEnrichment.R" ], "htmlDocs": [ "vignettes/ABAEnrichment/inst/doc/ABAEnrichment.html" ], "htmlTitles": [ "ABAEnrichment: gene expression enrichment in human brain regions" ] }, "ABarray": { "Package": "ABarray", "Version": "1.42.0", "Imports": [ "Biobase", "graphics", "grDevices", "methods", "multtest", "stats", "tcltk", "utils" ], "Suggests": [ "limma", "LPE" ], "License": "GPL", "MD5sum": "6068090f67ebd3462fda3009f599564d", "NeedsCompilation": "no", "Title": "Microarray QA and statistical data analysis for Applied Biosystems Genome Survey Microrarray (AB1700) gene expression data.", "Description": "Automated pipline to perform gene expression analysis for Applied Biosystems Genome Survey Microarray (AB1700) data format. Functions include data preprocessing, filtering, control probe analysis, statistical analysis in one single function. A GUI interface is also provided. The raw data, processed data, graphics output and statistical results are organized into folders according to the analysis settings used.", "biocViews": [ "Microarray", "OneChannel", "Preprocessing", "Software" ], "Author": "Yongming Andrew Sun", "Maintainer": "Yongming Andrew Sun ", "source.ver": "src/contrib/ABarray_1.42.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ABarray_1.42.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ABarray_1.42.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ABarray_1.42.0.tgz", "vignettes": [ "vignettes/ABarray/inst/doc/ABarray.pdf", "vignettes/ABarray/inst/doc/ABarrayGUI.pdf" ], "vignetteTitles": [ "ABarray gene expression", "ABarray gene expression GUI interface" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false }, "ABSSeq": { "Package": "ABSSeq", "Version": "1.20.4", "Depends": [ "R (>= 2.10)", "methods" ], "Imports": [ "locfit", "limma" ], "License": "GPL (>= 3)", "MD5sum": "5833f70e751a60391524bcd76fd8deb1", "NeedsCompilation": "no", "Title": "ABSSeq: a new RNA-Seq analysis method based on modelling absolute expression differences", "Description": "Inferring differential expression genes by absolute counts difference between two groups, utilizing Negative binomial distribution and moderating fold-change according to heterogeneity of dispersion across expression level.", "biocViews": [ "DifferentialExpression", "Software" ], "Author": "Wentao Yang", "Maintainer": "Wentao Yang ", "source.ver": "src/contrib/ABSSeq_1.20.4.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ABSSeq_1.20.4.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ABSSeq_1.20.4.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ABSSeq_1.20.4.tgz", "vignettes": [ "vignettes/ABSSeq/inst/doc/ABSSeq.pdf" ], "vignetteTitles": [ "ABSSeq" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ABSSeq/inst/doc/ABSSeq.R" ] }, "acde": { "Package": "acde", "Version": "1.4.0", "Depends": [ "R(>= 3.3)", "boot(>= 1.3)" ], "Imports": [ "stats", "graphics" ], "Suggests": [ "BiocGenerics", "RUnit" ], "License": "GPL-3", "MD5sum": "80ced523a273942ff77ccf480ecdf165", "NeedsCompilation": "no", "Title": "Artificial Components Detection of Differentially Expressed Genes", "Description": "This package provides a multivariate inferential analysis method for detecting differentially expressed genes in gene expression data. It uses artificial components, close to the data's principal components but with an exact interpretation in terms of differential genetic expression, to identify differentially expressed genes while controlling the false discovery rate (FDR). The methods on this package are described in the vignette or in the article 'Multivariate Method for Inferential Identification of Differentially Expressed Genes in Gene Expression Experiments' by J. P. Acosta, L. Lopez-Kleine and S. Restrepo (2015, pending publication).", "biocViews": [ "DifferentialExpression", "GeneExpression", "Microarray", "PrincipalComponent", "Software", "TimeCourse", "mRNAMicroarray" ], "Author": "Juan Pablo Acosta, Liliana Lopez-Kleine", "Maintainer": "Juan Pablo Acosta ", "source.ver": "src/contrib/acde_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/acde_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/acde_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/acde_1.4.0.tgz", "vignettes": [ "vignettes/acde/inst/doc/acde.pdf" ], "vignetteTitles": [ "Identification of Differentially Expressed Genes with Artificial Components" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/acde/inst/doc/acde.R" ] }, "aCGH": { "Package": "aCGH", "Version": "1.52.0", "Depends": [ "R (>= 2.10)", "cluster", "survival", "multtest" ], "Imports": [ "Biobase", "cluster", "grDevices", "graphics", "methods", "multtest", "stats", "survival", "splines", "utils" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "5921ef5304e3d8cfa998fc3dde442360", "NeedsCompilation": "yes", "Title": "Classes and functions for Array Comparative Genomic Hybridization data.", "Description": "Functions for reading aCGH data from image analysis output files and clone information files, creation of aCGH S3 objects for storing these data. Basic methods for accessing/replacing, subsetting, printing and plotting aCGH objects.", "biocViews": [ "CopyNumberVariation", "DataImport", "Genetics", "Software" ], "Author": "Jane Fridlyand , Peter Dimitrov ", "Maintainer": "Peter Dimitrov ", "source.ver": "src/contrib/aCGH_1.52.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/aCGH_1.52.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/aCGH_1.52.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/aCGH_1.52.0.tgz", "vignettes": [ "vignettes/aCGH/inst/doc/aCGH.pdf" ], "vignetteTitles": [ "aCGH Overview" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/aCGH/inst/doc/aCGH.R" ], "dependsOnMe": [ "CRImage" ], "importsMe": [ "ADaCGH2", "rCGH", "snapCGH" ], "suggestsMe": [ "beadarraySNP" ] }, "ACME": { "Package": "ACME", "Version": "2.30.0", "Depends": [ "R (>= 2.10)", "Biobase (>= 2.5.5)", "methods", "BiocGenerics" ], "Imports": [ "graphics", "stats" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "1e5d8d8b9c0791db4d8b2504937c9baa", "NeedsCompilation": "yes", "Title": "Algorithms for Calculating Microarray Enrichment (ACME)", "Description": "ACME (Algorithms for Calculating Microarray Enrichment) is a set of tools for analysing tiling array ChIP/chip, DNAse hypersensitivity, or other experiments that result in regions of the genome showing \"enrichment\". It does not rely on a specific array technology (although the array should be a \"tiling\" array), is very general (can be applied in experiments resulting in regions of enrichment), and is very insensitive to array noise or normalization methods. It is also very fast and can be applied on whole-genome tiling array experiments quite easily with enough memory.", "biocViews": [ "Microarray", "Normalization", "Software", "Technology" ], "Author": "Sean Davis ", "Maintainer": "Sean Davis ", "URL": "http://watson.nci.nih.gov/~sdavis", "source.ver": "src/contrib/ACME_2.30.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ACME_2.30.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ACME_2.30.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ACME_2.30.0.tgz", "vignettes": [ "vignettes/ACME/inst/doc/ACME.pdf" ], "vignetteTitles": [ "ACME" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ACME/inst/doc/ACME.R" ], "suggestsMe": [ "oligo" ] }, "ADaCGH2": { "Package": "ADaCGH2", "Version": "2.14.0", "Depends": [ "R (>= 3.2.0)", "parallel", "ff", "GLAD" ], "Imports": [ "bit", "ffbase", "DNAcopy", "tilingArray", "waveslim", "cluster", "aCGH", "snapCGH" ], "Suggests": [ "CGHregions", "Cairo", "limma" ], "Enhances": [ "Rmpi" ], "License": "GPL (>= 3)", "Archs": "i386, x64", "MD5sum": "6bee49612d3ab22ab76fad81ac96164a", "NeedsCompilation": "yes", "Title": "Analysis of big data from aCGH experiments using parallel computing and ff objects", "Description": "Analysis and plotting of array CGH data. Allows usage of Circular Binary Segementation, wavelet-based smoothing (both as in Liu et al., and HaarSeg as in Ben-Yaacov and Eldar), HMM, BioHMM, GLAD, CGHseg. Most computations are parallelized (either via forking or with clusters, including MPI and sockets clusters) and use ff for storing data.", "biocViews": [ "CopyNumberVariants", "Microarray", "Software" ], "Author": "Ramon Diaz-Uriarte and Oscar M. Rueda . Wavelet-based aCGH smoothing code from Li Hsu and Douglas Grove . Imagemap code from Barry Rowlingson . HaarSeg code from Erez Ben-Yaacov; downloaded from .", "Maintainer": "Ramon Diaz-Uriarte ", "URL": "https://github.com/rdiaz02/adacgh2", "source.ver": "src/contrib/ADaCGH2_2.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ADaCGH2_2.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ADaCGH2_2.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ADaCGH2_2.14.0.tgz", "vignettes": [ "vignettes/ADaCGH2/inst/doc/ADaCGH2-long-examples.pdf", "vignettes/ADaCGH2/inst/doc/ADaCGH2.pdf", "vignettes/ADaCGH2/inst/doc/benchmarks.pdf" ], "vignetteTitles": [ "ADaCGH2-long-examples.pdf", "ADaCGH2 Overview", "benchmarks.pdf" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ADaCGH2/inst/doc/ADaCGH2.R" ] }, "adSplit": { "Package": "adSplit", "Version": "1.44.0", "Depends": [ "R (>= 2.1.0)", "methods (>= 2.1.0)" ], "Imports": [ "AnnotationDbi", "Biobase (>= 1.5.12)", "cluster (>= 1.9.1)", "GO.db (>= 1.8.1)", "graphics", "grDevices", "KEGG.db (>= 1.8.1)", "methods", "multtest (>= 1.6.0)", "stats (>= 2.1.0)" ], "Suggests": [ "golubEsets (>= 1.0)", "vsn (>= 1.5.0)", "hu6800.db (>= 1.8.1)" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "fa75c757f6a13d43dfd8ac57df9f41ac", "NeedsCompilation": "yes", "Title": "Annotation-Driven Clustering", "Description": "This package implements clustering of microarray gene expression profiles according to functional annotations. For each term genes are annotated to, splits into two subclasses are computed and a significance of the supporting gene set is determined.", "biocViews": [ "Clustering", "Microarray", "Software" ], "Author": "Claudio Lottaz, Joern Toedling", "Maintainer": "Claudio Lottaz ", "URL": "http://compdiag.molgen.mpg.de/software/index.shtml", "source.ver": "src/contrib/adSplit_1.44.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/adSplit_1.44.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/adSplit_1.44.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/adSplit_1.44.0.tgz", "vignettes": [ "vignettes/adSplit/inst/doc/tr_2005_02.pdf" ], "vignetteTitles": [ "Annotation-Driven Clustering" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/adSplit/inst/doc/tr_2005_02.R" ] }, "affxparser": { "Package": "affxparser", "Version": "1.46.0", "Depends": [ "R (>= 2.14.0)" ], "Suggests": [ "R.oo (>= 1.20.0)", "R.utils (>= 2.4.0)", "AffymetrixDataTestFiles" ], "License": "LGPL (>= 2)", "Archs": "i386, x64", "MD5sum": "919a3d48659a4ac1759603b5579bc738", "NeedsCompilation": "yes", "Title": "Affymetrix File Parsing SDK", "Description": "Package for parsing Affymetrix files (CDF, CEL, CHP, BPMAP, BAR). It provides methods for fast and memory efficient parsing of Affymetrix files using the Affymetrix' Fusion SDK. Both ASCII- and binary-based files are supported. Currently, there are methods for reading chip definition file (CDF) and a cell intensity file (CEL). These files can be read either in full or in part. For example, probe signals from a few probesets can be extracted very quickly from a set of CEL files into a convenient list structure.", "biocViews": [ "DataImport", "Infrastructure", "Microarray", "OneChannel", "ProprietaryPlatforms", "Software" ], "Author": "Henrik Bengtsson [aut], James Bullard [aut], Robert Gentleman [ctb], Kasper Daniel Hansen [aut, cre], Jim Hester [ctb], Martin Morgan [ctb]", "Maintainer": "Kasper Daniel Hansen ", "URL": "https://github.com/HenrikBengtsson/affxparser", "BugReports": "https://github.com/HenrikBengtsson/affxparser/issues", "source.ver": "src/contrib/affxparser_1.46.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/affxparser_1.46.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/affxparser_1.46.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/affxparser_1.46.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "dependsOnMe": [ "ITALICS", "pdInfoBuilder", "rMAT", "Starr" ], "importsMe": [ "affyILM", "cn.farms", "crossmeta", "GeneRegionScan", "ITALICS", "oligo", "rMAT" ], "suggestsMe": [ "TIN" ] }, "affy": { "Package": "affy", "Version": "1.52.0", "Depends": [ "R (>= 2.8.0)", "BiocGenerics (>= 0.1.12)", "Biobase (>= 2.5.5)" ], "Imports": [ "affyio (>= 1.13.3)", "BiocInstaller", "graphics", "grDevices", "methods", "preprocessCore", "stats", "utils", "zlibbioc" ], "LinkingTo": [ "preprocessCore" ], "Suggests": [ "tkWidgets (>= 1.19.0)", "affydata", "widgetTools" ], "License": "LGPL (>= 2.0)", "Archs": "i386, x64", "MD5sum": "97c4fe88f8ff1178228d2560c7b33ceb", "NeedsCompilation": "yes", "Title": "Methods for Affymetrix Oligonucleotide Arrays", "Description": "The package contains functions for exploratory oligonucleotide array analysis. The dependence on tkWidgets only concerns few convenience functions. 'affy' is fully functional without it.", "biocViews": [ "Microarray", "OneChannel", "Preprocessing", "Software" ], "Author": "Rafael A. Irizarry , Laurent Gautier , Benjamin Milo Bolstad , and Crispin Miller with contributions from Magnus Astrand , Leslie M. Cope , Robert Gentleman, Jeff Gentry, Conrad Halling , Wolfgang Huber, James MacDonald , Benjamin I. P. Rubinstein, Christopher Workman , John Zhang", "Maintainer": "Rafael A. Irizarry ", "source.ver": "src/contrib/affy_1.52.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/affy_1.52.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/affy_1.52.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/affy_1.52.0.tgz", "vignettes": [ "vignettes/affy/inst/doc/affy.pdf", "vignettes/affy/inst/doc/builtinMethods.pdf", "vignettes/affy/inst/doc/customMethods.pdf", "vignettes/affy/inst/doc/vim.pdf" ], "vignetteTitles": [ "1. Primer", "2. Built-in Processing Methods", "3. Custom Processing Methods", "4. Import Methods" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/affy/inst/doc/affy.R", "vignettes/affy/inst/doc/builtinMethods.R", "vignettes/affy/inst/doc/customMethods.R", "vignettes/affy/inst/doc/vim.R" ], "dependsOnMe": [ "affyContam", "affydata", "AffyExpress", "affyPara", "affypdnn", "affyPLM", "affyQCReport", "AffyRNADegradation", "AgiMicroRna", "ALLMLL", "altcdfenvs", "AmpAffyExample", "arrayMvout", "ArrayTools", "bgx", "bronchialIL13", "ccTutorial", "ChimpHumanBrainData", "CLL", "Cormotif", "curatedBladderData", "curatedOvarianData", "DrugVsDisease", "dualKS", "ecoliLeucine", "ExiMiR", "farms", "frmaTools", "gcrma", "Hiiragi2013", "LMGene", "logitT", "maPredictDSC", "MAQCsubset", "MAQCsubsetAFX", "maskBAD", "MLP", "mvoutData", "panp", "plw", "prebs", "PREDAsampledata", "pumadata", "qpcrNorm", "ReadqPCR", "RefPlus", "rHVDM", "Risa", "RPA", "SCAN.UPC", "simpleaffy", "SpikeIn", "SpikeInSubset", "sscore", "Starr", "webbioc", "XhybCasneuf" ], "importsMe": [ "affycoretools", "affyILM", "affylmGUI", "affyQCReport", "arrayQualityMetrics", "ArrayTools", "CAFE", "ChIPXpress", "Cormotif", "crossmeta", "DeSousa2013", "EGAD", "farms", "ffpe", "frma", "gcrma", "GEOsubmission", "Harshlight", "HTqPCR", "iCheck", "lumi", "LVSmiRNA", "makecdfenv", "MSnbase", "PECA", "plier", "plw", "puma", "pvac", "rCGH", "Rnits", "simpleaffy", "STATegRa", "TCGAbiolinks", "tilingArray", "TurboNorm", "vsn", "waveTiling" ], "suggestsMe": [ "AnnotationForge", "ArrayExpress", "beadarray", "beadarraySNP", "BiocCaseStudies", "BiocGenerics", "Biostrings", "BufferedMatrixMethods", "categoryCompare", "ecolitk", "estrogen", "ExpressionView", "factDesign", "ffpeExampleData", "gCMAPWeb", "GeneRegionScan", "limma", "made4", "MLSeq", "oneChannelGUI", "paxtoolsr", "piano", "PREDA", "prot2D", "qcmetrics", "siggenes" ] }, "affycomp": { "Package": "affycomp", "Version": "1.50.0", "Depends": [ "R (>= 2.13.0)", "methods", "Biobase (>= 2.3.3)" ], "Suggests": [ "splines", "affycompData" ], "License": "GPL (>= 2)", "MD5sum": "570110fd8b1681348feedc48341f234a", "NeedsCompilation": "no", "Title": "Graphics Toolbox for Assessment of Affymetrix Expression Measures", "Description": "The package contains functions that can be used to compare expression measures for Affymetrix Oligonucleotide Arrays.", "biocViews": [ "Microarray", "OneChannel", "Preprocessing", "Software" ], "Author": "Rafael A. Irizarry and Zhijin Wu with contributions from Simon Cawley ", "Maintainer": "Rafael A. Irizarry ", "source.ver": "src/contrib/affycomp_1.50.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/affycomp_1.50.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/affycomp_1.50.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/affycomp_1.50.0.tgz", "vignettes": [ "vignettes/affycomp/inst/doc/affycomp.pdf" ], "vignetteTitles": [ "affycomp primer" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/affycomp/inst/doc/affycomp.R" ], "dependsOnMe": [ "affycompData" ] }, "AffyCompatible": { "Package": "AffyCompatible", "Version": "1.34.0", "Depends": [ "R (>= 2.7.0)", "XML (>= 2.8-1)", "RCurl (>= 0.8-1)", "methods" ], "Imports": [ "Biostrings" ], "License": "Artistic-2.0", "MD5sum": "17d0c75d84992710c1bcfa486dd9f416", "NeedsCompilation": "no", "Title": "Affymetrix GeneChip software compatibility", "Description": "This package provides an interface to Affymetrix chip annotation and sample attribute files. The package allows an easy way for users to download and manage local data bases of Affynmetrix NetAffx annotation files. The package also provides access to GeneChip Operating System (GCOS) and GeneChip Command Console (AGCC)-compatible sample annotation files.", "biocViews": [ "Infrastructure", "Microarray", "OneChannel", "Software" ], "Author": "Martin Morgan, Robert Gentleman", "Maintainer": "Martin Morgan ", "source.ver": "src/contrib/AffyCompatible_1.34.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/AffyCompatible_1.34.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/AffyCompatible_1.34.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/AffyCompatible_1.34.0.tgz", "vignettes": [ "vignettes/AffyCompatible/inst/doc/MAGEAndARR.pdf", "vignettes/AffyCompatible/inst/doc/NetAffxResource.pdf" ], "vignetteTitles": [ "Retrieving MAGE and ARR sample attributes", "Annotation retrieval with NetAffxResource" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/AffyCompatible/inst/doc/MAGEAndARR.R", "vignettes/AffyCompatible/inst/doc/NetAffxResource.R" ], "importsMe": [ "IdMappingRetrieval" ], "suggestsMe": [ "oneChannelGUI" ] }, "affyContam": { "Package": "affyContam", "Version": "1.32.0", "Depends": [ "R (>= 2.7.0)", "tools", "methods", "utils", "Biobase", "affy", "affydata" ], "License": "Artistic-2.0", "MD5sum": "86ca5bb087ecf710f3a67de4711afeea", "NeedsCompilation": "no", "Title": "structured corruption of affymetrix cel file data", "Description": "structured corruption of cel file data to demonstrate QA effectiveness", "biocViews": [ "Infrastructure", "Software" ], "Author": "V. Carey", "Maintainer": "V. Carey ", "source.ver": "src/contrib/affyContam_1.32.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/affyContam_1.32.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/affyContam_1.32.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/affyContam_1.32.0.tgz", "vignettes": [ "vignettes/affyContam/inst/doc/affyContam.pdf" ], "vignetteTitles": [ "affy contamination tools" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/affyContam/inst/doc/affyContam.R" ], "importsMe": [ "arrayMvout" ] }, "affycoretools": { "Package": "affycoretools", "Version": "1.46.5", "Depends": [ "Biobase", "methods" ], "Imports": [ "affy", "limma", "GOstats", "gcrma", "splines", "xtable", "AnnotationDbi", "ggplot2", "gplots", "oligoClasses", "ReportingTools", "hwriter", "lattice", "S4Vectors", "edgeR", "RSQLite", "BiocGenerics" ], "Suggests": [ "affydata", "hgfocuscdf", "BiocStyle", "knitr", "hgu95av2.db", "rgl" ], "License": "Artistic-2.0", "MD5sum": "b3c6541610b712769b46f74ef45cf63f", "NeedsCompilation": "no", "Title": "Functions useful for those doing repetitive analyses with Affymetrix GeneChips", "Description": "Various wrapper functions that have been written to streamline the more common analyses that a core Biostatistician might see.", "biocViews": [ "GeneExpression", "Microarray", "OneChannel", "ReportWriting", "Software" ], "Author": "James W. MacDonald", "Maintainer": "James W. MacDonald ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/affycoretools_1.46.5.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/affycoretools_1.46.5.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/affycoretools_1.46.5.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/affycoretools_1.46.5.tgz", "vignettes": [ "vignettes/affycoretools/inst/doc/RefactoredAffycoretools.pdf" ], "vignetteTitles": [ "affycoretools, refactored" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/affycoretools/inst/doc/RefactoredAffycoretools.R" ], "dependsOnMe": [ "AgiMicroRna" ] }, "AffyExpress": { "Package": "AffyExpress", "Version": "1.40.0", "Depends": [ "R (>= 2.10)", "affy (>= 1.23.4)", "limma" ], "Suggests": [ "simpleaffy", "R2HTML", "affyPLM", "hgu95av2cdf", "hgu95av2", "test3cdf", "genefilter", "estrogen", "annaffy", "gcrma" ], "License": "LGPL", "MD5sum": "3c923f92c1a1322e2b201281ccd64f53", "NeedsCompilation": "no", "Title": "Affymetrix Quality Assessment and Analysis Tool", "Description": "The purpose of this package is to provide a comprehensive and easy-to-use tool for quality assessment and to identify differentially expressed genes in the Affymetrix gene expression data.", "biocViews": [ "Annotation", "DifferentialExpression", "Microarray", "OneChannel", "Preprocessing", "QualityControl", "ReportWriting", "Software", "Visualization" ], "Author": "Xiwei Wu , Xuejun Arthur Li ", "Maintainer": "Xuejun Arthur Li ", "source.ver": "src/contrib/AffyExpress_1.40.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/AffyExpress_1.40.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/AffyExpress_1.40.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/AffyExpress_1.40.0.tgz", "vignettes": [ "vignettes/AffyExpress/inst/doc/AffyExpress.pdf" ], "vignetteTitles": [ "1. Primer" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/AffyExpress/inst/doc/AffyExpress.R" ] }, "affyILM": { "Package": "affyILM", "Version": "1.26.0", "Depends": [ "R (>= 2.10.0)", "methods", "gcrma" ], "Imports": [ "affxparser (>= 1.16.0)", "affy", "graphics", "methods", "Biobase" ], "Suggests": [ "AffymetrixDataTestFiles" ], "License": "GPL version 3", "MD5sum": "ba96d8400dfb1a44a7aca9f1084a15b7", "NeedsCompilation": "no", "Title": "Linear Model of background subtraction and the Langmuir isotherm", "Description": "affyILM is a preprocessing tool which estimates gene expression levels for Affymetrix Gene Chips. Input from physical chemistry is employed to first background subtract intensities before calculating concentrations on behalf of the Langmuir model.", "biocViews": [ "Microarray", "OneChannel", "Preprocessing", "Software" ], "Author": "K. Myriam Kroll, Fabrice Berger, Gerard Barkema, Enrico Carlon", "Maintainer": "Myriam Kroll and Fabrice Berger ", "source.ver": "src/contrib/affyILM_1.26.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/affyILM_1.26.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/affyILM_1.26.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/affyILM_1.26.0.tgz", "vignettes": [ "vignettes/affyILM/inst/doc/affyILM.pdf" ], "vignetteTitles": [ "affyILM1.3.0" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/affyILM/inst/doc/affyILM.R" ] }, "affyio": { "Package": "affyio", "Version": "1.44.0", "Depends": [ "R (>= 2.6.0)" ], "Imports": [ "zlibbioc" ], "License": "LGPL (>= 2)", "Archs": "i386, x64", "MD5sum": "b859000e41ac339670f78ecd52eff33d", "NeedsCompilation": "yes", "Title": "Tools for parsing Affymetrix data files", "Description": "Routines for parsing Affymetrix data files based upon file format information. Primary focus is on accessing the CEL and CDF file formats.", "biocViews": [ "DataImport", "Infrastructure", "Microarray", "Software" ], "Author": "Benjamin Milo Bolstad ", "Maintainer": "Benjamin Milo Bolstad ", "URL": "https://github.com/bmbolstad/affyio", "source.ver": "src/contrib/affyio_1.44.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/affyio_1.44.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/affyio_1.44.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/affyio_1.44.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "dependsOnMe": [ "affyPara", "makecdfenv", "SCAN.UPC", "sscore" ], "importsMe": [ "affy", "affylmGUI", "crlmm", "ExiMiR", "gcrma", "oligo", "oligoClasses", "puma" ], "suggestsMe": [ "BufferedMatrixMethods" ] }, "affylmGUI": { "Package": "affylmGUI", "Version": "1.48.0", "Imports": [ "limma", "tcltk", "affy", "BiocInstaller", "affyio", "tkrplot", "affyPLM", "R2HTML", "xtable", "gcrma", "AnnotationDbi" ], "License": "GPL (>=2)", "MD5sum": "d16e8d0e01ac274c2b520f35540d8494", "NeedsCompilation": "no", "Title": "GUI for limma package with Affymetrix microarrays", "Description": "A Graphical User Interface for analysis of Affymetrix microarray gene expression data using the affy and limma packages.", "biocViews": [ "BatchEffect", "Bayesian", "DataImport", "DifferentialExpression", "GUI", "GeneExpression", "Microarray", "MultipleComparison", "Normalization", "OneChannel", "Preprocessing", "ProprietaryPlatforms", "QualityControl", "Regression", "Software", "TimeCourse", "Transcription", "mRNAMicroarray" ], "Author": "James Wettenhall [aut], Ken Simpson [aut], Gordon Smyth [aut], Keith Satterley [ctb], Yifang Hu [ctb]", "Maintainer": "Yifang Hu , Gordon Smyth , Keith Satterley ", "URL": "http://bioinf.wehi.edu.au/affylmGUI/", "source.ver": "src/contrib/affylmGUI_1.48.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/affylmGUI_1.48.2.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/affylmGUI_1.48.2.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/affylmGUI_1.48.0.tgz", "vignettes": [ "vignettes/affylmGUI/inst/doc/affylmGUI.pdf", "vignettes/affylmGUI/inst/doc/extract.pdf" ], "vignetteTitles": [ "affylmGUI Vignette", "Extracting affy and limma objects from affylmGUI files" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/affylmGUI/inst/doc/affylmGUI.R" ], "htmlDocs": [ "vignettes/affylmGUI/inst/doc/about.html", "vignettes/affylmGUI/inst/doc/CustMenu.html", "vignettes/affylmGUI/inst/doc/index.html", "vignettes/affylmGUI/inst/doc/windowsFocus.html" ], "htmlTitles": [ "about.html", "CustMenu.html", "index.html", "windowsFocus.html" ], "dependsOnMe": [ "oneChannelGUI" ] }, "affyPara": { "Package": "affyPara", "Version": "1.34.0", "Depends": [ "R (>= 2.5.0)", "methods", "affy (>= 1.20.0)", "snow (>= 0.2-3)", "vsn (>= 3.6.0)", "aplpack (>= 1.1.1)", "affyio" ], "Suggests": [ "affydata" ], "Enhances": [ "affy" ], "License": "GPL-3", "MD5sum": "0c33a26476c6ff19545b65b0878a3121", "NeedsCompilation": "no", "Title": "Parallelized preprocessing methods for Affymetrix Oligonucleotide Arrays", "Description": "The package contains parallelized functions for exploratory oligonucleotide array analysis. The package is designed for large numbers of microarray data.", "biocViews": [ "Microarray", "Preprocessing", "Software" ], "Author": "Markus Schmidberger , Esmeralda Vicedo , Ulrich Mansmann ", "Maintainer": "Markus Schmidberger ", "URL": "http://www.ibe.med.uni-muenchen.de", "source.ver": "src/contrib/affyPara_1.34.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/affyPara_1.34.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/affyPara_1.34.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/affyPara_1.34.0.tgz", "vignettes": [ "vignettes/affyPara/inst/doc/affyPara.pdf", "vignettes/affyPara/inst/doc/vsnStudy.pdf" ], "vignetteTitles": [ "Parallelized affy functions for preprocessing", "Simulation Study for VSN Add-On Normalization and Subsample Size" ], "hasREADME": true, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/affyPara/inst/doc/affyPara.R", "vignettes/affyPara/inst/doc/vsnStudy.R" ] }, "affypdnn": { "Package": "affypdnn", "Version": "1.48.0", "Depends": [ "R (>= 2.13.0)", "affy (>= 1.5)" ], "Suggests": [ "affydata", "hgu95av2probe" ], "License": "LGPL", "MD5sum": "f7cf66254588387120a3b1ddbdf41790", "NeedsCompilation": "no", "Title": "Probe Dependent Nearest Neighbours (PDNN) for the affy package", "Description": "The package contains functions to perform the PDNN method described by Li Zhang et al.", "biocViews": [ "Microarray", "OneChannel", "Preprocessing", "Software" ], "Author": "H. Bjorn Nielsen and Laurent Gautier (Many thanks to Li Zhang early communications about the existence of the PDNN program and related publications).", "Maintainer": "Laurent Gautier", "source.ver": "src/contrib/affypdnn_1.48.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/affypdnn_1.48.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/affypdnn_1.48.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/affypdnn_1.48.0.tgz", "vignettes": [ "vignettes/affypdnn/inst/doc/affypdnn.pdf" ], "vignetteTitles": [ "affypdnn" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/affypdnn/inst/doc/affypdnn.R" ] }, "affyPLM": { "Package": "affyPLM", "Version": "1.50.0", "Depends": [ "R (>= 2.6.0)", "BiocGenerics (>= 0.3.2)", "affy (>= 1.11.0)", "Biobase (>= 2.17.8)", "gcrma", "stats", "preprocessCore (>= 1.5.1)" ], "Imports": [ "zlibbioc", "graphics", "grDevices", "methods" ], "LinkingTo": [ "preprocessCore" ], "Suggests": [ "affydata", "MASS" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "8cd5513706ffbebc70f51466fd7433ac", "NeedsCompilation": "yes", "Title": "Methods for fitting probe-level models", "Description": "A package that extends and improves the functionality of the base affy package. Routines that make heavy use of compiled code for speed. Central focus is on implementation of methods for fitting probe-level models and tools using these models. PLM based quality assessment tools.", "biocViews": [ "Microarray", "OneChannel", "Preprocessing", "QualityControl", "Software" ], "Author": "Ben Bolstad ", "Maintainer": "Ben Bolstad ", "URL": "https://github.com/bmbolstad/affyPLM", "source.ver": "src/contrib/affyPLM_1.50.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/affyPLM_1.50.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/affyPLM_1.50.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/affyPLM_1.50.0.tgz", "vignettes": [ "vignettes/affyPLM/inst/doc/AffyExtensions.pdf", "vignettes/affyPLM/inst/doc/MAplots.pdf", "vignettes/affyPLM/inst/doc/QualityAssess.pdf", "vignettes/affyPLM/inst/doc/ThreeStep.pdf" ], "vignetteTitles": [ "affyPLM: Fitting Probe Level Models", "affyPLM: Advanced use of the MAplot function", "affyPLM: Model Based QC Assessment of Affymetrix GeneChips", "affyPLM: the threestep function" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/affyPLM/inst/doc/AffyExtensions.R", "vignettes/affyPLM/inst/doc/MAplots.R", "vignettes/affyPLM/inst/doc/QualityAssess.R", "vignettes/affyPLM/inst/doc/ThreeStep.R" ], "dependsOnMe": [ "RefPlus" ], "importsMe": [ "affylmGUI", "affyQCReport", "arrayQualityMetrics" ], "suggestsMe": [ "AffyExpress", "arrayMvout", "ArrayTools", "BiocCaseStudies", "BiocGenerics", "ELBOW", "frmaTools", "metahdep", "oneChannelGUI", "piano" ] }, "affyQCReport": { "Package": "affyQCReport", "Version": "1.52.0", "Depends": [ "Biobase (>= 1.13.16)", "affy", "lattice" ], "Imports": [ "affy", "affyPLM", "Biobase", "genefilter", "graphics", "grDevices", "lattice", "RColorBrewer", "simpleaffy", "stats", "utils", "xtable" ], "Suggests": [ "tkWidgets (>= 1.5.23)", "affydata (>= 1.4.1)" ], "License": "LGPL (>= 2)", "MD5sum": "5365471bd610f4c0e92474db87854e70", "NeedsCompilation": "no", "Title": "QC Report Generation for affyBatch objects", "Description": "This package creates a QC report for an AffyBatch object. The report is intended to allow the user to quickly assess the quality of a set of arrays in an AffyBatch object.", "biocViews": [ "Microarray", "OneChannel", "QualityControl", "Software" ], "Author": "Craig Parman , Conrad Halling , Robert Gentleman", "Maintainer": "Craig Parman ", "source.ver": "src/contrib/affyQCReport_1.52.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/affyQCReport_1.52.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/affyQCReport_1.52.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/affyQCReport_1.52.0.tgz", "vignettes": [ "vignettes/affyQCReport/inst/doc/affyQCReport.pdf" ], "vignetteTitles": [ "affyQCReport: Methods for Generating Affymetrix QC Reports" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/affyQCReport/inst/doc/affyQCReport.R" ], "suggestsMe": [ "BiocCaseStudies" ] }, "AffyRNADegradation": { "Package": "AffyRNADegradation", "Version": "1.20.0", "Depends": [ "R (>= 2.9.0)", "methods", "affy" ], "Suggests": [ "AmpAffyExample" ], "License": "GPL-2", "MD5sum": "f0c7075a45f4210059eb66837be67873", "NeedsCompilation": "no", "Title": "Analyze and correct probe positional bias in microarray data due to RNA degradation", "Description": "The package helps with the assessment and correction of RNA degradation effects in Affymetrix 3' expression arrays. The parameter d gives a robust and accurate measure of RNA integrity. The correction removes the probe positional bias, and thus improves comparability of samples that are affected by RNA degradation.", "biocViews": [ "GeneExpression", "Microarray", "OneChannel", "Preprocessing", "QualityControl", "Software" ], "Author": "Mario Fasold", "Maintainer": "Mario Fasold ", "source.ver": "src/contrib/AffyRNADegradation_1.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/AffyRNADegradation_1.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/AffyRNADegradation_1.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/AffyRNADegradation_1.20.0.tgz", "vignettes": [ "vignettes/AffyRNADegradation/inst/doc/vignette.pdf" ], "vignetteTitles": [ "AffyRNADegradation Example" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/AffyRNADegradation/inst/doc/vignette.R" ] }, "AGDEX": { "Package": "AGDEX", "Version": "1.22.0", "Depends": [ "R (>= 2.10)", "Biobase", "GSEABase" ], "Imports": [ "stats" ], "License": "GPL Version 2 or later", "MD5sum": "c8bec49bf1e2135fec271934bab019fe", "NeedsCompilation": "no", "Title": "Agreement of Differential Expression Analysis", "Description": "A tool to evaluate agreement of differential expression for cross-species genomics", "biocViews": [ "GeneExpression", "Genetics", "Microarray", "Software" ], "Author": "Stan Pounds ; Cuilan Lani Gao ", "Maintainer": "Cuilan lani Gao ", "source.ver": "src/contrib/AGDEX_1.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/AGDEX_1.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/AGDEX_1.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/AGDEX_1.22.0.tgz", "vignettes": [ "vignettes/AGDEX/inst/doc/AGDEX.pdf" ], "vignetteTitles": [ "AGDEX.pdf" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/AGDEX/inst/doc/AGDEX.R" ] }, "agilp": { "Package": "agilp", "Version": "3.6.0", "Depends": [ "R (>= 2.14.0)" ], "License": "GPL-3", "MD5sum": "8d21eacaccb049c38a55b57e493adb42", "NeedsCompilation": "no", "Title": "Agilent expression array processing package", "Description": "More about what it does (maybe more than one line)", "Author": "Benny Chain ", "Maintainer": "Benny Chain ", "source.ver": "src/contrib/agilp_3.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/agilp_3.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/agilp_3.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/agilp_3.6.0.tgz", "vignettes": [ "vignettes/agilp/inst/doc/agilp_manual.pdf" ], "vignetteTitles": [ "An R Package for processing expression microarray data" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/agilp/inst/doc/agilp_manual.R" ], "biocViews": [ "Software" ] }, "AgiMicroRna": { "Package": "AgiMicroRna", "Version": "2.24.0", "Depends": [ "R (>= 2.10)", "methods", "Biobase", "limma", "affy (>= 1.22)", "preprocessCore", "affycoretools" ], "Imports": [ "Biobase" ], "Suggests": [ "geneplotter", "marray", "gplots", "gtools", "gdata", "codelink" ], "License": "GPL-3", "MD5sum": "d2985426d555bfdfae719814fb104b40", "NeedsCompilation": "no", "Title": "Processing and Differential Expression Analysis of Agilent microRNA chips", "Description": "Processing and Analysis of Agilent microRNA data", "biocViews": [ "AgilentChip", "DifferentialExpression", "Microarray", "OneChannel", "Preprocessing", "Software" ], "Author": "Pedro Lopez-Romero ", "Maintainer": "Pedro Lopez-Romero ", "source.ver": "src/contrib/AgiMicroRna_2.24.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/AgiMicroRna_2.24.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/AgiMicroRna_2.24.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/AgiMicroRna_2.24.0.tgz", "vignettes": [ "vignettes/AgiMicroRna/inst/doc/AgiMicroRna.pdf" ], "vignetteTitles": [ "AgiMicroRna" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/AgiMicroRna/inst/doc/AgiMicroRna.R" ] }, "AIMS": { "Package": "AIMS", "Version": "1.6.0", "Depends": [ "R (>= 2.10)", "e1071", "Biobase" ], "Suggests": [ "breastCancerVDX", "hgu133a.db", "RUnit", "BiocGenerics" ], "License": "Artistic-2.0", "MD5sum": "7c3e9f60864122267bc79487ec17f08b", "NeedsCompilation": "no", "Title": "AIMS : Absolute Assignment of Breast Cancer Intrinsic Molecular Subtype", "Description": "This package contains the AIMS implementation. It contains necessary functions to assign the five intrinsic molecular subtypes (Luminal A, Luminal B, Her2-enriched, Basal-like, Normal-like). Assignments could be done on individual samples as well as on dataset of gene expression data.", "biocViews": [ "Classification", "GeneExpression", "Microarray", "RNASeq", "Software" ], "Author": "Eric R. Paquet, Michael T. Hallett", "Maintainer": "Eric R Paquet ", "URL": "http://www.bci.mcgill.ca/AIMS", "source.ver": "src/contrib/AIMS_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/AIMS_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/AIMS_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/AIMS_1.6.0.tgz", "vignettes": [ "vignettes/AIMS/inst/doc/AIMS.pdf" ], "vignetteTitles": [ "AIMS An Introduction (HowTo)" ], "hasREADME": true, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/AIMS/inst/doc/AIMS.R" ], "dependsOnMe": [ "genefu" ] }, "ALDEx2": { "Package": "ALDEx2", "Version": "1.6.0", "Depends": [ "methods" ], "Imports": [ "S4Vectors", "IRanges", "GenomicRanges", "SummarizedExperiment", "BiocParallel" ], "License": "file LICENSE", "MD5sum": "86545f99da4b6619fa8f5211cf83bb86", "NeedsCompilation": "no", "Title": "Analysis Of Differential Abundance Taking Sample Variation Into Account", "Description": "A differential abundance analysis for the comparison of two or more conditions. For example, single-organism and meta-RNA-seq high-throughput sequencing assays, or of selected and unselected values from in-vitro sequence selections. Uses a Dirichlet-multinomial model to infer abundance from counts, that has been optimized for three or more experimental replicates. Infers sampling variation and calculates the expected false discovery rate given the biological and sampling variation using the Wilcox rank test or Welches t-test (aldex.ttest) or the glm and Kruskal Wallis tests (aldex.glm). Reports both P and fdr values calculated by the Benjamini Hochberg correction.", "biocViews": [ "Bayesian", "ChIPSeq", "DNASeq", "DifferentialExpression", "GeneExpression", "Metagenomics", "Microbiome", "RNASeq", "Sequencing", "Software" ], "Author": "Greg Gloor, Ruth Grace Wong, Andrew Fernandes, Arianne Albert, Matt Links, Jia Rong Wu", "Maintainer": "Greg Gloor ", "source.ver": "src/contrib/ALDEx2_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ALDEx2_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ALDEx2_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ALDEx2_1.6.0.tgz", "vignettes": [ "vignettes/ALDEx2/inst/doc/ALDEx2_vignette.pdf" ], "vignetteTitles": [ "An R Package for determining differential abundance in high throughput sequencing experiments" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/ALDEx2/inst/doc/ALDEx2_vignette.R" ] }, "AllelicImbalance": { "Package": "AllelicImbalance", "Version": "1.12.0", "Depends": [ "R (>= 3.2.0)", "grid", "GenomicRanges", "SummarizedExperiment (>= 0.2.0)", "GenomicAlignments" ], "Imports": [ "methods", "BiocGenerics", "AnnotationDbi", "BSgenome", "VariantAnnotation", "Biostrings", "S4Vectors (>= 0.9.25)", "IRanges", "Rsamtools", "GenomicFeatures", "Gviz", "lattice", "latticeExtra", "gridExtra", "seqinr", "GenomeInfoDb" ], "Suggests": [ "testthat", "org.Hs.eg.db", "TxDb.Hsapiens.UCSC.hg19.knownGene", "SNPlocs.Hsapiens.dbSNP144.GRCh37", "BiocStyle", "knitr", "rmarkdown" ], "License": "GPL-3", "MD5sum": "9952e93c00441a08ec5bdd5abce3402d", "NeedsCompilation": "no", "Title": "Investigates Allele Specific Expression", "Description": "Provides a framework for allelic specific expression investigation using RNA-seq data.", "biocViews": [ "Genetics", "Infrastructure", "Sequencing", "Software" ], "Author": "Jesper R Gadin, Lasse Folkersen", "Maintainer": "Jesper R Gadin ", "URL": "https://github.com/pappewaio/AllelicImbalance", "VignetteBuilder": "knitr", "BugReports": "https://github.com/pappewaio/AllelicImbalance/issues", "source.ver": "src/contrib/AllelicImbalance_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/AllelicImbalance_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/AllelicImbalance_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/AllelicImbalance_1.12.0.tgz", "vignettes": [ "vignettes/AllelicImbalance/inst/doc/AllelicImbalance-vignette.pdf" ], "vignetteTitles": [ "AllelicImbalance Vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/AllelicImbalance/inst/doc/AllelicImbalance-vignette.R" ] }, "alpine": { "Package": "alpine", "Version": "1.0.0", "Depends": [ "R (>= 3.3)" ], "Imports": [ "Biostrings", "IRanges", "GenomicRanges", "GenomicAlignments", "Rsamtools", "SummarizedExperiment", "GenomicFeatures", "speedglm", "splines", "graph", "RBGL", "stringr", "stats", "methods", "graphics", "GenomeInfoDb", "S4Vectors" ], "Suggests": [ "knitr", "testthat", "alpineData", "rtracklayer", "ensembldb", "BSgenome.Hsapiens.NCBI.GRCh38", "RColorBrewer" ], "License": "GPL (>=2)", "MD5sum": "f70ca32c5336aca7745ee3875bbbf28f", "NeedsCompilation": "no", "Title": "alpine", "Description": "Fragment sequence bias modeling and correction for RNA-seq transcript abundance estimation.", "biocViews": [ "AlternativeSplicing", "BatchEffect", "Coverage", "DifferentialSplicing", "GeneExpression", "Normalization", "QualityControl", "RNASeq", "Sequencing", "Software", "Transcription", "Visualization" ], "Author": "Michael Love, Rafael Irizarry", "Maintainer": "Michael Love ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/alpine_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/alpine_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/alpine_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/alpine_1.0.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/alpine/inst/doc/alpine.R" ], "htmlDocs": [ "vignettes/alpine/inst/doc/alpine.html" ], "htmlTitles": [ "alpine" ] }, "alsace": { "Package": "alsace", "Version": "1.10.0", "Depends": [ "R (>= 2.10)", "ALS", "ptw (>= 1.0.6)" ], "Suggests": [ "lattice" ], "License": "GPL (>= 2)", "MD5sum": "1750971f1c5f11e4dc931a01ab567bb5", "NeedsCompilation": "no", "Title": "ALS for the Automatic Chemical Exploration of mixtures", "Description": "Alternating Least Squares (or Multivariate Curve Resolution) for analytical chemical data, in particular hyphenated data where the first direction is a retention time axis, and the second a spectral axis. Package builds on the basic als function from the ALS package and adds functionality for high-throughput analysis, including definition of time windows, clustering of profiles, retention time correction, etcetera.", "Author": "Ron Wehrens", "Maintainer": "Ron Wehrens ", "URL": "https://github.com/rwehrens/alsace", "source.ver": "src/contrib/alsace_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/alsace_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/alsace_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/alsace_1.10.0.tgz", "vignettes": [ "vignettes/alsace/inst/doc/alsace.pdf" ], "vignetteTitles": [ "alsace" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/alsace/inst/doc/alsace.R" ], "biocViews": [ "Software" ] }, "altcdfenvs": { "Package": "altcdfenvs", "Version": "2.36.0", "Depends": [ "R (>= 2.7)", "methods", "BiocGenerics (>= 0.1.0)", "S4Vectors (>= 0.9.25)", "Biobase (>= 2.15.1)", "affy", "makecdfenv", "Biostrings", "hypergraph" ], "Suggests": [ "plasmodiumanophelescdf", "hgu95acdf", "hgu133aprobe", "hgu133a.db", "hgu133acdf", "Rgraphviz", "RColorBrewer" ], "License": "GPL (>= 2)", "MD5sum": "4db877b969bd2303155080026a4b1820", "NeedsCompilation": "no", "Title": "alternative CDF environments (aka probeset mappings)", "Description": "Convenience data structures and functions to handle cdfenvs", "biocViews": [ "Annotation", "Microarray", "OneChannel", "Preprocessing", "ProprietaryPlatforms", "QualityControl", "Software", "Transcription" ], "Author": "Laurent Gautier ", "Maintainer": "Laurent Gautier ", "source.ver": "src/contrib/altcdfenvs_2.36.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/altcdfenvs_2.36.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/altcdfenvs_2.36.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/altcdfenvs_2.36.0.tgz", "vignettes": [ "vignettes/altcdfenvs/inst/doc/altcdfenvs.pdf", "vignettes/altcdfenvs/inst/doc/modify.pdf", "vignettes/altcdfenvs/inst/doc/ngenomeschips.pdf" ], "vignetteTitles": [ "altcdfenvs", "affy primer", "affy primer" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/altcdfenvs/inst/doc/altcdfenvs.R", "vignettes/altcdfenvs/inst/doc/modify.R", "vignettes/altcdfenvs/inst/doc/ngenomeschips.R" ], "importsMe": [ "Harshlight" ] }, "AMOUNTAIN": { "Package": "AMOUNTAIN", "Version": "1.0.0", "Depends": [ "R (>= 3.1.0)" ], "Suggests": [ "BiocStyle", "qgraph" ], "License": "GPL (>= 2)", "MD5sum": "a10a538f8dfc006f95737ef04832dd8a", "NeedsCompilation": "no", "Title": "Active modules for multilayer weighted gene co-expression networks: a continuous optimization approach", "Description": "A pure data-driven gene network, weighted gene co-expression network (WGCN) could be constructed only from expression profile. Different layers in such networks may represent different time points, multiple conditions or various species. AMOUNTAIN aims to search active modules in multi-layer WGCN using a continuous optimization approach.", "biocViews": [ "DifferentialExpression", "GeneExpression", "Microarray", "Network", "Software" ], "Author": "Dong Li, Shan He, Zhisong Pan and Guyu Hu", "Maintainer": "Dong Li ", "source.ver": "src/contrib/AMOUNTAIN_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/AMOUNTAIN_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/AMOUNTAIN_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/AMOUNTAIN_1.0.0.tgz", "vignettes": [ "vignettes/AMOUNTAIN/inst/doc/AMOUNTAIN.pdf" ], "vignetteTitles": [ "Usage of AMOUNTAIN" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/AMOUNTAIN/inst/doc/AMOUNTAIN.R" ] }, "ampliQueso": { "Package": "ampliQueso", "Version": "1.12.0", "Depends": [ "R (>= 2.15.0)", "rnaSeqMap (>= 2.17.1)", "knitr", "rgl", "ggplot2", "gplots", "parallel", "doParallel", "foreach", "VariantAnnotation", "genefilter", "statmod", "xtable" ], "Imports": [ "edgeR", "DESeq", "samr" ], "License": "GPL-2", "MD5sum": "5543e5ad269aba0909def985caa93639", "NeedsCompilation": "no", "Title": "Analysis of amplicon enrichment panels", "Description": "The package provides tools and reports for the analysis of amplicon sequencing panels, such as AmpliSeq", "biocViews": [ "DifferentialExpression", "GeneExpression", "RNASeq", "ReportWriting", "Sequencing", "Software", "Transcription", "Visualization" ], "Author": "Alicja Szabelska ; Marek Wiewiorka ; Michal Okoniewski ", "Maintainer": "Michal Okoniewski ", "source.ver": "src/contrib/ampliQueso_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ampliQueso_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ampliQueso_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ampliQueso_1.12.0.tgz", "vignettes": [ "vignettes/ampliQueso/inst/doc/ampliQueso.pdf" ], "vignetteTitles": [ "ampliQueso primer" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ampliQueso/inst/doc/ampliQueso.R" ] }, "AnalysisPageServer": { "Package": "AnalysisPageServer", "Version": "1.8.1", "Imports": [ "log4r", "tools", "rjson", "Biobase", "graph" ], "Suggests": [ "RUnit", "XML", "SVGAnnotation", "knitr" ], "Enhances": [ "Rook (>= 1.1)", "fork", "FastRWeb", "ggplot2" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "b3ed0fc654ce9715f48782d66b6335a2", "NeedsCompilation": "yes", "Title": "A framework for sharing interactive data and plots from R through the web.", "Description": "AnalysisPageServer is a modular system that enables sharing of customizable R analyses via the web.", "biocViews": [ "DataRepresentation", "GUI", "Software", "Visualization" ], "Author": "Brad Friedman , Adrian Nowicki, Hunter Whitney , Matthew Brauer ", "Maintainer": "Brad Friedman ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/AnalysisPageServer_1.8.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/AnalysisPageServer_1.8.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/AnalysisPageServer_1.8.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/AnalysisPageServer_1.8.1.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": true, "hasLICENSE": false, "Rfiles": [ "vignettes/AnalysisPageServer/inst/doc/AnalysisPageServer.R", "vignettes/AnalysisPageServer/inst/doc/ApacheDeployment.R", "vignettes/AnalysisPageServer/inst/doc/embedding.R", "vignettes/AnalysisPageServer/inst/doc/ExampleServers.R", "vignettes/AnalysisPageServer/inst/doc/FastRWebDeployment.R", "vignettes/AnalysisPageServer/inst/doc/InteractiveApps.R", "vignettes/AnalysisPageServer/inst/doc/Interactivity.R", "vignettes/AnalysisPageServer/inst/doc/StaticContent.R", "vignettes/AnalysisPageServer/inst/doc/TrappingConditions.R" ], "htmlDocs": [ "vignettes/AnalysisPageServer/inst/doc/AnalysisPageServer.html", "vignettes/AnalysisPageServer/inst/doc/ApacheDeployment.html", "vignettes/AnalysisPageServer/inst/doc/embedding.html", "vignettes/AnalysisPageServer/inst/doc/ExampleServers.html", "vignettes/AnalysisPageServer/inst/doc/FastRWebDeployment.html", "vignettes/AnalysisPageServer/inst/doc/InteractiveApps.html", "vignettes/AnalysisPageServer/inst/doc/Interactivity.html", "vignettes/AnalysisPageServer/inst/doc/Licenses.html", "vignettes/AnalysisPageServer/inst/doc/StaticContent.html", "vignettes/AnalysisPageServer/inst/doc/TrappingConditions.html" ], "htmlTitles": [ "0. AnalysisPageServer", "6. Apache Deployment", "2. Embedding APS datasets in other documents", "4. Non-interactive servers and Rook Deployment", "7. FastRWeb Deployment", "5. Interactive Apps AnalysisPageServer", "3. AnalysisPageServer Interactivity", "8. Licenses", "1. Making Static Content Interactive with AnalysisPageServer", "8. Condition Trapping" ] }, "anamiR": { "Package": "anamiR", "Version": "1.0.1", "Depends": [ "R (>= 3.3.1)", "SummarizedExperiment(>= 1.1.6)" ], "Imports": [ "stats", "DBI", "limma", "lumi", "agricolae", "RMySQL", "DESeq2", "SummarizedExperiment", "gplots" ], "Suggests": [ "knitr", "rmarkdown" ], "License": "GPL-2", "MD5sum": "f39310d0b5fb33f61d0cf2015fdfe849", "NeedsCompilation": "no", "Title": "An integrated analysis package of miRNA and mRNA expression data", "Description": "This package is intended to identify potential interactions of miRNA-target gene interactions from miRNA and mRNA expression data. It contains functions for statistical test, databases of miRNA-target gene interaction and functional analysis.", "biocViews": [ "AssayDomain", "BiologicalQuestion", "DifferentialExpression", "GeneExpression", "GeneRegulation", "GeneSetEnrichment", "GeneTarget", "Genetics", "Microarray", "Normalization", "Pathways", "ResearchField", "Sequencing", "Software", "Technology", "WorkflowStep", "miRNA" ], "Author": "Ti-Tai Wang [aut, cre], Tzu-Pin Lu [aut], Chien-Yueh Lee[ctb,] Eric Y. Chuang [aut]", "Maintainer": "Ti-Tai Wang ", "URL": "https://github.com/AllenTiTaiWang/anamiR", "VignetteBuilder": "knitr", "BugReports": "https://github.com/AllenTiTaiWang/anamiR/issues", "source.ver": "src/contrib/anamiR_1.0.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/anamiR_1.0.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/anamiR_1.0.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/anamiR_1.0.1.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/anamiR/inst/doc/IntroductionToanamiR.R" ], "htmlDocs": [ "vignettes/anamiR/inst/doc/IntroductionToanamiR.html" ], "htmlTitles": [ "Introduction to anamiR" ] }, "Anaquin": { "Package": "Anaquin", "Version": "1.0.0", "Depends": [ "R (>= 3.3)" ], "Imports": [ "ggplot2", "ROCR", "knitr", "qvalue", "locfit", "methods", "stats", "utils", "plyr" ], "Suggests": [ "RUnit", "rmarkdown" ], "License": "BSD_3_clause + file LICENSE", "MD5sum": "deef4fc84bb7e12bd34f7d077afc600f", "NeedsCompilation": "no", "Title": "Statistical analysis of sequins", "Description": "The project is intended to support the use of sequins (synthetic sequencing spike-in controls) owned and made available by the Garvan Institute of Medical Research. The goal is to provide a standard open source library for quantitative analysis, modelling and visualization of spike-in controls.", "biocViews": [ "DifferentialExpression", "GeneExpression", "Preprocessing", "RNASeq", "Software" ], "Author": "Ted Wong", "Maintainer": "Ted Wong ", "URL": "www.sequin.xyz", "VignetteBuilder": "knitr", "BugReports": "https://github.com/student-t/RAnaquin/issues", "source.ver": "src/contrib/Anaquin_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Anaquin_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Anaquin_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Anaquin_1.0.0.tgz", "vignettes": [ "vignettes/Anaquin/inst/doc/Anaquin.pdf" ], "vignetteTitles": [ "Anaquin - Vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/Anaquin/inst/doc/Anaquin.R" ] }, "AneuFinder": { "Package": "AneuFinder", "Version": "1.2.1", "Depends": [ "R (>= 3.3)", "GenomicRanges", "cowplot", "AneuFinderData" ], "Imports": [ "methods", "utils", "grDevices", "graphics", "stats", "foreach", "doParallel", "BiocGenerics", "S4Vectors", "GenomeInfoDb", "IRanges", "Rsamtools", "bamsignals", "DNAcopy", "Biostrings", "GenomicAlignments", "ggplot2", "reshape2", "ggdendro", "ggrepel", "ReorderCluster", "mclust" ], "Suggests": [ "knitr", "BiocStyle", "testthat", "BSgenome.Hsapiens.UCSC.hg19", "BSgenome.Mmusculus.UCSC.mm10" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "fa8f25e8d6ad19ace7518f419e0550e4", "NeedsCompilation": "yes", "Title": "Analysis of Copy Number Variation in Single-Cell-Sequencing Data", "Description": "This package implements functions for CNV calling, plotting, export and analysis from whole-genome single cell sequencing data.", "biocViews": [ "CopyNumberVariation", "GenomicVariation", "HiddenMarkovModel", "Software", "WholeGenome" ], "Author": "Aaron Taudt, Bjorn Bakker, David Porubsky", "Maintainer": "Aaron Taudt ", "URL": "https://github.com/ataudt/aneufinder.git", "VignetteBuilder": "knitr", "source.ver": "src/contrib/AneuFinder_1.2.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/AneuFinder_1.2.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/AneuFinder_1.2.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/AneuFinder_1.2.1.tgz", "vignettes": [ "vignettes/AneuFinder/inst/doc/AneuFinder.pdf" ], "vignetteTitles": [ "A quick introduction to AneuFinder" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/AneuFinder/inst/doc/AneuFinder.R" ] }, "annaffy": { "Package": "annaffy", "Version": "1.46.0", "Depends": [ "R (>= 2.5.0)", "methods", "Biobase", "GO.db", "KEGG.db" ], "Imports": [ "AnnotationDbi (>= 0.1.15)", "DBI" ], "Suggests": [ "hgu95av2.db", "multtest", "tcltk" ], "License": "LGPL", "MD5sum": "887b49f983cf9106529c36b1a94901cb", "NeedsCompilation": "no", "Title": "Annotation tools for Affymetrix biological metadata", "Description": "Functions for handling data from Bioconductor Affymetrix annotation data packages. Produces compact HTML and text reports including experimental data and URL links to many online databases. Allows searching biological metadata using various criteria.", "biocViews": [ "Annotation", "GO", "Microarray", "OneChannel", "Pathways", "ReportWriting", "Software" ], "Author": "Colin A. Smith ", "Maintainer": "Colin A. Smith ", "source.ver": "src/contrib/annaffy_1.46.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/annaffy_1.46.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/annaffy_1.46.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/annaffy_1.46.0.tgz", "vignettes": [ "vignettes/annaffy/inst/doc/annaffy.pdf" ], "vignetteTitles": [ "annaffy Primer" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/annaffy/inst/doc/annaffy.R" ], "dependsOnMe": [ "a4Base", "a4Reporting", "PGSEA", "webbioc" ], "suggestsMe": [ "AffyExpress", "ArrayTools", "BiocCaseStudies", "oneChannelGUI" ] }, "annmap": { "Package": "annmap", "Version": "1.16.0", "Depends": [ "R (>= 2.15.0)", "methods", "GenomicRanges" ], "Imports": [ "DBI", "RMySQL (>= 0.6-0)", "digest", "Biobase", "grid", "lattice", "Rsamtools", "genefilter", "IRanges", "BiocGenerics" ], "Suggests": [ "RUnit", "rjson", "Gviz" ], "License": "GPL-2", "MD5sum": "25a66da1e4c760eed8ff6bdaae086ac8", "NeedsCompilation": "no", "Title": "Genome annotation and visualisation package pertaining to Affymetrix arrays and NGS analysis.", "Description": "annmap provides annotation mappings for Affymetrix exon arrays and coordinate based queries to support deep sequencing data analysis. Database access is hidden behind the API which provides a set of functions such as genesInRange(), geneToExon(), exonDetails(), etc. Functions to plot gene architecture and BAM file data are also provided. Underlying data are from Ensembl.", "biocViews": [ "Annotation", "Microarray", "OneChannel", "ReportWriting", "Software", "Transcription", "Visualization" ], "Author": "Tim Yates ", "Maintainer": "Chris Wirth ", "URL": "http://annmap.cruk.manchester.ac.uk", "source.ver": "src/contrib/annmap_1.16.0.tar.gz", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/annmap_1.16.0.tgz", "vignettes": [ "vignettes/annmap/inst/doc/annmap.pdf", "vignettes/annmap/inst/doc/cookbook.pdf", "vignettes/annmap/inst/doc/INSTALL.pdf" ], "vignetteTitles": [ "annmap primer", "The Annmap Cookbook", "annmap installation instruction" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false }, "annotate": { "Package": "annotate", "Version": "1.52.1", "Depends": [ "R (>= 2.10)", "AnnotationDbi (>= 1.27.5)", "XML" ], "Imports": [ "Biobase", "DBI", "xtable", "graphics", "utils", "stats", "methods", "BiocGenerics (>= 0.13.8)", "RCurl" ], "Suggests": [ "hgu95av2.db", "genefilter", "Biostrings (>= 2.25.10)", "IRanges", "rae230a.db", "rae230aprobe", "tkWidgets", "GO.db", "org.Hs.eg.db", "org.Mm.eg.db", "hom.Hs.inp.db", "humanCHRLOC", "Rgraphviz", "RUnit" ], "License": "Artistic-2.0", "MD5sum": "b2512b78686d031af9b9024f91b7db7b", "NeedsCompilation": "no", "Title": "Annotation for microarrays", "Description": "Using R enviroments for annotation.", "biocViews": [ "Annotation", "GO", "Pathways", "Software" ], "Author": "R. Gentleman", "Maintainer": "Bioconductor Package Maintainer ", "source.ver": "src/contrib/annotate_1.52.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/annotate_1.52.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/annotate_1.52.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/annotate_1.52.1.tgz", "vignettes": [ "vignettes/annotate/inst/doc/annotate.pdf", "vignettes/annotate/inst/doc/chromLoc.pdf", "vignettes/annotate/inst/doc/GOusage.pdf", "vignettes/annotate/inst/doc/prettyOutput.pdf", "vignettes/annotate/inst/doc/query.pdf", "vignettes/annotate/inst/doc/useDataPkgs.pdf", "vignettes/annotate/inst/doc/useHomology.pdf", "vignettes/annotate/inst/doc/useProbeInfo.pdf" ], "vignetteTitles": [ "Annotation Overview", "HowTo: use chromosomal information", "Basic GO Usage", "HowTo: Get HTML Output", "HOWTO: Use the online query tools", "Using Data Packages", "Using the homology package", "Using Affymetrix Probe Level Data" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/annotate/inst/doc/annotate.R", "vignettes/annotate/inst/doc/chromLoc.R", "vignettes/annotate/inst/doc/GOusage.R", "vignettes/annotate/inst/doc/prettyOutput.R", "vignettes/annotate/inst/doc/query.R", "vignettes/annotate/inst/doc/useDataPkgs.R", "vignettes/annotate/inst/doc/useHomology.R", "vignettes/annotate/inst/doc/useProbeInfo.R" ], "dependsOnMe": [ "ChromHeatMap", "GeneAnswers", "geneplotter", "GOSim", "GSEABase", "idiogram", "macat", "MGFM", "MineICA", "MLInterfaces", "Neve2006", "PCpheno", "phenoTest", "PREDA", "PREDAsampledata", "RpsiXML", "ScISI", "SemDist" ], "importsMe": [ "CAFE", "Category", "categoryCompare", "CNEr", "codelink", "debrowser", "DOQTL", "DrugVsDisease", "facopy", "gCMAP", "gCMAPWeb", "GeneAnswers", "genefilter", "GlobalAncova", "globaltest", "GOstats", "lumi", "methyAnalysis", "methylumi", "MGFR", "mvGST", "phenoTest", "qpgraph", "ReportingTools", "ScISI", "splicegear", "systemPipeR", "tigre" ], "suggestsMe": [ "adme16cod.db", "ag.db", "ath1121501.db", "BiocCaseStudies", "BiocGenerics", "biomaRt", "bovine.db", "canine.db", "canine2.db", "celegans.db", "chicken.db", "clariomdhumanprobeset.db", "clariomdhumantranscriptcluster.db", "clariomshumanhttranscriptcluster.db", "clariomshumantranscriptcluster.db", "clariomsmousehttranscriptcluster.db", "clariomsmousetranscriptcluster.db", "clariomsrathttranscriptcluster.db", "clariomsrattranscriptcluster.db", "drosgenome1.db", "drosophila2.db", "ecoli2.db", "GenomicRanges", "GGHumanMethCancerPanelv1.db", "GlobalAncova", "GOstats", "GSAR", "GSEAlm", "h10kcod.db", "h20kcod.db", "hcg110.db", "hgfocus.db", "hgu133a.db", "hgu133a2.db", "hgu133b.db", "hgu133plus2.db", "hgu219.db", "hgu95a.db", "hgu95av2.db", "hgu95b.db", "hgu95c.db", "hgu95d.db", "hgu95e.db", "hguatlas13k.db", "hgubeta7.db", "hguDKFZ31.db", "hgug4100a.db", "hgug4101a.db", "hgug4110b.db", "hgug4111a.db", "hgug4112a.db", "hgug4845a.db", "hguqiagenv3.db", "hi16cod.db", "hs25kresogen.db", "Hs6UG171.db", "HsAgilentDesign026652.db", "hta20probeset.db", "hta20transcriptcluster.db", "hthgu133a.db", "hthgu133b.db", "hu35ksuba.db", "hu35ksubb.db", "hu35ksubc.db", "hu35ksubd.db", "hu6800.db", "huex10stprobeset.db", "huex10sttranscriptcluster.db", "hugene10stprobeset.db", "hugene10sttranscriptcluster.db", "hugene11stprobeset.db", "hugene11sttranscriptcluster.db", "hugene20stprobeset.db", "hugene20sttranscriptcluster.db", "hugene21stprobeset.db", "hugene21sttranscriptcluster.db", "HuO22.db", "hwgcod.db", "IlluminaHumanMethylation27k.db", "IlluminaHumanMethylation450k.db", "illuminaHumanv1.db", "illuminaHumanv2.db", "illuminaHumanv2BeadID.db", "illuminaHumanv3.db", "illuminaHumanv4.db", "illuminaHumanWGDASLv3.db", "illuminaHumanWGDASLv4.db", "illuminaMousev1.db", "illuminaMousev1p1.db", "illuminaMousev2.db", "illuminaRatv1.db", "indac.db", "JazaeriMetaData.db", "LAPOINTE.db", "lumiHumanAll.db", "lumiMouseAll.db", "lumiRatAll.db", "m10kcod.db", "m20kcod.db", "maigesPack", "metagenomeSeq", "mgu74a.db", "mgu74av2.db", "mgu74b.db", "mgu74bv2.db", "mgu74c.db", "mgu74cv2.db", "mguatlas5k.db", "mgug4104a.db", "mgug4120a.db", "mgug4121a.db", "mgug4122a.db", "mi16cod.db", "miRBaseVersions.db", "MLP", "mm24kresogen.db", "MmAgilentDesign026655.db", "moe430a.db", "moe430b.db", "moex10stprobeset.db", "moex10sttranscriptcluster.db", "mogene10stprobeset.db", "mogene10sttranscriptcluster.db", "mogene11stprobeset.db", "mogene11sttranscriptcluster.db", "mogene20stprobeset.db", "mogene20sttranscriptcluster.db", "mogene21stprobeset.db", "mogene21sttranscriptcluster.db", "mouse4302.db", "mouse430a2.db", "mpedbarray.db", "mta10probeset.db", "mta10transcriptcluster.db", "mu11ksuba.db", "mu11ksubb.db", "Mu15v1.db", "mu19ksuba.db", "mu19ksubb.db", "mu19ksubc.db", "Mu22v3.db", "mwgcod.db", "Norway981.db", "nugohs1a520180.db", "nugomm1a520177.db", "oneChannelGUI", "OperonHumanV3.db", "org.Ag.eg.db", "org.At.tair.db", "org.Bt.eg.db", "org.Ce.eg.db", "org.Cf.eg.db", "org.Dm.eg.db", "org.Dr.eg.db", "org.EcK12.eg.db", "org.EcSakai.eg.db", "org.Gg.eg.db", "org.Hs.eg.db", "org.Mm.eg.db", "org.Mmu.eg.db", "org.Pf.plasmo.db", "org.Pt.eg.db", "org.Rn.eg.db", "org.Sc.sgd.db", "org.Sco.eg.db", "org.Ss.eg.db", "org.Tgondii.eg.db", "org.Xl.eg.db", "PartheenMetaData.db", "pedbarrayv10.db", "pedbarrayv9.db", "POCRCannotation.db", "porcine.db", "puma", "r10kcod.db", "rae230a.db", "rae230b.db", "raex10stprobeset.db", "raex10sttranscriptcluster.db", "ragene10stprobeset.db", "ragene10sttranscriptcluster.db", "ragene11stprobeset.db", "ragene11sttranscriptcluster.db", "ragene20stprobeset.db", "ragene20sttranscriptcluster.db", "ragene21stprobeset.db", "ragene21sttranscriptcluster.db", "rat2302.db", "rgu34a.db", "rgu34b.db", "rgu34c.db", "rguatlas4k.db", "rgug4105a.db", "rgug4130a.db", "rgug4131a.db", "ri16cod.db", "RnAgilentDesign028282.db", "RnBeads", "rnu34.db", "Roberts2005Annotation.db", "rta10probeset.db", "rta10transcriptcluster.db", "rtu34.db", "rwgcod.db", "SHDZ.db", "siggenes", "SummarizedExperiment", "u133x3p.db", "xlaevis.db", "yeast2.db", "ygs98.db", "zebrafish.db" ] }, "AnnotationDbi": { "Package": "AnnotationDbi", "Version": "1.36.2", "Depends": [ "R (>= 2.7.0)", "methods", "utils", "stats4", "BiocGenerics (>= 0.15.10)", "Biobase (>= 1.17.0)", "IRanges" ], "Imports": [ "methods", "utils", "DBI", "RSQLite", "stats4", "BiocGenerics", "Biobase", "S4Vectors (>= 0.9.25)", "IRanges" ], "Suggests": [ "DBI (>= 0.2-4)", "RSQLite (>= 0.6-4)", "hgu95av2.db", "GO.db", "org.Sc.sgd.db", "org.At.tair.db", "KEGG.db", "RUnit", "TxDb.Hsapiens.UCSC.hg19.knownGene", "hom.Hs.inp.db", "org.Hs.eg.db", "reactome.db", "AnnotationForge", "graph", "EnsDb.Hsapiens.v75", "BiocStyle", "knitr" ], "License": "Artistic-2.0", "MD5sum": "ef0bfa62487e2ec5f301a182897006f7", "NeedsCompilation": "no", "Title": "Annotation Database Interface", "Description": "Provides user interface and database connection code for annotation data packages using SQLite data storage.", "biocViews": [ "Annotation", "GenomeAnnotation", "Microarray", "Sequencing", "Software" ], "Author": "Hervé Pagès, Marc Carlson, Seth Falcon, Nianhua Li", "Maintainer": "Bioconductor Package Maintainer ", "VignetteBuilder": "knitr", "Video": "https://www.youtube.com/watch?v=8qvGNTVz3Ik", "source.ver": "src/contrib/AnnotationDbi_1.36.2.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/AnnotationDbi_1.36.2.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/AnnotationDbi_1.36.2.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/AnnotationDbi_1.36.2.tgz", "vignettes": [ "vignettes/AnnotationDbi/inst/doc/AnnotationDbi.pdf", "vignettes/AnnotationDbi/inst/doc/IntroToAnnotationPackages.pdf" ], "vignetteTitles": [ "How to use bimaps from the \".db\" annotation packages", "AnnotationDbi: Introduction To Bioconductor Annotation Packages" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/AnnotationDbi/inst/doc/AnnotationDbi.R", "vignettes/AnnotationDbi/inst/doc/IntroToAnnotationPackages.R" ], "dependsOnMe": [ "a4Base", "a4Preproc", "adme16cod.db", "ag.db", "agprobe", "annotate", "AnnotationForge", "AnnotationFuncs", "anopheles.db0", "arabidopsis.db0", "ASpli", "ath1121501.db", "ath1121501probe", "attract", "barley1probe", "bovine.db", "bovine.db0", "bovineprobe", "bsubtilisprobe", "canine.db", "canine.db0", "canine2.db", "canine2probe", "canineprobe", "Category", "celegans.db", "celegansprobe", "chicken.db", "chicken.db0", "chickenprobe", "chimera", "chimp.db0", "ChromHeatMap", "citrusprobe", "clariomdhumanprobeset.db", "clariomdhumantranscriptcluster.db", "clariomshumanhttranscriptcluster.db", "clariomshumantranscriptcluster.db", "clariomsmousehttranscriptcluster.db", "clariomsmousetranscriptcluster.db", "clariomsrathttranscriptcluster.db", "clariomsrattranscriptcluster.db", "cottonprobe", "customProDB", "DEXSeq", "DO.db", "drosgenome1.db", "drosgenome1probe", "drosophila2.db", "drosophila2probe", "ecoli2.db", "ecoli2probe", "ecoliasv2probe", "ecoliK12.db0", "ecoliprobe", "ecoliSakai.db0", "EGSEA", "eisa", "ExpressionView", "FEM", "fly.db0", "gahgu133a.db", "gahgu133aprobe", "gahgu133b.db", "gahgu133bprobe", "gahgu133plus2.db", "gahgu133plus2probe", "gahgu95av2.db", "gahgu95av2probe", "gahgu95b.db", "gahgu95bprobe", "gahgu95c.db", "gahgu95cprobe", "gahgu95d.db", "gahgu95dprobe", "gahgu95e.db", "gahgu95eprobe", "GenomicFeatures", "GGdata", "GGHumanMethCancerPanelv1.db", "GO.db", "GOFunction", "goProfiles", "h10kcod.db", "h20kcod.db", "hcg110.db", "hcg110probe", "hgfocus.db", "hgfocusprobe", "hgu133a.db", "hgu133a2.db", "hgu133a2probe", "hgu133aprobe", "hgu133atagprobe", "hgu133b.db", "hgu133bprobe", "hgu133plus2.db", "hgu133plus2probe", "hgu219.db", "hgu219probe", "hgu95a.db", "hgu95aprobe", "hgu95av2.db", "hgu95av2probe", "hgu95b.db", "hgu95bprobe", "hgu95c.db", "hgu95cprobe", "hgu95d.db", "hgu95dprobe", "hgu95e.db", "hgu95eprobe", "hguatlas13k.db", "hgubeta7.db", "hguDKFZ31.db", "hgug4100a.db", "hgug4101a.db", "hgug4110b.db", "hgug4111a.db", "hgug4112a.db", "hgug4845a.db", "hguqiagenv3.db", "hi16cod.db", "hom.At.inp.db", "hom.Ce.inp.db", "hom.Dm.inp.db", "hom.Dr.inp.db", "hom.Hs.inp.db", "hom.Mm.inp.db", "hom.Rn.inp.db", "hom.Sc.inp.db", "Homo.sapiens", "hs25kresogen.db", "Hs6UG171.db", "HsAgilentDesign026652.db", "hta20probeset.db", "hta20transcriptcluster.db", "hthgu133a.db", "hthgu133aprobe", "hthgu133b.db", "hthgu133bprobe", "hthgu133pluspmprobe", "htmg430aprobe", "htmg430bprobe", "htmg430pmprobe", "htrat230pmprobe", "htratfocusprobe", "hu35ksuba.db", "hu35ksubaprobe", "hu35ksubb.db", "hu35ksubbprobe", "hu35ksubc.db", "hu35ksubcprobe", "hu35ksubd.db", "hu35ksubdprobe", "hu6800.db", "hu6800probe", "huex10stprobeset.db", "huex10sttranscriptcluster.db", "HuExExonProbesetLocation", "HuExExonProbesetLocationHg18", "HuExExonProbesetLocationHg19", "hugene10stprobeset.db", "hugene10sttranscriptcluster.db", "hugene10stv1probe", "hugene11stprobeset.db", "hugene11sttranscriptcluster.db", "hugene20stprobeset.db", "hugene20sttranscriptcluster.db", "hugene21stprobeset.db", "hugene21sttranscriptcluster.db", "human.db0", "HuO22.db", "hwgcod.db", "IlluminaHumanMethylation27k.db", "IlluminaHumanMethylation450k.db", "IlluminaHumanMethylation450kprobe", "illuminaHumanv1.db", "illuminaHumanv2.db", "illuminaHumanv2BeadID.db", "illuminaHumanv3.db", "illuminaHumanv4.db", "illuminaHumanWGDASLv3.db", "illuminaHumanWGDASLv4.db", "illuminaMousev1.db", "illuminaMousev1p1.db", "illuminaMousev2.db", "illuminaRatv1.db", "indac.db", "JazaeriMetaData.db", "KEGG.db", "LAPOINTE.db", "lumiHumanAll.db", "lumiHumanIDMapping", "lumiMouseAll.db", "lumiMouseIDMapping", "lumiRatAll.db", "lumiRatIDMapping", "m10kcod.db", "m20kcod.db", "maizeprobe", "malaria.db0", "maPredictDSC", "medicagoprobe", "MGFM", "mgu74a.db", "mgu74aprobe", "mgu74av2.db", "mgu74av2probe", "mgu74b.db", "mgu74bprobe", "mgu74bv2.db", "mgu74bv2probe", "mgu74c.db", "mgu74cprobe", "mgu74cv2.db", "mgu74cv2probe", "mguatlas5k.db", "mgug4104a.db", "mgug4120a.db", "mgug4121a.db", "mgug4122a.db", "mi16cod.db", "mirbase.db", "mirna10probe", "miRNAtap", "MLP", "mm24kresogen.db", "MmAgilentDesign026655.db", "moe430a.db", "moe430aprobe", "moe430b.db", "moe430bprobe", "moex10stprobeset.db", "moex10sttranscriptcluster.db", "MoExExonProbesetLocation", "mogene10stprobeset.db", "mogene10sttranscriptcluster.db", "mogene10stv1probe", "mogene11stprobeset.db", "mogene11sttranscriptcluster.db", "mogene20stprobeset.db", "mogene20sttranscriptcluster.db", "mogene21stprobeset.db", "mogene21sttranscriptcluster.db", "mouse.db0", "mouse4302.db", "mouse4302probe", "mouse430a2.db", "mouse430a2probe", "mpedbarray.db", "mta10probeset.db", "mta10transcriptcluster.db", "mu11ksuba.db", "mu11ksubaprobe", "mu11ksubb.db", "mu11ksubbprobe", "Mu15v1.db", "mu19ksuba.db", "mu19ksubb.db", "mu19ksubc.db", "Mu22v3.db", "Mus.musculus", "mwgcod.db", "Norway981.db", "nugohs1a520180.db", "nugohs1a520180probe", "nugomm1a520177.db", "nugomm1a520177probe", "OperonHumanV3.db", "org.Ag.eg.db", "org.At.tair.db", "org.Bt.eg.db", "org.Ce.eg.db", "org.Cf.eg.db", "org.Dm.eg.db", "org.Dr.eg.db", "org.EcK12.eg.db", "org.EcSakai.eg.db", "org.Gg.eg.db", "org.Hs.eg.db", "org.Hs.ipi.db", "org.Mm.eg.db", "org.Mmu.eg.db", "org.Pf.plasmo.db", "org.Pt.eg.db", "org.Rn.eg.db", "org.Sc.sgd.db", "org.Sco.eg.db", "org.Ss.eg.db", "org.Tgondii.eg.db", "org.Xl.eg.db", "OrganismDbi", "paeg1aprobe", "PAnnBuilder", "PANTHER.db", "PartheenMetaData.db", "pathRender", "pedbarrayv10.db", "pedbarrayv9.db", "PFAM.db", "PGSEA", "pig.db0", "plasmodiumanophelesprobe", "POCRCannotation.db", "poplarprobe", "porcine.db", "porcineprobe", "primeviewprobe", "proBAMr", "r10kcod.db", "rae230a.db", "rae230aprobe", "rae230b.db", "rae230bprobe", "raex10stprobeset.db", "raex10sttranscriptcluster.db", "RaExExonProbesetLocation", "ragene10stprobeset.db", "ragene10sttranscriptcluster.db", "ragene10stv1probe", "ragene11stprobeset.db", "ragene11sttranscriptcluster.db", "ragene20stprobeset.db", "ragene20sttranscriptcluster.db", "ragene21stprobeset.db", "ragene21sttranscriptcluster.db", "rat.db0", "rat2302.db", "rat2302probe", "rattoxfxprobe", "Rattus.norvegicus", "reactome.db", "rgu34a.db", "rgu34aprobe", "rgu34b.db", "rgu34bprobe", "rgu34c.db", "rgu34cprobe", "rguatlas4k.db", "rgug4105a.db", "rgug4130a.db", "rgug4131a.db", "rhesus.db0", "rhesusprobe", "ri16cod.db", "riceprobe", "RnAgilentDesign028282.db", "rnu34.db", "rnu34probe", "Roberts2005Annotation.db", "RpsiXML", "rta10probeset.db", "rta10transcriptcluster.db", "rtu34.db", "rtu34probe", "rwgcod.db", "safe", "saureusprobe", "SemDist", "SHDZ.db", "soybeanprobe", "sugarcaneprobe", "targetscan.Hs.eg.db", "targetscan.Mm.eg.db", "test3probe", "tinesath1probe", "tomatoprobe", "topGO", "u133x3p.db", "u133x3pprobe", "vitisviniferaprobe", "wheatprobe", "worm.db0", "xenopus.db0", "xenopuslaevisprobe", "xlaevis.db", "xlaevis2probe", "xtropicalisprobe", "yeast.db0", "yeast2.db", "yeast2probe", "ygs98.db", "ygs98probe", "zebrafish.db", "zebrafish.db0", "zebrafishprobe" ], "importsMe": [ "adme16cod.db", "adSplit", "affycoretools", "affylmGUI", "ag.db", "agcdf", "AllelicImbalance", "annaffy", "AnnotationHub", "AnnotationHubData", "annotatr", "anopheles.db0", "arabidopsis.db0", "ath1121501.db", "ath1121501cdf", "barley1cdf", "beadarray", "biomaRt", "BioNet", "biovizBase", "bovine.db", "bovine.db0", "bovinecdf", "bsubtiliscdf", "bumphunter", "CancerMutationAnalysis", "canine.db", "canine.db0", "canine2.db", "canine2cdf", "caninecdf", "categoryCompare", "ccmap", "celegans.db", "celeganscdf", "cellity", "cheung2010", "chicken.db", "chicken.db0", "chickencdf", "chimp.db0", "ChIPpeakAnno", "ChIPseeker", "citruscdf", "clariomdhumanprobeset.db", "clariomdhumantranscriptcluster.db", "clariomshumanhttranscriptcluster.db", "clariomshumantranscriptcluster.db", "clariomsmousehttranscriptcluster.db", "clariomsmousetranscriptcluster.db", "clariomsrathttranscriptcluster.db", "clariomsrattranscriptcluster.db", "clusterProfiler", "CoCiteStats", "compEpiTools", "cottoncdf", "crisprseekplus", "CrispRVariants", "crossmeta", "csaw", "customProDB", "cyp450cdf", "debrowser", "derfinder", "DeSousa2013", "DO.db", "domainsignatures", "DOSE", "drosgenome1.db", "drosgenome1cdf", "drosophila2.db", "drosophila2cdf", "dSimer", "ecoli2.db", "ecoli2cdf", "ecoliasv2cdf", "ecolicdf", "ecoliK12.db0", "ecoliSakai.db0", "EDASeq", "eegc", "EnrichmentBrowser", "ensembldb", "erma", "ExpressionView", "FDb.FANTOM4.promoters.hg19", "FDb.InfiniumMethylation.hg18", "FDb.InfiniumMethylation.hg19", "FDb.UCSC.snp135common.hg19", "FDb.UCSC.snp137common.hg19", "FDb.UCSC.tRNAs", "fly.db0", "gage", "gahgu133a.db", "gahgu133b.db", "gahgu133plus2.db", "gahgu95av2.db", "gahgu95b.db", "gahgu95c.db", "gahgu95d.db", "gahgu95e.db", "gCMAP", "gCMAPWeb", "genefilter", "geneplotter", "GenVisR", "GGBase", "ggbio", "GGHumanMethCancerPanelv1.db", "GGtools", "GlobalAncova", "globaltest", "GO.db", "GOFunction", "GOpro", "GOSemSim", "goseq", "GOSim", "GOstats", "goTools", "gp53cdf", "gQTLstats", "graphite", "GSEABase", "Gviz", "gwascat", "h10kcod.db", "h20kcod.db", "hcg110.db", "hcg110cdf", "hgfocus.db", "hgfocuscdf", "hgu133a.db", "hgu133a2.db", "hgu133a2cdf", "hgu133acdf", "hgu133atagcdf", "hgu133b.db", "hgu133bcdf", "hgu133plus2.db", "hgu133plus2cdf", "hgu219.db", "hgu219cdf", "hgu95a.db", "hgu95acdf", "hgu95av2.db", "hgu95av2cdf", "hgu95b.db", "hgu95bcdf", "hgu95c.db", "hgu95ccdf", "hgu95d.db", "hgu95dcdf", "hgu95e.db", "hgu95ecdf", "hguatlas13k.db", "hgubeta7.db", "hguDKFZ31.db", "hgug4100a.db", "hgug4101a.db", "hgug4110b.db", "hgug4111a.db", "hgug4112a.db", "hgug4845a.db", "hguqiagenv3.db", "hi16cod.db", "hivprtplus2cdf", "hom.At.inp.db", "hom.Ce.inp.db", "hom.Dm.inp.db", "hom.Dr.inp.db", "hom.Hs.inp.db", "hom.Mm.inp.db", "hom.Rn.inp.db", "hom.Sc.inp.db", "Homo.sapiens", "hs25kresogen.db", "Hs6UG171.db", "HsAgilentDesign026652.db", "Hspec", "hspeccdf", "hta20probeset.db", "hta20transcriptcluster.db", "hthgu133a.db", "hthgu133acdf", "hthgu133b.db", "hthgu133bcdf", "hthgu133pluspmcdf", "htmg430acdf", "htmg430bcdf", "htmg430pmcdf", "htrat230pmcdf", "htratfocuscdf", "HTSanalyzeR", "hu35ksuba.db", "hu35ksubacdf", "hu35ksubb.db", "hu35ksubbcdf", "hu35ksubc.db", "hu35ksubccdf", "hu35ksubd.db", "hu35ksubdcdf", "hu6800.db", "hu6800cdf", "hu6800subacdf", "hu6800subbcdf", "hu6800subccdf", "hu6800subdcdf", "huex10stprobeset.db", "huex10sttranscriptcluster.db", "hugene10stprobeset.db", "hugene10sttranscriptcluster.db", "hugene10stv1cdf", "hugene11stprobeset.db", "hugene11sttranscriptcluster.db", "hugene20stprobeset.db", "hugene20sttranscriptcluster.db", "hugene21stprobeset.db", "hugene21sttranscriptcluster.db", "human.db0", "HuO22.db", "hwgcod.db", "IlluminaHumanMethylation27k.db", "IlluminaHumanMethylation450k.db", "illuminaHumanv1.db", "illuminaHumanv2.db", "illuminaHumanv2BeadID.db", "illuminaHumanv3.db", "illuminaHumanv4.db", "illuminaHumanWGDASLv3.db", "illuminaHumanWGDASLv4.db", "illuminaMousev1.db", "illuminaMousev1p1.db", "illuminaMousev2.db", "illuminaRatv1.db", "indac.db", "InPAS", "interactiveDisplay", "IVAS", "JazaeriMetaData.db", "KEGG.db", "KEGGlincs", "keggorthology", "KEGGprofile", "LAPOINTE.db", "limmaGUI", "lumi", "lumiHumanAll.db", "lumiHumanIDMapping", "lumiMouseAll.db", "lumiMouseIDMapping", "lumiRatAll.db", "lumiRatIDMapping", "m10kcod.db", "m20kcod.db", "MafDb.ESP6500SI.V2.SSA137", "maizecdf", "malaria.db0", "mAPKL", "mdgsa", "medicagocdf", "MeSHDbi", "meshes", "MetaboSignal", "methyAnalysis", "methylumi", "mgu74a.db", "mgu74acdf", "mgu74av2.db", "mgu74av2cdf", "mgu74b.db", "mgu74bcdf", "mgu74bv2.db", "mgu74bv2cdf", "mgu74c.db", "mgu74ccdf", "mgu74cv2.db", "mgu74cv2cdf", "mguatlas5k.db", "mgug4104a.db", "mgug4120a.db", "mgug4121a.db", "mgug4122a.db", "mi16cod.db", "MineICA", "MiRaGE", "mirbase.db", "miRBaseVersions.db", "mirIntegrator", "mirna102xgaincdf", "mirna10cdf", "mirna20cdf", "miRNAmeConverter", "miRNAtap.db", "missMethyl", "mm24kresogen.db", "MmAgilentDesign026655.db", "moe430a.db", "moe430acdf", "moe430b.db", "moe430bcdf", "moex10stprobeset.db", "moex10sttranscriptcluster.db", "mogene10stprobeset.db", "mogene10sttranscriptcluster.db", "mogene10stv1cdf", "mogene11stprobeset.db", "mogene11sttranscriptcluster.db", "mogene20stprobeset.db", "mogene20sttranscriptcluster.db", "mogene21stprobeset.db", "mogene21sttranscriptcluster.db", "mouse.db0", "mouse4302.db", "mouse4302cdf", "mouse430a2.db", "mouse430a2cdf", "mpedbarray.db", "mta10probeset.db", "mta10transcriptcluster.db", "mu11ksuba.db", "mu11ksubacdf", "mu11ksubb.db", "mu11ksubbcdf", "Mu15v1.db", "mu19ksuba.db", "mu19ksubacdf", "mu19ksubb.db", "mu19ksubbcdf", "mu19ksubc.db", "mu19ksubccdf", "Mu22v3.db", "mu6500subacdf", "mu6500subbcdf", "mu6500subccdf", "mu6500subdcdf", "Mus.musculus", "mvGST", "mwgcod.db", "NanoStringQCPro", "Norway981.db", "nugohs1a520180.db", "nugohs1a520180cdf", "nugomm1a520177.db", "nugomm1a520177cdf", "OperonHumanV3.db", "org.Ag.eg.db", "org.At.tair.db", "org.Bt.eg.db", "org.Ce.eg.db", "org.Cf.eg.db", "org.Dm.eg.db", "org.Dr.eg.db", "org.EcK12.eg.db", "org.EcSakai.eg.db", "org.Gg.eg.db", "org.Hs.eg.db", "org.Hs.ipi.db", "org.Mm.eg.db", "org.Mmu.eg.db", "org.Pf.plasmo.db", "org.Pt.eg.db", "org.Rn.eg.db", "org.Sc.sgd.db", "org.Sco.eg.db", "org.Ss.eg.db", "org.Tgondii.eg.db", "org.Xl.eg.db", "PADOG", "paeg1acdf", "PAnnBuilder", "PartheenMetaData.db", "pathview", "pcaExplorer", "pcaGoPromoter", "PCpheno", "pedbarrayv10.db", "pedbarrayv9.db", "PFAM.db", "PGA", "phenoTest", "pig.db0", "plasmodiumanophelescdf", "POCRCannotation.db", "PolyPhen.Hsapiens.dbSNP131", "poplarcdf", "porcine.db", "porcinecdf", "ppiData", "primeviewcdf", "pwOmics", "qpgraph", "r10kcod.db", "rae230a.db", "rae230acdf", "rae230b.db", "rae230bcdf", "raex10stprobeset.db", "raex10sttranscriptcluster.db", "ragene10stprobeset.db", "ragene10sttranscriptcluster.db", "ragene10stv1cdf", "ragene11stprobeset.db", "ragene11sttranscriptcluster.db", "ragene20stprobeset.db", "ragene20sttranscriptcluster.db", "ragene21stprobeset.db", "ragene21sttranscriptcluster.db", "rat.db0", "rat2302.db", "rat2302cdf", "rattoxfxcdf", "Rattus.norvegicus", "RCAS", "rCGH", "reactome.db", "ReactomePA", "REDseq", "ReportingTools", "rgsepd", "rgu34a.db", "rgu34acdf", "rgu34b.db", "rgu34bcdf", "rgu34c.db", "rgu34ccdf", "rguatlas4k.db", "rgug4105a.db", "rgug4130a.db", "rgug4131a.db", "rhesus.db0", "rhesuscdf", "ri16cod.db", "ricecdf", "RmiR.Hs.miRNA", "RmiR.hsa", "RnAgilentDesign028282.db", "rnu34.db", "rnu34cdf", "Roberts2005Annotation.db", "rta10probeset.db", "rta10transcriptcluster.db", "rTRM", "rtu34.db", "rtu34cdf", "rwgcod.db", "saureuscdf", "ScISI", "SGSeq", "SHDZ.db", "SIFT.Hsapiens.dbSNP132", "SIFT.Hsapiens.dbSNP137", "SLGI", "SMITE", "soybeancdf", "SpidermiR", "StarBioTrek", "sugarcanecdf", "SVM2CRM", "targetscan.Hs.eg.db", "targetscan.Mm.eg.db", "test1cdf", "test2cdf", "test3cdf", "tigre", "tomatocdf", "ToPASeq", "trackViewer", "TxDb.Athaliana.BioMart.plantsmart22", "TxDb.Athaliana.BioMart.plantsmart25", "TxDb.Athaliana.BioMart.plantsmart28", "TxDb.Btaurus.UCSC.bosTau8.refGene", "TxDb.Celegans.UCSC.ce11.refGene", "TxDb.Celegans.UCSC.ce6.ensGene", "TxDb.Cfamiliaris.UCSC.canFam3.refGene", "TxDb.Dmelanogaster.UCSC.dm3.ensGene", "TxDb.Dmelanogaster.UCSC.dm6.ensGene", "TxDb.Drerio.UCSC.danRer10.refGene", "TxDb.Ggallus.UCSC.galGal4.refGene", "TxDb.Hsapiens.BioMart.igis", "TxDb.Hsapiens.UCSC.hg18.knownGene", "TxDb.Hsapiens.UCSC.hg19.knownGene", "TxDb.Hsapiens.UCSC.hg19.lincRNAsTranscripts", "TxDb.Hsapiens.UCSC.hg38.knownGene", "TxDb.Mmulatta.UCSC.rheMac3.refGene", "TxDb.Mmulatta.UCSC.rheMac8.refGene", "TxDb.Mmusculus.UCSC.mm10.ensGene", "TxDb.Mmusculus.UCSC.mm10.knownGene", "TxDb.Mmusculus.UCSC.mm9.knownGene", "TxDb.Ptroglodytes.UCSC.panTro4.refGene", "TxDb.Rnorvegicus.BioMart.igis", "TxDb.Rnorvegicus.UCSC.rn4.ensGene", "TxDb.Rnorvegicus.UCSC.rn5.refGene", "TxDb.Rnorvegicus.UCSC.rn6.refGene", "TxDb.Scerevisiae.UCSC.sacCer2.sgdGene", "TxDb.Scerevisiae.UCSC.sacCer3.sgdGene", "TxDb.Sscrofa.UCSC.susScr3.refGene", "u133aaofav2cdf", "u133x3p.db", "u133x3pcdf", "UniProt.ws", "VariantAnnotation", "VariantFiltering", "vitisviniferacdf", "wheatcdf", "worm.db0", "xenopus.db0", "xenopuslaeviscdf", "xlaevis.db", "xlaevis2cdf", "xtropicaliscdf", "ye6100subacdf", "ye6100subbcdf", "ye6100subccdf", "ye6100subdcdf", "yeast.db0", "yeast2.db", "yeast2cdf", "ygs98.db", "ygs98cdf", "zebrafish.db", "zebrafish.db0", "zebrafishcdf" ], "suggestsMe": [ "BiocCaseStudies", "BiocGenerics", "DEGreport", "esetVis", "FGNet", "fgsea", "gCrisprTools", "geecc", "GeneAnswers", "GeneRegionScan", "GenomicRanges", "limma", "miRLAB", "MmPalateMiRNA", "oligo", "oligo", "oneChannelGUI", "piano", "Pigengene", "pRoloc", "qcmetrics", "R3CPET", "recount", "sigPathway", "SummarizedExperiment" ] }, "AnnotationForge": { "Package": "AnnotationForge", "Version": "1.16.1", "Depends": [ "R (>= 2.7.0)", "methods", "utils", "BiocGenerics (>= 0.15.10)", "Biobase (>= 1.17.0)", "AnnotationDbi (>= 1.33.14)" ], "Imports": [ "DBI", "RSQLite", "XML", "S4Vectors", "RCurl" ], "Suggests": [ "biomaRt", "httr", "GenomeInfoDb", "Biostrings", "affy", "hgu95av2.db", "human.db0", "org.Hs.eg.db", "Homo.sapiens", "hom.Hs.inp.db", "GO.db", "BiocStyle", "knitr" ], "License": "Artistic-2.0", "MD5sum": "8cbc423604c2274e3f3e06372e3b368d", "NeedsCompilation": "no", "Title": "Code for Building Annotation Database Packages", "Description": "Provides code for generating Annotation packages and their databases. Packages produced are intended to be used with AnnotationDbi.", "biocViews": [ "Annotation", "Infrastructure", "Software" ], "Author": "Marc Carlson, Herve Pages", "Maintainer": "Bioconductor Package Maintainer ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/AnnotationForge_1.16.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/AnnotationForge_1.16.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/AnnotationForge_1.16.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/AnnotationForge_1.16.1.tgz", "vignettes": [ "vignettes/AnnotationForge/inst/doc/makeProbePackage.pdf", "vignettes/AnnotationForge/inst/doc/MakingNewAnnotationPackages.pdf", "vignettes/AnnotationForge/inst/doc/SQLForge.pdf" ], "vignetteTitles": [ "Creating probe packages", "AnnotationForge: Creating select Interfaces for custom Annotation resources", "SQLForge: An easy way to create a new annotation package with a standard database schema." ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/AnnotationForge/inst/doc/makeProbePackage.R", "vignettes/AnnotationForge/inst/doc/MakingNewAnnotationPackages.R", "vignettes/AnnotationForge/inst/doc/MakingNewOrganismPackages.R", "vignettes/AnnotationForge/inst/doc/SQLForge.R" ], "htmlDocs": [ "vignettes/AnnotationForge/inst/doc/MakingNewOrganismPackages.html" ], "htmlTitles": [ "Making New Organism Packages" ], "importsMe": [ "AnnotationHubData", "GGHumanMethCancerPanelv1.db", "GOstats" ], "suggestsMe": [ "AnnotationDbi", "AnnotationHub" ] }, "AnnotationFuncs": { "Package": "AnnotationFuncs", "Version": "1.24.0", "Depends": [ "R (>= 2.7.0)", "AnnotationDbi" ], "Imports": [ "DBI" ], "Suggests": [ "org.Bt.eg.db", "GO.db", "org.Hs.eg.db", "hom.Hs.inp.db" ], "License": "GPL-2", "MD5sum": "f709876dd4917cfd337a3ab01b4e76f3", "NeedsCompilation": "no", "Title": "Annotation translation functions", "Description": "Functions for handling translating between different identifieres using the Biocore Data Team data-packages (e.g. org.Bt.eg.db).", "biocViews": [ "AnnotationData", "Software" ], "Author": "Stefan McKinnon Edwards ", "Maintainer": "Stefan McKinnon Edwards ", "URL": "http://www.iysik.com/index.php?page=annotation-functions", "source.ver": "src/contrib/AnnotationFuncs_1.24.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/AnnotationFuncs_1.24.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/AnnotationFuncs_1.24.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/AnnotationFuncs_1.24.0.tgz", "vignettes": [ "vignettes/AnnotationFuncs/inst/doc/AnnotationFuncsUserguide.pdf" ], "vignetteTitles": [ "Annotation mapping functions" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/AnnotationFuncs/inst/doc/AnnotationFuncsUserguide.R" ], "importsMe": [ "bioCancer" ] }, "AnnotationHub": { "Package": "AnnotationHub", "Version": "2.6.5", "Depends": [ "BiocGenerics (>= 0.15.10)" ], "Imports": [ "utils", "methods", "grDevices", "RSQLite", "BiocInstaller", "AnnotationDbi", "S4Vectors", "interactiveDisplayBase", "httr", "yaml" ], "Suggests": [ "IRanges", "GenomicRanges", "GenomeInfoDb", "VariantAnnotation", "Rsamtools", "rtracklayer", "BiocStyle", "knitr", "AnnotationForge", "rBiopaxParser", "RUnit", "GenomicFeatures", "MSnbase", "mzR", "Biostrings", "SummarizedExperiment" ], "Enhances": [ "AnnotationHubData" ], "License": "Artistic-2.0", "MD5sum": "c19ef29f4826ff2357685a44babd1cbc", "NeedsCompilation": "yes", "Title": "Client to access AnnotationHub resources", "Description": "This package provides a client for the Bioconductor AnnotationHub web resource. The AnnotationHub web resource provides a central location where genomic files (e.g., VCF, bed, wig) and other resources from standard locations (e.g., UCSC, Ensembl) can be discovered. The resource includes metadata about each resource, e.g., a textual description, tags, and date of modification. The client creates and manages a local cache of files retrieved by the user, helping with quick and reproducible access.", "biocViews": [ "DataImport", "GUI", "Infrastructure", "Software", "ThirdPartyClient" ], "Author": "Martin Morgan [cre], Marc Carlson [ctb], Dan Tenenbaum [ctb], Sonali Arora [ctb]", "Maintainer": "Bioconductor Package Maintainer ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/AnnotationHub_2.6.5.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/AnnotationHub_2.6.5.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/AnnotationHub_2.6.5.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/AnnotationHub_2.6.5.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/AnnotationHub/inst/doc/AnnotationHub-HOWTO.R", "vignettes/AnnotationHub/inst/doc/AnnotationHub.R" ], "htmlDocs": [ "vignettes/AnnotationHub/inst/doc/AnnotationHub-HOWTO.html", "vignettes/AnnotationHub/inst/doc/AnnotationHub.html" ], "htmlTitles": [ "AnnotationHub: AnnotationHub HOW TO's", "AnnotationHub: Access the AnnotationHub Web Service" ], "dependsOnMe": [ "AnnotationHubData", "curatedMetagenomicData", "ExperimentHub", "ProteomicsAnnotationHubData", "RefNet" ], "importsMe": [ "alpineData", "alternativeSplicingEvents.hg19", "annotatr", "ensembldb", "grasp2db", "gwascat", "psichomics", "pwOmics" ], "suggestsMe": [ "Chicago", "CINdex", "clusterProfiler", "DNAshapeR", "dupRadar", "GenomicRanges", "GOSemSim", "MSnbase", "OrganismDbi", "Pbase", "VariantAnnotation" ] }, "AnnotationHubData": { "Package": "AnnotationHubData", "Version": "1.4.1", "Depends": [ "R (>= 3.2.2)", "methods", "utils", "S4Vectors (>= 0.7.21)", "IRanges (>= 2.3.23)", "GenomicRanges", "AnnotationHub" ], "Imports": [ "GenomicFeatures", "Rsamtools", "rtracklayer", "BiocGenerics", "jsonlite", "BiocInstaller", "httr", "AnnotationDbi", "Biobase", "Biostrings", "DBI", "GEOquery", "GenomeInfoDb", "OrganismDbi", "RSQLite", "rBiopaxParser", "AnnotationForge", "futile.logger (>= 1.3.0)", "XML", "xml2", "curl" ], "Suggests": [ "RUnit", "knitr", "RMySQL", "BiocStyle", "grasp2db" ], "License": "Artistic-2.0", "MD5sum": "28f4bbecf9aa35a67568e7f5ec8c0da4", "NeedsCompilation": "no", "Title": "Transform public data resources into Bioconductor Data Structures", "Description": "These recipes convert a wide variety and a growing number of public bioinformatic data sets into easily-used standard Bioconductor data structures.", "biocViews": [ "DataImport", "Software" ], "Author": "Martin Morgan [ctb], Marc Carlson [ctb], Dan Tenenbaum [ctb], Sonali Arora [ctb], Paul Shannon [ctb], Bioconductor Package Maintainer [cre]", "Maintainer": "Bioconductor Package Maintainer ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/AnnotationHubData_1.4.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/AnnotationHubData_1.4.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/AnnotationHubData_1.4.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/AnnotationHubData_1.4.1.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/AnnotationHubData/inst/doc/IntroductionToAnnotationHubData.R" ], "htmlDocs": [ "vignettes/AnnotationHubData/inst/doc/IntroductionToAnnotationHubData.html" ], "htmlTitles": [ "Introduction to AnnotationHubData" ], "dependsOnMe": [ "ExperimentHubData", "ProteomicsAnnotationHubData" ] }, "annotationTools": { "Package": "annotationTools", "Version": "1.48.0", "Imports": [ "Biobase", "stats" ], "License": "GPL", "MD5sum": "d8395a287e1330c2002691468e544e08", "NeedsCompilation": "no", "Title": "Annotate microarrays and perform cross-species gene expression analyses using flat file databases.", "Description": "Functions to annotate microarrays, find orthologs, and integrate heterogeneous gene expression profiles using annotation and other molecular biology information available as flat file database (plain text files).", "biocViews": [ "Annotation", "Microarray", "Software" ], "Author": "Alexandre Kuhn ", "Maintainer": "Alexandre Kuhn ", "source.ver": "src/contrib/annotationTools_1.48.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/annotationTools_1.48.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/annotationTools_1.48.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/annotationTools_1.48.0.tgz", "vignettes": [ "vignettes/annotationTools/inst/doc/annotationTools.pdf" ], "vignetteTitles": [ "annotationTools Overview" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/annotationTools/inst/doc/annotationTools.R" ], "importsMe": [ "DOQTL" ] }, "annotatr": { "Package": "annotatr", "Version": "1.0.3", "Depends": [ "R (>= 3.3.0)" ], "Imports": [ "AnnotationDbi", "AnnotationHub", "dplyr", "GenomicFeatures", "GenomicRanges", "GenomeInfoDb (>= 1.10.3)", "ggplot2", "IRanges", "methods", "org.Dm.eg.db", "org.Hs.eg.db", "org.Mm.eg.db", "org.Rn.eg.db", "readr", "regioneR", "reshape2", "rtracklayer", "S4Vectors", "stats", "TxDb.Dmelanogaster.UCSC.dm3.ensGene", "TxDb.Dmelanogaster.UCSC.dm6.ensGene", "TxDb.Hsapiens.UCSC.hg19.knownGene", "TxDb.Hsapiens.UCSC.hg38.knownGene", "TxDb.Mmusculus.UCSC.mm9.knownGene", "TxDb.Mmusculus.UCSC.mm10.knownGene", "TxDb.Rnorvegicus.UCSC.rn4.ensGene", "TxDb.Rnorvegicus.UCSC.rn5.refGene", "TxDb.Rnorvegicus.UCSC.rn6.refGene", "utils" ], "Suggests": [ "BiocStyle", "devtools", "knitr", "rmarkdown", "roxygen2", "testthat" ], "License": "GPL-3", "MD5sum": "ccc5adb46cc83cc372e1044bb65346a4", "NeedsCompilation": "no", "Title": "Annotation of Genomic Regions to Genomic Annotations", "Description": "Given a set of genomic sites/regions (e.g. ChIP-seq peaks, CpGs, differentially methylated CpGs or regions, SNPs, etc.) it is often of interest to investigate the intersecting genomic annotations. Such annotations include those relating to gene models (promoters, 5'UTRs, exons, introns, and 3'UTRs), CpGs (CpG islands, CpG shores, CpG shelves), or regulatory sequences such as enhancers. The annotatr package provides an easy way to summarize and visualize the intersection of genomic sites/regions with genomic annotations.", "biocViews": [ "Annotation", "FunctionalGenomics", "GenomeAnnotation", "Software", "Visualization" ], "Author": "Raymond G. Cavalcante [aut, cre], Maureen A. Sartor [ths]", "Maintainer": "Raymond G. Cavalcante ", "VignetteBuilder": "knitr", "BugReports": "https://www.github.com/rcavalcante/annotatr/issues", "source.ver": "src/contrib/annotatr_1.0.3.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/annotatr_1.0.3.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/annotatr_1.0.3.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/annotatr_1.0.3.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/annotatr/inst/doc/annotatr-vignette.R" ], "htmlDocs": [ "vignettes/annotatr/inst/doc/annotatr-vignette.html" ], "htmlTitles": [ "Vignette Title" ] }, "anota": { "Package": "anota", "Version": "1.22.0", "Depends": [ "qvalue" ], "Imports": [ "multtest", "qvalue" ], "License": "GPL-3", "MD5sum": "b917630b2767f8f5cf80f10e4cdf0145", "NeedsCompilation": "no", "Title": "ANalysis Of Translational Activity (ANOTA).", "Description": "Genome wide studies of translational control is emerging as a tool to study verious biological conditions. The output from such analysis is both the mRNA level (e.g. cytosolic mRNA level) and the levl of mRNA actively involved in translation (the actively translating mRNA level) for each mRNA. The standard analysis of such data strives towards identifying differential translational between two or more sample classes - i.e. differences in actively translated mRNA levels that are independent of underlying differences in cytosolic mRNA levels. This package allows for such analysis using partial variances and the random variance model. As 10s of thousands of mRNAs are analyzed in parallell the library performs a number of tests to assure that the data set is suitable for such analysis.", "biocViews": [ "DifferentialExpression", "GeneExpression", "Microarray", "Sequencing", "Software" ], "Author": "Ola Larsson , Nahum Sonenberg , Robert Nadon ", "Maintainer": "Ola Larsson ", "source.ver": "src/contrib/anota_1.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/anota_1.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/anota_1.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/anota_1.22.0.tgz", "vignettes": [ "vignettes/anota/inst/doc/anota.pdf" ], "vignetteTitles": [ "ANalysis Of Translational Activity (anota)" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/anota/inst/doc/anota.R" ], "dependsOnMe": [ "tRanslatome" ] }, "antiProfiles": { "Package": "antiProfiles", "Version": "1.14.0", "Depends": [ "R (>= 3.0)", "matrixStats (>= 0.50.0)", "methods (>= 2.14)", "locfit (>= 1.5)" ], "Suggests": [ "antiProfilesData", "RColorBrewer" ], "License": "Artistic-2.0", "MD5sum": "9e3d405c92d5accbb16aabc057db6afd", "NeedsCompilation": "no", "Title": "Implementation of gene expression anti-profiles", "Description": "Implements gene expression anti-profiles as described in Corrada Bravo et al., BMC Bioinformatics 2012, 13:272 doi:10.1186/1471-2105-13-272.", "biocViews": [ "Classification", "GeneExpression", "Software" ], "Author": "Hector Corrada Bravo, Rafael A. Irizarry and Jeffrey T. Leek", "Maintainer": "Hector Corrada Bravo ", "URL": "https://github.com/HCBravoLab/antiProfiles", "source.ver": "src/contrib/antiProfiles_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/antiProfiles_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/antiProfiles_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/antiProfiles_1.14.0.tgz", "vignettes": [ "vignettes/antiProfiles/inst/doc/antiProfiles.pdf" ], "vignetteTitles": [ "Introduction to antiProfiles" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/antiProfiles/inst/doc/antiProfiles.R" ] }, "apComplex": { "Package": "apComplex", "Version": "2.40.0", "Depends": [ "R (>= 2.10)", "graph", "RBGL" ], "Imports": [ "Rgraphviz", "stats", "org.Sc.sgd.db" ], "License": "LGPL", "MD5sum": "98d55585f38ba25d8920aba50a65f935", "NeedsCompilation": "no", "Title": "Estimate protein complex membership using AP-MS protein data", "Description": "Functions to estimate a bipartite graph of protein complex membership using AP-MS data.", "biocViews": [ "GraphAndNetwork", "MassSpectrometry", "NetworkInference", "Software" ], "Author": "Denise Scholtens ", "Maintainer": "Denise Scholtens ", "source.ver": "src/contrib/apComplex_2.40.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/apComplex_2.40.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/apComplex_2.40.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/apComplex_2.40.0.tgz", "vignettes": [ "vignettes/apComplex/inst/doc/apComplex.pdf" ], "vignetteTitles": [ "apComplex" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/apComplex/inst/doc/apComplex.R" ], "dependsOnMe": [ "ScISI" ], "suggestsMe": [ "BiocCaseStudies" ] }, "aroma.light": { "Package": "aroma.light", "Version": "3.4.0", "Depends": [ "R (>= 2.15.2)" ], "Imports": [ "R.methodsS3 (>= 1.7.1)", "R.oo (>= 1.20.0)", "R.utils (>= 2.4.0)", "matrixStats (>= 0.50.2)" ], "Suggests": [ "princurve (>= 1.1-12)" ], "License": "GPL (>= 2)", "MD5sum": "8e28dc69064f12b22dd5f08f0aadb974", "NeedsCompilation": "no", "Title": "Light-Weight Methods for Normalization and Visualization of Microarray Data using Only Basic R Data Types", "Description": "Methods for microarray analysis that take basic data types such as matrices and lists of vectors. These methods can be used standalone, be utilized in other packages, or be wrapped up in higher-level classes.", "biocViews": [ "Infrastructure", "Microarray", "MultiChannel", "OneChannel", "Preprocessing", "Software", "TwoChannel", "Visualization" ], "Author": "Henrik Bengtsson [aut, cre, cph], Pierre Neuvial [ctb]", "Maintainer": "Henrik Bengtsson ", "URL": "https://github.com/HenrikBengtsson/aroma.light, http://www.aroma-project.org", "BugReports": "https://github.com/HenrikBengtsson/aroma.light/issues", "source.ver": "src/contrib/aroma.light_3.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/aroma.light_3.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/aroma.light_3.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/aroma.light_3.4.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "importsMe": [ "EDASeq" ], "suggestsMe": [ "TIN" ] }, "ArrayExpress": { "Package": "ArrayExpress", "Version": "1.34.0", "Depends": [ "R (>= 2.9.0)", "Biobase (>= 2.4.0)" ], "Imports": [ "XML", "oligo", "limma" ], "Suggests": [ "affy" ], "License": "Artistic-2.0", "MD5sum": "596bc81db538f194072222fe13fc3ec3", "NeedsCompilation": "no", "Title": "Access the ArrayExpress Microarray Database at EBI and build Bioconductor data structures: ExpressionSet, AffyBatch, NChannelSet", "Description": "Access the ArrayExpress Repository at EBI and build Bioconductor data structures: ExpressionSet, AffyBatch, NChannelSet", "biocViews": [ "DataImport", "Microarray", "OneChannel", "Software", "TwoChannel" ], "Author": "Audrey Kauffmann, Ibrahim Emam, Michael Schubert", "Maintainer": "Ugis Sarkans ", "source.ver": "src/contrib/ArrayExpress_1.34.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ArrayExpress_1.34.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ArrayExpress_1.34.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ArrayExpress_1.34.0.tgz", "vignettes": [ "vignettes/ArrayExpress/inst/doc/ArrayExpress.pdf" ], "vignetteTitles": [ "ArrayExpress: Import and convert ArrayExpress data sets into R object" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ArrayExpress/inst/doc/ArrayExpress.R" ], "dependsOnMe": [ "DrugVsDisease" ], "suggestsMe": [ "gCMAPWeb", "Hiiragi2013" ] }, "ArrayExpressHTS": { "Package": "ArrayExpressHTS", "Version": "1.24.0", "Depends": [ "sampling", "Rsamtools (>= 1.19.36)", "snow" ], "Imports": [ "Biobase", "BiocGenerics", "Biostrings", "DESeq", "GenomicRanges", "Hmisc", "IRanges", "R2HTML", "RColorBrewer", "Rsamtools", "ShortRead", "XML", "biomaRt", "edgeR", "grDevices", "graphics", "methods", "rJava", "stats", "svMisc", "utils", "sendmailR", "bitops" ], "LinkingTo": [ "Rsamtools" ], "License": "Artistic License 2.0", "MD5sum": "a3aa8a654b7110e3d21f8b74f211bb5b", "NeedsCompilation": "yes", "Title": "ArrayExpress High Throughput Sequencing Processing Pipeline", "Description": "RNA-Seq processing pipeline for public ArrayExpress experiments or local datasets", "biocViews": [ "RNASeq", "Sequencing", "Software" ], "Author": "Angela Goncalves, Andrew Tikhonov", "Maintainer": "Angela Goncalves , Andrew Tikhonov ", "source.ver": "src/contrib/ArrayExpressHTS_1.24.0.tar.gz", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ArrayExpressHTS_1.24.0.tgz", "vignettes": [ "vignettes/ArrayExpressHTS/inst/doc/ArrayExpressHTS.pdf" ], "vignetteTitles": [ "ArrayExpressHTS: RNA-Seq Pipeline for transcription profiling experiments" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ArrayExpressHTS/inst/doc/ArrayExpressHTS.R" ] }, "arrayMvout": { "Package": "arrayMvout", "Version": "1.32.0", "Depends": [ "R (>= 2.6.0)", "tools", "methods", "utils", "parody", "Biobase", "affy", "lumi" ], "Imports": [ "simpleaffy", "mdqc", "affyContam" ], "Suggests": [ "MAQCsubset", "mvoutData", "lumiBarnes", "affyPLM", "affydata", "hgu133atagcdf" ], "License": "Artistic-2.0", "MD5sum": "b03a66949b8e9553e0e9612d0a35838f", "NeedsCompilation": "no", "Title": "multivariate outlier detection for expression array QA", "Description": "This package supports the application of diverse quality metrics to AffyBatch instances, summarizing these metrics via PCA, and then performing parametric outlier detection on the PCs to identify aberrant arrays with a fixed Type I error rate", "biocViews": [ "Infrastructure", "Microarray", "QualityControl", "Software" ], "Author": "Z. Gao, A. Asare, R. Wang, V. Carey", "Maintainer": "V. Carey ", "source.ver": "src/contrib/arrayMvout_1.32.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/arrayMvout_1.32.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/arrayMvout_1.32.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/arrayMvout_1.32.0.tgz", "vignettes": [ "vignettes/arrayMvout/inst/doc/arrayMvout.pdf" ], "vignetteTitles": [ "arrayMvout -- multivariate outlier algorithm for expression arrays" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/arrayMvout/inst/doc/arrayMvout.R" ] }, "arrayQuality": { "Package": "arrayQuality", "Version": "1.52.0", "Depends": [ "R (>= 2.2.0)" ], "Imports": [ "graphics", "grDevices", "grid", "gridBase", "hexbin", "limma", "marray", "methods", "RColorBrewer", "stats", "utils" ], "Suggests": [ "mclust", "MEEBOdata", "HEEBOdata" ], "License": "LGPL", "MD5sum": "7e0a162bb2757e04fa588d8810f9d6fe", "NeedsCompilation": "no", "Title": "Assessing array quality on spotted arrays", "Description": "Functions for performing print-run and array level quality assessment.", "biocViews": [ "Microarray", "QualityControl", "Software", "TwoChannel", "Visualization" ], "Author": "Agnes Paquet and Jean Yee Hwa Yang ", "Maintainer": "Agnes Paquet ", "URL": "http://arrays.ucsf.edu/", "source.ver": "src/contrib/arrayQuality_1.52.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/arrayQuality_1.52.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/arrayQuality_1.52.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/arrayQuality_1.52.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false }, "arrayQualityMetrics": { "Package": "arrayQualityMetrics", "Version": "3.30.0", "Imports": [ "affy", "affyPLM (>= 1.27.3)", "beadarray", "Biobase", "Cairo (>= 1.4-6)", "genefilter", "graphics", "grDevices", "grid", "gridSVG (>= 1.4-3)", "Hmisc", "hwriter", "lattice", "latticeExtra", "limma", "methods", "RColorBrewer", "setRNG", "stats", "SVGAnnotation (>= 0.9-0)", "utils", "vsn (>= 3.23.3)", "XML" ], "Suggests": [ "ALLMLL", "CCl4", "BiocStyle", "knitr" ], "License": "LGPL (>= 2)", "MD5sum": "5b12789f63770a5e170e8b6cd3702c51", "NeedsCompilation": "no", "Title": "Quality metrics report for microarray data sets", "Description": "This package generates microarray quality metrics reports for data in Bioconductor microarray data containers (ExpressionSet, NChannelSet, AffyBatch). One and two color array platforms are supported.", "biocViews": [ "Microarray", "OneChannel", "QualityControl", "ReportWriting", "Software", "TwoChannel" ], "Author": "Audrey Kauffmann, Wolfgang Huber", "Maintainer": "Audrey Kauffmann ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/arrayQualityMetrics_3.30.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/arrayQualityMetrics_3.30.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/arrayQualityMetrics_3.30.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/arrayQualityMetrics_3.30.0.tgz", "vignettes": [ "vignettes/arrayQualityMetrics/inst/doc/aqm.pdf", "vignettes/arrayQualityMetrics/inst/doc/arrayQualityMetrics.pdf" ], "vignetteTitles": [ "Advanced topics: Customizing arrayQualityMetrics reports and programmatic processing of the output", "Introduction: microarray quality assessment with arrayQualityMetrics" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/arrayQualityMetrics/inst/doc/aqm.R", "vignettes/arrayQualityMetrics/inst/doc/arrayQualityMetrics.R" ], "importsMe": [ "EGAD" ] }, "ArrayTools": { "Package": "ArrayTools", "Version": "1.34.0", "Depends": [ "R (>= 2.7.0)", "affy (>= 1.23.4)", "Biobase (>= 2.5.5)", "methods" ], "Imports": [ "affy", "Biobase", "graphics", "grDevices", "limma", "methods", "stats", "utils", "xtable" ], "Suggests": [ "simpleaffy", "R2HTML", "affydata", "affyPLM", "genefilter", "annaffy", "gcrma", "hugene10sttranscriptcluster.db" ], "License": "LGPL (>= 2.0)", "MD5sum": "d05dc675980ef3f9c5f5894e84ade223", "NeedsCompilation": "no", "Title": "geneChip Analysis Package", "Description": "This package is designed to provide solutions for quality assessment and to detect differentially expressed genes for the Affymetrix GeneChips, including both 3' -arrays and gene 1.0-ST arrays. The package generates comprehensive analysis reports in HTML format. Hyperlinks on the report page will lead to a series of QC plots, processed data, and differentially expressed gene lists. Differentially expressed genes are reported in tabular format with annotations hyperlinked to online biological databases.", "biocViews": [ "Annotation", "DifferentialExpression", "Microarray", "OneChannel", "Preprocessing", "QualityControl", "ReportWriting", "Software", "StatisticalMethod", "Visualization" ], "Author": "Xiwei Wu, Arthur Li", "Maintainer": "Arthur Li ", "source.ver": "src/contrib/ArrayTools_1.34.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ArrayTools_1.34.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ArrayTools_1.34.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ArrayTools_1.34.0.tgz", "vignettes": [ "vignettes/ArrayTools/inst/doc/ArrayTools.pdf" ], "vignetteTitles": [ "1. Primer" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ArrayTools/inst/doc/ArrayTools.R" ] }, "ArrayTV": { "Package": "ArrayTV", "Version": "1.12.0", "Depends": [ "R (>= 2.14)" ], "Imports": [ "methods", "foreach", "S4Vectors (>= 0.9.25)", "DNAcopy", "oligoClasses (>= 1.21.3)" ], "Suggests": [ "RColorBrewer", "crlmm", "ff", "BSgenome.Hsapiens.UCSC.hg18", "BSgenome.Hsapiens.UCSC.hg19", "lattice", "latticeExtra", "RUnit", "BiocGenerics" ], "Enhances": [ "doMC", "doSNOW", "doParallel" ], "License": "GPL (>= 2)", "MD5sum": "96307adc39396050f82a1482495bad3a", "NeedsCompilation": "no", "Title": "Implementation of wave correction for arrays", "Description": "Wave correction for genotyping and copy number arrays", "biocViews": [ "CopyNumberVariation", "Software" ], "Author": "Eitan Halper-Stromberg", "Maintainer": "Eitan Halper-Stromberg ", "source.ver": "src/contrib/ArrayTV_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ArrayTV_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ArrayTV_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ArrayTV_1.12.0.tgz", "vignettes": [ "vignettes/ArrayTV/inst/doc/ArrayTV.pdf" ], "vignetteTitles": [ "ArrayTV Vignette" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ArrayTV/inst/doc/ArrayTV.R" ], "suggestsMe": [ "VanillaICE" ] }, "ARRmNormalization": { "Package": "ARRmNormalization", "Version": "1.14.0", "Depends": [ "R (>= 2.15.1)", "ARRmData" ], "License": "Artistic-2.0", "MD5sum": "6e691ea88f981a38da1d4eba6d5c5be8", "NeedsCompilation": "no", "Title": "Adaptive Robust Regression normalization for Illumina methylation data", "Description": "Perform the Adaptive Robust Regression method (ARRm) for the normalization of methylation data from the Illumina Infinium HumanMethylation 450k assay.", "biocViews": [ "DNAMethylation", "Microarray", "Preprocessing", "Software", "TwoChannel" ], "Author": "Jean-Philippe Fortin, Celia M.T. Greenwood, Aurelie Labbe.", "Maintainer": "Jean-Philippe Fortin ", "source.ver": "src/contrib/ARRmNormalization_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ARRmNormalization_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ARRmNormalization_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ARRmNormalization_1.14.0.tgz", "vignettes": [ "vignettes/ARRmNormalization/inst/doc/ARRmNormalization.pdf" ], "vignetteTitles": [ "ARRmNormalization" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ARRmNormalization/inst/doc/ARRmNormalization.R" ] }, "ASAFE": { "Package": "ASAFE", "Version": "1.0.0", "Depends": [ "R (>= 3.2)" ], "Suggests": [ "knitr", "testthat" ], "License": "Artistic-2.0", "MD5sum": "95c7030231ed950b25c420c98bfd6255", "NeedsCompilation": "no", "Title": "Ancestry Specific Allele Frequency Estimation", "Description": "Given admixed individuals' bi-allelic SNP genotypes and ancestry pairs (where each ancestry can take one of three values) for multiple SNPs, perform an EM algorithm to deal with the fact that SNP genotypes are unphased with respect to ancestry pairs, in order to estimate ancestry-specific allele frequencies for all SNPs.", "biocViews": [ "BiomedicalInformatics", "ExperimentalDesign", "Genetics", "GenomeWideAssociation", "LinkageDisequilibrium", "SNP", "Software" ], "Author": "Qian Zhang ", "Maintainer": "Qian Zhang ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/ASAFE_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ASAFE_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ASAFE_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ASAFE_1.0.0.tgz", "vignettes": [ "vignettes/ASAFE/inst/doc/ASAFE.pdf" ], "vignetteTitles": [ "ASAFE (Ancestry Specific Allele Frequency Estimation)" ], "hasREADME": true, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ASAFE/inst/doc/ASAFE.R" ] }, "ASEB": { "Package": "ASEB", "Version": "1.18.0", "Depends": [ "R (>= 2.8.0)", "methods" ], "Imports": [ "graphics", "methods", "utils" ], "License": "GPL (>= 3)", "Archs": "i386, x64", "MD5sum": "63b9a05ce0069401dcb55bfbbfc49619", "NeedsCompilation": "yes", "Title": "Predict Acetylated Lysine Sites", "Description": "ASEB is an R package to predict lysine sites that can be acetylated by a specific KAT-family.", "biocViews": [ "Proteomics", "Software" ], "Author": "Likun Wang and Tingting Li .", "Maintainer": "Likun Wang ", "source.ver": "src/contrib/ASEB_1.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ASEB_1.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ASEB_1.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ASEB_1.18.0.tgz", "vignettes": [ "vignettes/ASEB/inst/doc/ASEB.pdf" ], "vignetteTitles": [ "ASEB" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ASEB/inst/doc/ASEB.R" ] }, "ASGSCA": { "Package": "ASGSCA", "Version": "1.8.0", "Imports": [ "Matrix", "MASS" ], "Suggests": [ "BiocStyle" ], "License": "GPL-3", "MD5sum": "b4a51222c608ed671e99cda8db34c798", "NeedsCompilation": "no", "Title": "Association Studies for multiple SNPs and multiple traits using Generalized Structured Equation Models", "Description": "The package provides tools to model and test the association between multiple genotypes and multiple traits, taking into account the prior biological knowledge. Genes, and clinical pathways are incorporated in the model as latent variables. The method is based on Generalized Structured Component Analysis (GSCA).", "biocViews": [ "Software", "StructuralEquationModels" ], "Author": "Hela Romdhani, Stepan Grinek , Heungsun Hwang and Aurelie Labbe.", "Maintainer": "Hela Romdhani ", "source.ver": "src/contrib/ASGSCA_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ASGSCA_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ASGSCA_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ASGSCA_1.8.0.tgz", "vignettes": [ "vignettes/ASGSCA/inst/doc/ASGSCA.pdf" ], "vignetteTitles": [ "Association Studies using Generalized Structured Equation Models." ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ASGSCA/inst/doc/ASGSCA.R" ] }, "ASpli": { "Package": "ASpli", "Version": "1.0.0", "Depends": [ "methods", "GenomicRanges", "GenomicFeatures", "edgeR", "BiocGenerics", "IRanges", "GenomicAlignments", "DESeq2", "DEXSeq", "Gviz", "grDevices", "stats", "utils", "S4Vectors", "AnnotationDbi", "parallel" ], "Suggests": [ "RNAseqData.HNRNPC.bam.chr14", "BiocStyle" ], "License": "GPL", "MD5sum": "093115b1a53d00cab058e5edc944586e", "NeedsCompilation": "no", "Title": "Analysis of alternative splicing using RNA-Seq", "Description": "Integrative pipeline for the analyisis of alternative splicing using RNAseq.", "biocViews": [ "Alignment", "AlternativeSplicing", "Coverage", "DifferentialExpression", "DifferentialSplicing", "GeneExpression", "GenomeAnnotation", "RNASeq", "Sequencing", "Software", "TimeCourse", "Transcription" ], "Author": "Estefania Mancini, Marcelo Yanovsky and Ariel Chernomoretz", "Maintainer": "Estefania Mancini ", "source.ver": "src/contrib/ASpli_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ASpli_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ASpli_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ASpli_1.0.0.tgz", "vignettes": [ "vignettes/ASpli/inst/doc/ASpli.pdf" ], "vignetteTitles": [ "Analysis of alternative splicing using ASpli" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ASpli/inst/doc/ASpli.R" ] }, "ASSET": { "Package": "ASSET", "Version": "1.12.0", "Depends": [ "MASS", "msm", "rmeta", "mvtnorm", "tmvnsim" ], "Suggests": [ "RUnit", "BiocGenerics" ], "License": "GPL-2 + file LICENSE", "MD5sum": "508e1e033360a70b69f812c2ee143813", "NeedsCompilation": "no", "Title": "An R package for subset-based association analysis of heterogeneous traits and subtypes", "Description": "An R package for subset-based analysis of heterogeneous traits and subtypes.", "biocViews": [ "Bioinformatics", "Software" ], "Author": "Samsiddhi Bhattacharjee, Nilanjan Chatterjee and William Wheeler", "Maintainer": "William Wheeler ", "source.ver": "src/contrib/ASSET_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ASSET_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ASSET_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ASSET_1.12.0.tgz", "vignettes": [ "vignettes/ASSET/inst/doc/vignette.pdf" ], "vignetteTitles": [ "ASSET Vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/ASSET/inst/doc/vignette.R" ] }, "ASSIGN": { "Package": "ASSIGN", "Version": "1.10.0", "Depends": [ "Rlab", "msm", "gplots" ], "Imports": [ "graphics", "grDevices", "stats", "utils" ], "License": "MIT", "MD5sum": "2b826747e52791b492b3cffb2a568a3c", "NeedsCompilation": "no", "Title": "Adaptive Signature Selection and InteGratioN (ASSIGN)", "Description": "ASSIGN is a computational tool to evaluate the pathway deregulation/activation status in individual patient samples. ASSIGN employs a flexible Bayesian factor analysis approach that adapts predetermined pathway signatures derived either from knowledge-based literatures or from perturbation experiments to the cell-/tissue-specific pathway signatures. The deregulation/activation level of each context-specific pathway is quantified to a score, which represents the extent to which a patient sample encompasses the pathway deregulation/activation signature.", "biocViews": [ "Bayesian", "GeneExpression", "Pathways", "Software" ], "Author": "Ying Shen, Andrea H. Bild, and W. Evan Johnson", "Maintainer": "Ying Shen ", "source.ver": "src/contrib/ASSIGN_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ASSIGN_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ASSIGN_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ASSIGN_1.10.0.tgz", "vignettes": [ "vignettes/ASSIGN/inst/doc/ASSIGN.vignette.pdf" ], "vignetteTitles": [ "Primer" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ASSIGN/inst/doc/ASSIGN.vignette.R" ] }, "AtlasRDF": { "Package": "AtlasRDF", "Version": "1.10.0", "Depends": [ "R (>= 2.10)", "hash", "SPARQL", "methods" ], "License": "Apache License 2.0", "MD5sum": "5e4183598648d2ee26ebd8b0ebd8bcaf", "NeedsCompilation": "no", "Title": "Gene Expression Atlas query and gene set enrichment package.", "Description": "Query the Gene Expression Atlas RDF data at the European Bioinformatics Institute using genes, experimental factors (such as disease, cell type, compound treatments), pathways and proteins. Also contains a function to perform an enrichment of your gene list across Experimental Factor Ontology (EFO) using the Atlas background set.", "biocViews": [ "DataImport", "DataRepresentation", "DifferentialExpression", "GeneExpression", "GeneSetEnrichment", "Microarray", "Software" ], "Author": "James Malone, Simon Jupp, Maryam Soleimani", "Maintainer": "Simon Jupp ", "source.ver": "src/contrib/AtlasRDF_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/AtlasRDF_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/AtlasRDF_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/AtlasRDF_1.10.0.tgz", "vignettes": [ "vignettes/AtlasRDF/inst/doc/AtlasRDF_vignette.pdf" ], "vignetteTitles": [ "An introduction to the AtlasRDF-R package" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/AtlasRDF/inst/doc/AtlasRDF_vignette.R" ] }, "attract": { "Package": "attract", "Version": "1.26.0", "Depends": [ "R (>= 3.3.1)", "methods", "AnnotationDbi" ], "Imports": [ "Biobase", "limma", "cluster", "GOstats", "graphics", "stats", "reactome.db", "KEGGREST", "org.Hs.eg.db", "utils" ], "Suggests": [ "illuminaHumanv1.db" ], "License": "LGPL (>= 2.0)", "MD5sum": "493ba2ec49ca18ec206e452e52178e66", "NeedsCompilation": "no", "Title": "Methods to Find the Gene Expression Modules that Represent the Drivers of Kauffman's Attractor Landscape", "Description": "This package contains the functions to find the gene expression modules that represent the drivers of Kauffman's attractor landscape. The modules are the core attractor pathways that discriminate between different cell types of groups of interest. Each pathway has a set of synexpression groups, which show transcriptionally-coordinated changes in gene expression.", "biocViews": [ "GeneExpression", "GeneSetEnrichment", "KEGG", "Microarray", "Pathways", "RNASeq", "Reactome", "Software" ], "Author": "Jessica Mar", "Maintainer": "Samuel Zimmerman ", "source.ver": "src/contrib/attract_1.26.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/attract_1.26.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/attract_1.26.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/attract_1.26.0.tgz", "vignettes": [ "vignettes/attract/inst/doc/attract.pdf" ], "vignetteTitles": [ "Tutorial on How to Use the Functions in the \\texttt{attract} Package" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/attract/inst/doc/attract.R" ] }, "BaalChIP": { "Package": "BaalChIP", "Version": "1.0.0", "Depends": [ "R (>= 3.3.1)", "GenomicRanges", "IRanges", "Rsamtools" ], "Imports": [ "GenomicAlignments", "GenomeInfoDb", "doParallel", "parallel", "doBy", "reshape2", "scales", "coda", "foreach", "ggplot2", "methods", "utils", "graphics", "stats" ], "Suggests": [ "RUnit", "BiocGenerics", "knitr", "rmarkdown", "BiocStyle" ], "License": "Artistic-2.0", "MD5sum": "6804b4b818003cce8fcfb618de9b31c1", "NeedsCompilation": "no", "Title": "BaalChIP: Bayesian analysis of allele-specific transcription factor binding in cancer genomes", "Description": "The package offers functions to process multiple ChIP-seq BAM files and detect allele-specific events. Computes allele counts at individual variants (SNPs/SNVs), implements extensive QC steps to remove problematic variants, and utilizes a bayesian framework to identify statistically significant allele- specific events. BaalChIP is able to account for copy number differences between the two alleles, a known phenotypical feature of cancer samples.", "biocViews": [ "Bayesian", "ChIPSeq", "Sequencing", "Software" ], "Author": "Ines de Santiago, Wei Liu, Ke Yuan, Bruce Ponder, Kerstin Meyer, Florian Markowetz", "Maintainer": "Ines de Santiago ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/BaalChIP_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BaalChIP_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BaalChIP_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BaalChIP_1.0.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/BaalChIP/inst/doc/BaalChIP.R" ], "htmlDocs": [ "vignettes/BaalChIP/inst/doc/BaalChIP.html" ], "htmlTitles": [ "Analyzing ChIP-seq and FAIRE-seq data with the BaalChIP package" ] }, "BAC": { "Package": "BAC", "Version": "1.34.0", "Depends": [ "R (>= 2.10)" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "dcc911644ca89c81e66205f8b66f0606", "NeedsCompilation": "yes", "Title": "Bayesian Analysis of Chip-chip experiment", "Description": "This package uses a Bayesian hierarchical model to detect enriched regions from ChIP-chip experiments", "biocViews": [ "Microarray", "Software", "Transcription" ], "Author": "Raphael Gottardo", "Maintainer": "Raphael Gottardo ", "source.ver": "src/contrib/BAC_1.34.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BAC_1.34.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BAC_1.34.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BAC_1.34.0.tgz", "vignettes": [ "vignettes/BAC/inst/doc/BAC.pdf" ], "vignetteTitles": [ "1. Primer" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/BAC/inst/doc/BAC.R" ] }, "bacon": { "Package": "bacon", "Version": "1.2.0", "Depends": [ "R (>= 3.3)", "methods", "stats", "ggplot2", "graphics", "BiocParallel", "ellipse" ], "Suggests": [ "BiocStyle", "knitr", "rmarkdown", "testthat", "roxygen2" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "c636081ffdeb0289e2f546c971cfac3e", "NeedsCompilation": "yes", "Title": "Controlling bias and inflation in association studies using the empirical null distribution", "Description": "Bacon can be used to remove inflation and bias often observed in epigenome- and transcriptome-wide association studies. To this end bacon constructs an empirical null distribution using a Gibbs Sampling algorithm by fitting a three-component normal mixture on z-scores.", "biocViews": [ "BatchEffect", "Bayesian", "GenomeWideAssociation", "MethylationArray", "MultipleComparison", "RNASeq", "Regression", "Software", "StatisticalMethod", "Transcriptomics" ], "Author": "Maarten van Iterson [aut, cre], Erik van Zwet [ctb]", "Maintainer": "Maarten van Iterson ", "URL": "https://github.com/mvaniterson/bacon", "VignetteBuilder": "knitr", "BugReports": "https://github.com/mvaniterson/bacon/issues", "source.ver": "src/contrib/bacon_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/bacon_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/bacon_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/bacon_1.2.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/bacon/inst/doc/bacon.R" ], "htmlDocs": [ "vignettes/bacon/inst/doc/bacon.html" ], "htmlTitles": [ "Controlling bias and inflation in association studies using the empirical null distribution" ] }, "BADER": { "Package": "BADER", "Version": "1.12.0", "Suggests": [ "pasilla (>= 0.2.10)" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "c1379646a5568064e56fa0cfa14ca6f1", "NeedsCompilation": "yes", "Title": "Bayesian Analysis of Differential Expression in RNA Sequencing Data", "Description": "For RNA sequencing count data, BADER fits a Bayesian hierarchical model. The algorithm returns the posterior probability of differential expression for each gene between two groups A and B. The joint posterior distribution of the variables in the model can be returned in the form of posterior samples, which can be used for further down-stream analyses such as gene set enrichment.", "biocViews": [ "DifferentialExpression", "RNASeq", "SAGE", "Sequencing", "Software" ], "Author": "Andreas Neudecker, Matthias Katzfuss", "Maintainer": "Andreas Neudecker ", "source.ver": "src/contrib/BADER_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BADER_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BADER_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BADER_1.12.0.tgz", "vignettes": [ "vignettes/BADER/inst/doc/BADER.pdf" ], "vignetteTitles": [ "Analysing RNA-Seq data with the \"BADER\" package" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/BADER/inst/doc/BADER.R" ] }, "BadRegionFinder": { "Package": "BadRegionFinder", "Version": "1.2.0", "Imports": [ "VariantAnnotation", "Rsamtools", "biomaRt", "GenomicRanges", "S4Vectors", "utils", "stats", "grDevices", "graphics" ], "Suggests": [ "BSgenome.Hsapiens.UCSC.hg19" ], "License": "LGPL-3", "MD5sum": "cc23937db14423f27cb10fde218224e1", "NeedsCompilation": "no", "Title": "BadRegionFinder: an R/Bioconductor package for identifying regions with bad coverage", "Description": "BadRegionFinder is a package for identifying regions with a bad, acceptable and good coverage in sequence alignment data available as bam files. The whole genome may be considered as well as a set of target regions. Various visual and textual types of output are available.", "biocViews": [ "Alignment", "Classification", "Coverage", "Sequencing", "Software", "WholeGenome" ], "Author": "Sarah Sandmann", "Maintainer": "Sarah Sandmann ", "source.ver": "src/contrib/BadRegionFinder_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BadRegionFinder_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BadRegionFinder_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BadRegionFinder_1.2.0.tgz", "vignettes": [ "vignettes/BadRegionFinder/inst/doc/BadRegionFinder.pdf" ], "vignetteTitles": [ "Using BadRegionFinder" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/BadRegionFinder/inst/doc/BadRegionFinder.R" ] }, "BAGS": { "Package": "BAGS", "Version": "2.14.0", "Depends": [ "R (>= 2.10)", "breastCancerVDX", "Biobase" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "83909ade219a1b0081f8d060cf1c2030", "NeedsCompilation": "yes", "Title": "A Bayesian Approach for Geneset Selection", "Description": "R package providing functions to perform geneset significance analysis over simple cross-sectional data between 2 and 5 phenotypes of interest.", "biocViews": [ "Bayesian", "Software" ], "Author": "Alejandro Quiroz-Zarate", "Maintainer": "Alejandro Quiroz-Zarate ", "source.ver": "src/contrib/BAGS_2.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BAGS_2.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BAGS_2.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BAGS_2.14.0.tgz", "vignettes": [ "vignettes/BAGS/inst/doc/BAGS.pdf" ], "vignetteTitles": [ "BAGS: A Bayesian Approach for Geneset Selection." ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/BAGS/inst/doc/BAGS.R" ] }, "ballgown": { "Package": "ballgown", "Version": "2.6.0", "Depends": [ "R (>= 3.1.1)", "methods" ], "Imports": [ "GenomicRanges (>= 1.17.25)", "IRanges (>= 1.99.22)", "S4Vectors (>= 0.9.39)", "RColorBrewer", "splines", "sva", "limma", "rtracklayer (>= 1.29.25)", "Biobase (>= 2.25.0)", "GenomeInfoDb" ], "Suggests": [ "testthat", "knitr" ], "License": "Artistic-2.0", "MD5sum": "40935656d2f7378be303eeff7255b4c4", "NeedsCompilation": "no", "Title": "Flexible, isoform-level differential expression analysis", "Description": "Tools for statistical analysis of assembled transcriptomes, including flexible differential expression analysis, visualization of transcript structures, and matching of assembled transcripts to annotation.", "biocViews": [ "DifferentialExpression", "Preprocessing", "RNASeq", "Software", "StatisticalMethod" ], "Author": "Jack Fu [aut], Alyssa C. Frazee [aut, cre], Leonardo Collado-Torres [aut], Andrew E. Jaffe [aut], Jeffrey T. Leek [aut, ths]", "Maintainer": "Jack Fu ", "VignetteBuilder": "knitr", "BugReports": "https://github.com/alyssafrazee/ballgown/issues", "source.ver": "src/contrib/ballgown_2.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ballgown_2.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ballgown_2.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ballgown_2.6.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ballgown/inst/doc/ballgown.R" ], "htmlDocs": [ "vignettes/ballgown/inst/doc/ballgown.html" ], "htmlTitles": [ "Flexible isoform-level differential expression analysis with Ballgown" ], "suggestsMe": [ "polyester", "variancePartition" ] }, "bamsignals": { "Package": "bamsignals", "Version": "1.6.0", "Depends": [ "R (>= 3.2.0)" ], "Imports": [ "methods", "BiocGenerics", "Rcpp (>= 0.10.6)", "IRanges", "GenomicRanges", "zlibbioc" ], "LinkingTo": [ "Rcpp", "Rhtslib", "zlibbioc" ], "Suggests": [ "testthat (>= 0.9)", "Rsamtools", "BiocStyle", "knitr", "rmarkdown" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "4fa449e37d4944a5ad1f723dc8ad1257", "NeedsCompilation": "yes", "Title": "Extract read count signals from bam files", "Description": "This package allows to efficiently obtain count vectors from indexed bam files. It counts the number of reads in given genomic ranges and it computes reads profiles and coverage profiles. It also handles paired-end data.", "biocViews": [ "Alignment", "Coverage", "DataImport", "Sequencing", "Software" ], "Author": "Alessandro Mammana [aut, cre], Johannes Helmuth [aut]", "Maintainer": "Alessandro Mammana ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/bamsignals_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/bamsignals_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/bamsignals_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/bamsignals_1.6.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/bamsignals/inst/doc/bamsignals.R" ], "htmlDocs": [ "vignettes/bamsignals/inst/doc/bamsignals.html" ], "htmlTitles": [ "Introduction to the bamsignals package" ], "importsMe": [ "AneuFinder", "chromstaR", "normr" ] }, "BaseSpaceR": { "Package": "BaseSpaceR", "Version": "1.18.0", "Depends": [ "R (>= 2.15.0)", "RCurl", "RJSONIO" ], "Imports": [ "methods" ], "Suggests": [ "RUnit", "IRanges", "Rsamtools" ], "License": "Apache License 2.0", "MD5sum": "2c70c8d061b707341b606a6e53e9ef0a", "NeedsCompilation": "no", "Title": "R SDK for BaseSpace RESTful API", "Description": "A rich R interface to Illumina's BaseSpace cloud computing environment, enabling the fast development of data analysis and visualisation tools.", "biocViews": [ "ConnectTools", "DataImport", "DataRepresentation", "Genetics", "HighThroughputSequencing", "Infrastructure", "Sequencing", "Software" ], "Author": "Adrian Alexa", "Maintainer": "Jared O'Connell ", "source.ver": "src/contrib/BaseSpaceR_1.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BaseSpaceR_1.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BaseSpaceR_1.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BaseSpaceR_1.18.0.tgz", "vignettes": [ "vignettes/BaseSpaceR/inst/doc/BaseSpaceR.pdf" ], "vignetteTitles": [ "BaseSpaceR" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/BaseSpaceR/inst/doc/BaseSpaceR.R" ] }, "Basic4Cseq": { "Package": "Basic4Cseq", "Version": "1.10.0", "Depends": [ "R (>= 3.0.0)", "Biostrings", "GenomicAlignments", "caTools", "GenomicRanges" ], "Imports": [ "methods", "RCircos", "BSgenome.Ecoli.NCBI.20080805" ], "Suggests": [ "BSgenome.Hsapiens.UCSC.hg19" ], "License": "LGPL-3", "MD5sum": "4b8d6cc0ee8ec509829b05f242c4ec66", "NeedsCompilation": "no", "Title": "Basic4Cseq: an R/Bioconductor package for analyzing 4C-seq data", "Description": "Basic4Cseq is an R/Bioconductor package for basic filtering, analysis and subsequent visualization of 4C-seq data. Virtual fragment libraries can be created for any BSGenome package, and filter functions for both reads and fragments and basic quality controls are included. Fragment data in the vicinity of the experiment's viewpoint can be visualized as a coverage plot based on a running median approach and a multi-scale contact profile.", "biocViews": [ "QualityControl", "Software", "Visualization" ], "Author": "Carolin Walter", "Maintainer": "Carolin Walter ", "source.ver": "src/contrib/Basic4Cseq_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Basic4Cseq_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Basic4Cseq_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Basic4Cseq_1.10.0.tgz", "vignettes": [ "vignettes/Basic4Cseq/inst/doc/vignette.pdf" ], "vignetteTitles": [ "Basic4Cseq: an R/Bioconductor package for the analysis of 4C-seq data" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Basic4Cseq/inst/doc/vignette.R" ] }, "BasicSTARRseq": { "Package": "BasicSTARRseq", "Version": "1.2.0", "Depends": [ "GenomicRanges", "GenomicAlignments" ], "Imports": [ "S4Vectors", "methods", "IRanges", "GenomeInfoDb", "stats" ], "Suggests": [ "knitr" ], "License": "LGPL-3", "MD5sum": "8763a47d423fd6b385313b1a1a2a968d", "NeedsCompilation": "no", "Title": "Basic peak calling on STARR-seq data", "Description": "Basic peak calling on STARR-seq data based on a method introduced in \"Genome-Wide Quantitative Enhancer Activity Maps Identified by STARR-seq\" Arnold et al. Science. 2013 Mar 1;339(6123):1074-7. doi: 10.1126/science. 1232542. Epub 2013 Jan 17.", "biocViews": [ "Coverage", "FunctionalGenomics", "FunctionalPrediction", "GeneRegulation", "PeakDetection", "Software" ], "Author": "Annika Buerger", "Maintainer": "Annika Buerger ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/BasicSTARRseq_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BasicSTARRseq_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BasicSTARRseq_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BasicSTARRseq_1.2.0.tgz", "vignettes": [ "vignettes/BasicSTARRseq/inst/doc/BasicSTARRseq.pdf" ], "vignetteTitles": [ "BasicSTARRseq.pdf" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/BasicSTARRseq/inst/doc/BasicSTARRseq.R" ] }, "BatchQC": { "Package": "BatchQC", "Version": "1.2.1", "Depends": [ "R (>= 3.3.0)" ], "Imports": [ "utils", "rmarkdown", "knitr", "pander", "gplots", "MCMCpack", "shiny", "sva", "corpcor", "moments", "matrixStats", "ggvis", "d3heatmap", "reshape2", "limma", "grDevices", "graphics", "stats", "methods" ], "Suggests": [ "testthat" ], "License": "GPL (>= 2)", "MD5sum": "009884d4a0fe91a41bd32b85cb4467fe", "NeedsCompilation": "no", "Title": "Batch Effects Quality Control Software", "Description": "Sequencing and microarray samples often are collected or processed in multiple batches or at different times. This often produces technical biases that can lead to incorrect results in the downstream analysis. BatchQC is a software tool that streamlines batch preprocessing and evaluation by providing interactive diagnostics, visualizations, and statistical analyses to explore the extent to which batch variation impacts the data. BatchQC diagnostics help determine whether batch adjustment needs to be done, and how correction should be applied before proceeding with a downstream analysis. Moreover, BatchQC interactively applies multiple common batch effect approaches to the data, and the user can quickly see the benefits of each method. BatchQC is developed as a Shiny App. The output is organized into multiple tabs, and each tab features an important part of the batch effect analysis and visualization of the data. The BatchQC interface has the following analysis groups: Summary, Differential Expression, Median Correlations, Heatmaps, Circular Dendrogram, PCA Analysis, Shape, ComBat and SVA.", "biocViews": [ "BatchEffect", "DifferentialExpression", "GraphAndNetwork", "Microarray", "Preprocessing", "PrincipalComponent", "QualityControl", "RNASeq", "Sequencing", "Software", "Visualization" ], "Author": "Solaiappan Manimaran , W. Evan Johnson , Heather Selby , Claire Ruberman , Kwame Okrah , Hector Corrada Bravo ", "Maintainer": "Solaiappan Manimaran ", "URL": "https://github.com/mani2012/BatchQC", "SystemRequirements": "pandoc (http://pandoc.org/installing.html) for generating reports from markdown files.", "VignetteBuilder": "knitr", "BugReports": "https://github.com/mani2012/BatchQC/issues", "source.ver": "src/contrib/BatchQC_1.2.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BatchQC_1.2.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BatchQC_1.2.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BatchQC_1.2.1.tgz", "vignettes": [ "vignettes/BatchQC/inst/doc/BatchQC_usage_advanced.pdf" ], "vignetteTitles": [ "BatchQC_usage_advanced" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/BatchQC/inst/doc/BatchQC_usage_advanced.R" ], "htmlDocs": [ "vignettes/BatchQC/inst/doc/BatchQC_examples.html", "vignettes/BatchQC/inst/doc/BatchQCIntro.html" ], "htmlTitles": [ "BatchQC_examples", "BatchQCIntro" ], "importsMe": [ "PathoStat" ] }, "BayesKnockdown": { "Package": "BayesKnockdown", "Version": "1.0.0", "Depends": [ "R (>= 3.3)" ], "Imports": [ "stats", "Biobase" ], "License": "GPL-3", "MD5sum": "181a7217110805f605959f0bf4c58fd3", "NeedsCompilation": "no", "Title": "BayesKnockdown: Posterior Probabilities for Edges from Knockdown Data", "Description": "A simple, fast Bayesian method for computing posterior probabilities for relationships between a single predictor variable and multiple potential outcome variables, incorporating prior probabilities of relationships. In the context of knockdown experiments, the predictor variable is the knocked-down gene, while the other genes are potential targets. Can also be used for differential expression/2-class data.", "biocViews": [ "Bayesian", "GeneExpression", "GeneTarget", "Network", "NetworkInference", "Software" ], "Author": "William Chad Young", "Maintainer": "William Chad Young ", "source.ver": "src/contrib/BayesKnockdown_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BayesKnockdown_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BayesKnockdown_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BayesKnockdown_1.0.0.tgz", "vignettes": [ "vignettes/BayesKnockdown/inst/doc/BayesKnockdown.pdf" ], "vignetteTitles": [ "BayesKnockdown.pdf" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/BayesKnockdown/inst/doc/BayesKnockdown.R" ] }, "BayesPeak": { "Package": "BayesPeak", "Version": "1.26.0", "Depends": [ "R (>= 2.14)", "IRanges" ], "Imports": [ "IRanges", "graphics" ], "Suggests": [ "BiocStyle", "parallel" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "2a53cf0c53bde590b2221f5868f95bec", "NeedsCompilation": "yes", "Title": "Bayesian Analysis of ChIP-seq Data", "Description": "This package is an implementation of the BayesPeak algorithm for peak-calling in ChIP-seq data.", "biocViews": [ "ChIPSeq", "Software" ], "Author": "Christiana Spyrou, Jonathan Cairns, Rory Stark, Andy Lynch, Simon Tavar\\\\'{e},", "Maintainer": "Jonathan Cairns ", "source.ver": "src/contrib/BayesPeak_1.26.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BayesPeak_1.26.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BayesPeak_1.26.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BayesPeak_1.26.0.tgz", "vignettes": [ "vignettes/BayesPeak/inst/doc/BayesPeak.pdf" ], "vignetteTitles": [ "BayesPeak Vignette" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/BayesPeak/inst/doc/BayesPeak.R" ] }, "baySeq": { "Package": "baySeq", "Version": "2.8.0", "Depends": [ "R (>= 2.3.0)", "methods", "GenomicRanges", "abind", "parallel" ], "Imports": [ "edgeR" ], "Suggests": [ "BiocStyle", "BiocGenerics" ], "License": "GPL-3", "MD5sum": "cd4fbec5ad9d468eac59b8e7122bce6d", "NeedsCompilation": "no", "Title": "Empirical Bayesian analysis of patterns of differential expression in count data", "Description": "This package identifies differential expression in high-throughput 'count' data, such as that derived from next-generation sequencing machines, calculating estimated posterior likelihoods of differential expression (or more complex hypotheses) via empirical Bayesian methods.", "biocViews": [ "DifferentialExpression", "MultipleComparison", "SAGE", "Sequencing", "Software" ], "Author": "Thomas J. Hardcastle", "Maintainer": "Thomas J. Hardcastle ", "source.ver": "src/contrib/baySeq_2.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/baySeq_2.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/baySeq_2.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/baySeq_2.8.0.tgz", "vignettes": [ "vignettes/baySeq/inst/doc/baySeq_generic.pdf", "vignettes/baySeq/inst/doc/baySeq.pdf" ], "vignetteTitles": [ "Advanced baySeq analyses", "baySeq" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/baySeq/inst/doc/baySeq_generic.R", "vignettes/baySeq/inst/doc/baySeq.R" ], "dependsOnMe": [ "EDDA", "Rcade", "segmentSeq", "TCC" ], "importsMe": [ "debrowser", "EDDA", "metaseqR", "riboSeqR" ], "suggestsMe": [ "compcodeR", "oneChannelGUI" ] }, "BBCAnalyzer": { "Package": "BBCAnalyzer", "Version": "1.4.0", "Imports": [ "SummarizedExperiment", "VariantAnnotation", "Rsamtools", "grDevices", "GenomicRanges", "IRanges", "Biostrings" ], "Suggests": [ "BSgenome.Hsapiens.UCSC.hg19" ], "License": "LGPL-3", "MD5sum": "d770f93ca9fc1ddf382911f5bac05970", "NeedsCompilation": "no", "Title": "BBCAnalyzer: an R/Bioconductor package for visualizing base counts", "Description": "BBCAnalyzer is a package for visualizing the relative or absolute number of bases, deletions and insertions at defined positions in sequence alignment data available as bam files in comparison to the reference bases. Markers for the relative base frequencies, the mean quality of the detected bases, known mutations or polymorphisms and variants called in the data may additionally be included in the plots.", "biocViews": [ "Alignment", "Coverage", "GeneticVariability", "SNP", "Sequencing", "Software" ], "Author": "Sarah Sandmann", "Maintainer": "Sarah Sandmann ", "source.ver": "src/contrib/BBCAnalyzer_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BBCAnalyzer_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BBCAnalyzer_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BBCAnalyzer_1.4.0.tgz", "vignettes": [ "vignettes/BBCAnalyzer/inst/doc/BBCAnalyzer.pdf" ], "vignetteTitles": [ "Using BBCAnalyzer" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/BBCAnalyzer/inst/doc/BBCAnalyzer.R" ] }, "BCRANK": { "Package": "BCRANK", "Version": "1.36.0", "Depends": [ "methods" ], "Imports": [ "Biostrings" ], "Suggests": [ "seqLogo" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "d46a00897669624518bdfa87b0ddf209", "NeedsCompilation": "yes", "Title": "Predicting binding site consensus from ranked DNA sequences", "Description": "Functions and classes for de novo prediction of transcription factor binding consensus by heuristic search", "biocViews": [ "GeneRegulation", "MotifDiscovery", "Software" ], "Author": "Adam Ameur ", "Maintainer": "Adam Ameur ", "source.ver": "src/contrib/BCRANK_1.36.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BCRANK_1.36.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BCRANK_1.36.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BCRANK_1.36.0.tgz", "vignettes": [ "vignettes/BCRANK/inst/doc/BCRANK.pdf" ], "vignetteTitles": [ "BCRANK" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/BCRANK/inst/doc/BCRANK.R" ] }, "beadarray": { "Package": "beadarray", "Version": "2.24.0", "Depends": [ "R (>= 2.13.0)", "BiocGenerics (>= 0.3.2)", "Biobase (>= 2.17.8)", "methods", "ggplot2" ], "Imports": [ "BeadDataPackR", "limma", "AnnotationDbi", "stats4", "reshape2", "GenomicRanges", "IRanges", "illuminaio" ], "Suggests": [ "lumi", "vsn", "affy", "hwriter", "beadarrayExampleData", "illuminaHumanv3.db", "gridExtra", "BiocStyle", "TxDb.Hsapiens.UCSC.hg19.knownGene", "ggbio", "Nozzle.R1", "knitr" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "c1065a9d4d4be174f43285648b57d817", "NeedsCompilation": "yes", "Title": "Quality assessment and low-level analysis for Illumina BeadArray data", "Description": "The package is able to read bead-level data (raw TIFFs and text files) output by BeadScan as well as bead-summary data from BeadStudio. Methods for quality assessment and low-level analysis are provided.", "biocViews": [ "Microarray", "OneChannel", "Preprocessing", "QualityControl", "Software" ], "Author": "Mark Dunning, Mike Smith, Jonathan Cairns, Andy Lynch, Matt Ritchie", "Maintainer": "Mark Dunning ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/beadarray_2.24.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/beadarray_2.24.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/beadarray_2.24.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/beadarray_2.24.0.tgz", "vignettes": [ "vignettes/beadarray/inst/doc/beadarray.pdf", "vignettes/beadarray/inst/doc/beadlevel.pdf", "vignettes/beadarray/inst/doc/beadsummary.pdf", "vignettes/beadarray/inst/doc/ImageProcessing.pdf" ], "vignetteTitles": [ "beadarray.pdf", "beadlevel.pdf", "beadsummary.pdf", "ImageProcessing.pdf" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/beadarray/inst/doc/beadarray.R", "vignettes/beadarray/inst/doc/beadlevel.R", "vignettes/beadarray/inst/doc/beadsummary.R", "vignettes/beadarray/inst/doc/ImageProcessing.R" ], "importsMe": [ "arrayQualityMetrics", "BeadArrayUseCases", "blima", "epigenomix" ], "suggestsMe": [ "beadarraySNP", "blimaTestingData", "lumi" ], "dependsOnMe": [ "beadarrayExampleData" ] }, "beadarraySNP": { "Package": "beadarraySNP", "Version": "1.40.0", "Depends": [ "methods", "Biobase (>= 2.14)", "quantsmooth" ], "Suggests": [ "aCGH", "affy", "limma", "snapCGH", "beadarray", "DNAcopy" ], "License": "GPL-2", "MD5sum": "68de514c889de49347c7b03d99040ca6", "NeedsCompilation": "no", "Title": "Normalization and reporting of Illumina SNP bead arrays", "Description": "Importing data from Illumina SNP experiments and performing copy number calculations and reports.", "biocViews": [ "CopyNumberVariation", "DataImport", "GeneticVariability", "Preprocessing", "SNP", "Software", "TwoChannel" ], "Author": "Jan Oosting", "Maintainer": "Jan Oosting ", "source.ver": "src/contrib/beadarraySNP_1.40.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/beadarraySNP_1.40.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/beadarraySNP_1.40.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/beadarraySNP_1.40.0.tgz", "vignettes": [ "vignettes/beadarraySNP/inst/doc/beadarraySNP.pdf" ], "vignetteTitles": [ "beadarraySNP.pdf" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/beadarraySNP/inst/doc/beadarraySNP.R" ] }, "BeadDataPackR": { "Package": "BeadDataPackR", "Version": "1.26.0", "Suggests": [ "BiocStyle", "knitr" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "9811a4688527a507bc1cb0cd3d4d9024", "NeedsCompilation": "yes", "Title": "Compression of Illumina BeadArray data", "Description": "Provides functionality for the compression and decompression of raw bead-level data from the Illumina BeadArray platform", "biocViews": [ "Microarray", "Software" ], "Author": "Mike Smith, Andy Lynch", "Maintainer": "Mike Smith ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/BeadDataPackR_1.26.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BeadDataPackR_1.26.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BeadDataPackR_1.26.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BeadDataPackR_1.26.0.tgz", "vignettes": [ "vignettes/BeadDataPackR/inst/doc/BeadDataPackR.pdf" ], "vignetteTitles": [ "BeadDataPackR.pdf" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/BeadDataPackR/inst/doc/BeadDataPackR.R" ], "importsMe": [ "beadarray" ] }, "BEAT": { "Package": "BEAT", "Version": "1.12.0", "Depends": [ "R (>= 2.13.0)" ], "Imports": [ "GenomicRanges", "ShortRead", "Biostrings", "BSgenome" ], "License": "LGPL (>= 3.0)", "MD5sum": "2511c71a9fd020e10f89d42a99fa4e08", "NeedsCompilation": "no", "Title": "BEAT - BS-Seq Epimutation Analysis Toolkit", "Description": "Model-based analysis of single-cell methylation data", "biocViews": [ "DNAMethylation", "Epigenetics", "Genetics", "MethylSeq", "Software" ], "Author": "Kemal Akman ", "Maintainer": "Kemal Akman ", "source.ver": "src/contrib/BEAT_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BEAT_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BEAT_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BEAT_1.12.0.tgz", "vignettes": [ "vignettes/BEAT/inst/doc/BEAT.pdf" ], "vignetteTitles": [ "Analysing single-cell BS-Seq data with the \"BEAT\" package" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/BEAT/inst/doc/BEAT.R" ] }, "BEclear": { "Package": "BEclear", "Version": "1.6.0", "Depends": [ "snowfall", "Matrix" ], "License": "GPL-2", "MD5sum": "a693f475f19761bc5b75820336d625e9", "NeedsCompilation": "no", "Title": "Correct for batch effects in DNA methylation data", "Description": "Provides some functions to detect and correct for batch effects in DNA methylation data. The core function \"BEclear\" is based on latent factor models and can also be used to predict missing values in any other matrix containing real numbers.", "biocViews": [ "BatchEffect", "DNAMethylation", "Software" ], "Author": "Markus Merl, Ruslan Akulenko", "Maintainer": "Markus Merl ", "source.ver": "src/contrib/BEclear_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BEclear_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BEclear_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BEclear_1.6.0.tgz", "vignettes": [ "vignettes/BEclear/inst/doc/BEclear.pdf" ], "vignetteTitles": [ "BEclear tutorial" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/BEclear/inst/doc/BEclear.R" ] }, "betr": { "Package": "betr", "Version": "1.32.0", "Depends": [ "R(>= 2.6.0)" ], "Imports": [ "Biobase (>= 2.5.5)", "limma", "mvtnorm", "methods", "stats" ], "Suggests": [ "Biobase" ], "License": "LGPL", "MD5sum": "9ff64c84a1b471d37daf381b5011405a", "NeedsCompilation": "no", "Title": "Identify differentially expressed genes in microarray time-course data", "Description": "The betr package implements the BETR (Bayesian Estimation of Temporal Regulation) algorithm to identify differentially expressed genes in microarray time-course data.", "biocViews": [ "DifferentialExpression", "Microarray", "Software", "TimeCourse" ], "Author": "Martin Aryee", "Maintainer": "Martin Aryee ", "PackageStatus": "Deprecated", "source.ver": "src/contrib/betr_1.32.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/betr_1.32.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/betr_1.32.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/betr_1.32.0.tgz", "vignettes": [ "vignettes/betr/inst/doc/betr.pdf" ], "vignetteTitles": [ "BETR Vignette" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/betr/inst/doc/betr.R" ] }, "bgafun": { "Package": "bgafun", "Version": "1.36.0", "Depends": [ "made4", "seqinr", "ade4" ], "License": "Artistic-2.0", "MD5sum": "33cf7d7645a01f3f87e5f892d2014008", "NeedsCompilation": "no", "Title": "BGAfun A method to identify specifity determining residues in protein families", "Description": "A method to identify specifity determining residues in protein families using Between Group Analysis", "biocViews": [ "Classification", "Software" ], "Author": "Iain Wallace", "Maintainer": "Iain Wallace ", "source.ver": "src/contrib/bgafun_1.36.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/bgafun_1.36.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/bgafun_1.36.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/bgafun_1.36.0.tgz", "vignettes": [ "vignettes/bgafun/inst/doc/bgafun.pdf" ], "vignetteTitles": [ "bgafun.pdf" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/bgafun/inst/doc/bgafun.R" ] }, "BgeeDB": { "Package": "BgeeDB", "Version": "2.0.0", "Depends": [ "R (>= 3.3.0)", "topGO", "tidyr" ], "Imports": [ "data.table", "RCurl", "digest", "methods", "stats", "utils", "dplyr", "graph", "Biobase" ], "Suggests": [ "knitr", "BiocStyle", "testthat", "rmarkdown" ], "License": "GPL-2", "MD5sum": "9b25e6aac8f01b57728a70b8aa0c8f51", "NeedsCompilation": "no", "Title": "Annotation and gene expression data retrieval from Bgee database", "Description": "A package for the annotation and gene expression data download from Bgee database, and TopAnat analysis: GO-like enrichment of anatomical terms, mapped to genes by expression patterns.", "biocViews": [ "DataImport", "GO", "GeneExpression", "GeneSetEnrichment", "Microarray", "Sequencing", "Software" ], "Author": "Andrea Komljenovic [aut, cre], Julien Roux [aut, cre]", "Maintainer": "Andrea Komljenovic , Frederic Bastian ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/BgeeDB_2.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BgeeDB_2.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BgeeDB_2.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BgeeDB_2.0.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/BgeeDB/inst/doc/BgeeDB_Manual.R" ], "htmlDocs": [ "vignettes/BgeeDB/inst/doc/BgeeDB_Manual.html" ], "htmlTitles": [ "Vignette Title" ], "importsMe": [ "psygenet2r" ] }, "BGmix": { "Package": "BGmix", "Version": "1.34.0", "Depends": [ "R (>= 2.3.1)", "KernSmooth" ], "License": "GPL-2", "MD5sum": "8e0f1b9145b7b0f5c2f3bb93fa05b85c", "NeedsCompilation": "yes", "Title": "Bayesian models for differential gene expression", "Description": "Fully Bayesian mixture models for differential gene expression", "biocViews": [ "DifferentialExpression", "Microarray", "MultipleComparison", "Software" ], "Author": "Alex Lewin, Natalia Bochkina", "Maintainer": "Alex Lewin ", "source.ver": "src/contrib/BGmix_1.34.0.tar.gz", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BGmix_1.34.0.tgz", "vignettes": [ "vignettes/BGmix/inst/doc/BGmix.pdf" ], "vignetteTitles": [ "BGmix Tutorial" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/BGmix/inst/doc/BGmix.R" ] }, "bgx": { "Package": "bgx", "Version": "1.40.0", "Depends": [ "R (>= 2.0.1)", "Biobase", "affy (>= 1.5.0)", "gcrma (>= 2.4.1)" ], "Suggests": [ "affydata", "hgu95av2cdf" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "b7513e93cdbd999dd5431b982910f274", "NeedsCompilation": "yes", "Title": "Bayesian Gene eXpression", "Description": "Bayesian integrated analysis of Affymetrix GeneChips", "biocViews": [ "DifferentialExpression", "Microarray", "Software" ], "Author": "Ernest Turro, Graeme Ambler, Anne-Mette K Hein", "Maintainer": "Ernest Turro ", "source.ver": "src/contrib/bgx_1.40.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/bgx_1.40.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/bgx_1.40.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/bgx_1.40.0.tgz", "vignettes": [ "vignettes/bgx/inst/doc/bgx.pdf" ], "vignetteTitles": [ "HowTo BGX" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/bgx/inst/doc/bgx.R" ] }, "BHC": { "Package": "BHC", "Version": "1.26.0", "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "8244635e7dec33e45c91322d6622b2b4", "NeedsCompilation": "yes", "Title": "Bayesian Hierarchical Clustering", "Description": "The method performs bottom-up hierarchical clustering, using a Dirichlet Process (infinite mixture) to model uncertainty in the data and Bayesian model selection to decide at each step which clusters to merge. This avoids several limitations of traditional methods, for example how many clusters there should be and how to choose a principled distance metric. This implementation accepts multinomial (i.e. discrete, with 2+ categories) or time-series data. This version also includes a randomised algorithm which is more efficient for larger data sets.", "biocViews": [ "Clustering", "Microarray", "Software" ], "Author": "Rich Savage, Emma Cooke, Robert Darkins, Yang Xu", "Maintainer": "Rich Savage ", "source.ver": "src/contrib/BHC_1.26.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BHC_1.26.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BHC_1.26.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BHC_1.26.0.tgz", "vignettes": [ "vignettes/BHC/inst/doc/bhc.pdf" ], "vignetteTitles": [ "Bayesian Hierarchical Clustering" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/BHC/inst/doc/bhc.R" ] }, "BicARE": { "Package": "BicARE", "Version": "1.32.0", "Depends": [ "R (>= 1.8.0)", "Biobase (>= 2.5.5)", "multtest", "GSEABase" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "2b21b88138b8c3294c7c285b725365c1", "NeedsCompilation": "yes", "Title": "Biclustering Analysis and Results Exploration", "Description": "Biclustering Analysis and Results Exploration", "biocViews": [ "Clustering", "Microarray", "Software", "Transcription" ], "Author": "Pierre Gestraud", "Maintainer": "Pierre Gestraud ", "URL": "http://bioinfo.curie.fr", "source.ver": "src/contrib/BicARE_1.32.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BicARE_1.32.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BicARE_1.32.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BicARE_1.32.0.tgz", "vignettes": [ "vignettes/BicARE/inst/doc/BicARE.pdf" ], "vignetteTitles": [ "BicARE" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/BicARE/inst/doc/BicARE.R" ] }, "BiGGR": { "Package": "BiGGR", "Version": "1.10.0", "Depends": [ "R (>= 2.14.0)", "rsbml", "hyperdraw", "LIM", "stringr" ], "Imports": [ "hypergraph", "limSolve" ], "License": "file LICENSE", "MD5sum": "8958225235184927e24b741b4762f5af", "NeedsCompilation": "no", "Title": "Constraint based modeling in R using metabolic reconstruction databases", "Description": "This package provides an interface to simulate metabolic reconstruction from the BiGG database(http://bigg.ucsd.edu/) and other metabolic reconstruction databases. The package facilitates flux balance analysis (FBA) and the sampling of feasible flux distributions. Metabolic networks and estimated fluxes can be visualized with hypergraphs.", "biocViews": [ "GraphAndNetwork", "Metabolomics", "Network", "Pathway", "Software", "Systems Biology", "Visualization" ], "Author": "Anand K. Gavai, Hannes Hettling", "Maintainer": "Anand K. Gavai , Hannes Hettling ", "URL": "http://www.bioconductor.org/", "source.ver": "src/contrib/BiGGR_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BiGGR_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BiGGR_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BiGGR_1.10.0.tgz", "vignettes": [ "vignettes/BiGGR/inst/doc/BiGGR.pdf" ], "vignetteTitles": [ "BiGGR" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/BiGGR/inst/doc/BiGGR.R" ] }, "bigmelon": { "Package": "bigmelon", "Version": "1.0.0", "Depends": [ "R (>= 3.3)", "wateRmelon (>= 1.17.1)", "gdsfmt (>= 1.0.4)", "methods", "methylumi", "minfi", "Biobase" ], "Imports": [ "stats", "utils" ], "Suggests": [ "BiocGenerics", "BiocStyle", "minfiData" ], "License": "GPL-3", "MD5sum": "f60cd1404f2bd2fc33c284b8e3ad7990", "NeedsCompilation": "no", "Title": "Illumina methylation array analysis for large experiments", "Description": "Methods for working with Illumina arrays using gdsfmt.", "biocViews": [ "CpGIsland", "DNAMethylation", "DataImport", "MethylationArray", "Microarray", "Preprocessing", "QualityControl", "Software", "TwoChannel" ], "Author": "Tyler Gorrie-Stone, Ayden Saffari, Karim Malki, Leonard C Schalkwyk", "Maintainer": "Tyler Gorrie-Stone ", "source.ver": "src/contrib/bigmelon_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/bigmelon_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/bigmelon_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/bigmelon_1.0.0.tgz", "vignettes": [ "vignettes/bigmelon/inst/doc/bigmelon.pdf" ], "vignetteTitles": [ "The \\Rpackage{bigmelon} Package" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/bigmelon/inst/doc/bigmelon.R" ] }, "bigmemoryExtras": { "Package": "bigmemoryExtras", "Version": "1.20.0", "Depends": [ "R (>= 2.12)", "bigmemory (>= 4.3)" ], "Imports": [ "methods" ], "Suggests": [ "RUnit", "BiocGenerics", "BiocStyle", "knitr" ], "License": "Artistic-2.0", "OS_type": "unix", "MD5sum": "e8a271efb0bcf9706bf6baa902549408", "NeedsCompilation": "no", "Title": "An extension of the bigmemory package with added safety, convenience, and a factor class", "Description": "This package defines a \"BigMatrix\" ReferenceClass which adds safety and convenience features to the filebacked.big.matrix class from the bigmemory package. BigMatrix protects against segfaults by monitoring and gracefully restoring the connection to on-disk data and it also protects against accidental data modification with a filesystem-based permissions system. We provide utilities for using BigMatrix-derived classes as assayData matrices within the Biobase package's eSet family of classes. BigMatrix provides some optimizations related to attaching to, and indexing into, file-backed matrices with dimnames. Additionally, the package provides a \"BigMatrixFactor\" class, a file-backed matrix with factor properties.", "biocViews": [ "DataRepresentation", "Infrastructure", "Software" ], "Author": "Peter M. Haverty", "Maintainer": "Peter M. Haverty ", "URL": "https://github.com/phaverty/bigmemoryExtras", "VignetteBuilder": "knitr", "source.ver": "src/contrib/bigmemoryExtras_1.20.0.tar.gz", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/bigmemoryExtras_1.20.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false }, "bioassayR": { "Package": "bioassayR", "Version": "1.12.1", "Depends": [ "R (>= 3.1.0)", "DBI (>= 0.3.1)", "RSQLite (>= 1.0.0)", "methods", "Matrix", "rjson", "BiocGenerics (>= 0.13.8)" ], "Imports": [ "XML", "ChemmineR" ], "Suggests": [ "BiocStyle", "RCurl", "biomaRt", "cellHTS2", "knitr", "knitcitations", "RefManageR", "testthat", "ggplot2" ], "License": "Artistic-2.0", "MD5sum": "42cadec7b8f8ee507cf5239f9cca44a4", "NeedsCompilation": "no", "Title": "Cross-target analysis of small molecule bioactivity", "Description": "bioassayR is a computational tool that enables simultaneous analysis of thousands of bioassay experiments performed over a diverse set of compounds and biological targets. Unique features include support for large-scale cross-target analyses of both public and custom bioassays, generation of high throughput screening fingerprints (HTSFPs), and an optional preloaded database that provides access to a substantial portion of publicly available bioactivity data.", "biocViews": [ "Bioinformatics", "CellBasedAssays", "DataImport", "Infrastructure", "Metabolomics", "MicrotitrePlateAssay", "Proteomics", "Software", "Visualization" ], "Author": "Tyler Backman, Ronly Schlenk, Thomas Girke", "Maintainer": "Tyler Backman ", "URL": "https://github.com/TylerBackman/bioassayR", "VignetteBuilder": "knitr", "BugReports": "https://github.com/TylerBackman/bioassayR/issues", "source.ver": "src/contrib/bioassayR_1.12.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/bioassayR_1.12.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/bioassayR_1.12.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/bioassayR_1.12.1.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/bioassayR/inst/doc/bioassayR.R" ], "htmlDocs": [ "vignettes/bioassayR/inst/doc/bioassayR.html" ], "htmlTitles": [ "Introduction and Examples" ] }, "Biobase": { "Package": "Biobase", "Version": "2.34.0", "Depends": [ "R (>= 2.10)", "BiocGenerics (>= 0.3.2)", "utils" ], "Imports": [ "methods" ], "Suggests": [ "tools", "tkWidgets", "ALL", "RUnit", "golubEsets" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "b761d9241462a4c6403731203c9fbb94", "NeedsCompilation": "yes", "Title": "Biobase: Base functions for Bioconductor", "Description": "Functions that are needed by many other packages or which replace R functions.", "biocViews": [ "Infrastructure", "Software" ], "Author": "R. Gentleman, V. Carey, M. Morgan, S. Falcon", "Maintainer": "Bioconductor Package Maintainer ", "source.ver": "src/contrib/Biobase_2.34.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Biobase_2.34.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Biobase_2.34.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Biobase_2.34.0.tgz", "vignettes": [ "vignettes/Biobase/inst/doc/BiobaseDevelopment.pdf", "vignettes/Biobase/inst/doc/esApply.pdf", "vignettes/Biobase/inst/doc/ExpressionSetIntroduction.pdf" ], "vignetteTitles": [ "Notes for eSet developers", "esApply Introduction", "An introduction to Biobase and ExpressionSets" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Biobase/inst/doc/BiobaseDevelopment.R", "vignettes/Biobase/inst/doc/esApply.R", "vignettes/Biobase/inst/doc/ExpressionSetIntroduction.R" ], "dependsOnMe": [ "a4Base", "a4Core", "ACME", "affy", "affycomp", "affycompData", "affyContam", "affycoretools", "affyPLM", "affyQCReport", "AGDEX", "AgiMicroRna", "AIMS", "ALL", "altcdfenvs", "annaffy", "AnnotationDbi", "AnnotationForge", "antiProfilesData", "ArrayExpress", "arrayMvout", "ArrayTools", "BAGS", "bcellViper", "beadarray", "beadarrayExampleData", "beadarraySNP", "bgx", "BicARE", "bigmelon", "BiocCaseStudies", "bioDist", "BioMVCClass", "BioQC", "birta", "bladderbatch", "BrainStars", "CAMERA", "cancerclass", "cancerdata", "Cardinal", "casper", "Category", "categoryCompare", "CCl4", "CCPROMISE", "cellHTS2", "ceu1kg", "ceuhm3", "CGHbase", "CGHcall", "CGHregions", "charm", "cheung2010", "chimera", "chroGPS", "ClassifyR", "clippda", "CLL", "clusterStab", "CMA", "cn.farms", "codelink", "colonCA", "convert", "copa", "covEB", "covRNA", "CRCL18", "curatedBreastData", "curatedMetagenomicData", "davidTiling", "DESeq", "DEXSeq", "DFP", "diggit", "diggitdata", "DLBCL", "doppelgangR", "dressCheck", "dsQTL", "DSS", "dualKS", "dyebias", "EBarrays", "EDASeq", "edge", "EGSEA", "eisa", "ENmix", "EnrichmentBrowser", "epigenomix", "epivizrData", "etec16s", "ExiMiR", "ExpressionAtlas", "fabia", "fabiaData", "factDesign", "fastseg", "fibroEset", "flowBeads", "frma", "gaga", "gaschYHS", "gCMAPWeb", "GeneAnswers", "GeneExpressionSignature", "GeneMeta", "geneplotter", "geneRecommender", "GeneRegionScan", "GeneSelectMMD", "GeneSelector", "geNetClassifier", "GEOquery", "GGdata", "GOexpress", "GOFunction", "golubEsets", "goProfiles", "GOstats", "GSE62944", "GSEABase", "GSEAlm", "GSVAdata", "GWASTools", "hapFabia", "harbChIP", "HCsnip", "HELP", "Hiiragi2013", "hmyriB36", "hopach", "HTqPCR", "htSeqTools", "HumanAffyData", "humanStemCell", "HybridMTest", "iBMQ", "iCheck", "IdeoViz", "idiogram", "InPAS", "INSPEcT", "isobar", "iterativeBMA", "Iyer517", "kidpack", "leeBamViews", "leukemiasEset", "LMGene", "lumi", "lumiBarnes", "lungExpression", "macat", "mAPKL", "MAQCsubset", "MAQCsubsetAFX", "MAQCsubsetILM", "maSigPro", "massiR", "MEAL", "MergeMaid", "metabomxtr", "metagenomeFeatures", "metagenomeSeq", "MethPed", "methyAnalysis", "methylumi", "Mfuzz", "MiChip", "MIMOSA", "MineICA", "minfi", "MiRaGE", "miRcomp", "miRNATarget", "MLInterfaces", "MLSeq", "MMDiff2", "MmPalateMiRNA", "monocle", "msd16s", "MSnbase", "Mulcom", "MultiDataSet", "multtest", "mvoutData", "NanoStringDiff", "Neve2006", "NOISeq", "nondetects", "normalize450K", "NormqPCR", "oligo", "oneChannelGUI", "OrderedList", "OTUbase", "OutlierD", "PADOG", "pandaR", "PAnnBuilder", "panp", "pcaMethods", "pcot2", "pdInfoBuilder", "pdmclass", "pepStat", "PGSEA", "phenoTest", "PLPE", "plrs", "prada", "PREDA", "PREDAsampledata", "ProData", "pRolocGUI", "PROMISE", "prostateCancerCamcap", "prostateCancerGrasso", "prostateCancerStockholm", "prostateCancerTaylor", "prostateCancerVarambally", "prot2D", "pumadata", "qpcrNorm", "R453Plus1Toolbox", "RbcBook1", "rbsurv", "rcellminer", "rcellminerData", "ReadqPCR", "reb", "RefPlus", "rHVDM", "Ringo", "Risa", "Rmagpie", "rMAT", "RNAinteract", "rnaSeqMap", "Rnits", "Roleswitch", "RpsiXML", "RTCA", "RTopper", "RUVnormalizeData", "RUVSeq", "safe", "SCAN.UPC", "scater", "SeqGSEA", "sigaR", "SigCheck", "siggenes", "simpleaffy", "simulatorZ", "SpeCond", "SPEM", "SpikeInSubset", "spkTools", "splicegear", "spliceSites", "splineTimeR", "stepwiseCM", "SummarizedExperiment", "TCGAcrcmiRNA", "TCGAcrcmRNA", "TDARACNE", "tigre", "tilingArray", "topGO", "tRanslatome", "tspair", "tweeDEseqCountData", "twilight", "UNDO", "variancePartition", "VegaMC", "viper", "vsn", "wateRmelon", "waveTiling", "webbioc", "xcms", "XDE", "yarn", "yeastCC" ], "importsMe": [ "ABarray", "aCGH", "adSplit", "affyILM", "affyQCReport", "AgiMicroRna", "AnalysisPageServer", "annmap", "annotate", "AnnotationDbi", "AnnotationHubData", "annotationTools", "ArrayExpressHTS", "arrayQualityMetrics", "ArrayTools", "attract", "ballgown", "BayesKnockdown", "betr", "BgeeDB", "biobroom", "bioCancer", "biocViews", "BioNet", "BioSeqClass", "biosigner", "biosvd", "birte", "BiSeq", "blima", "BrainStars", "bsseq", "BubbleTree", "CAFE", "canceR", "ccTutorial", "ceu1kgv", "cgdv17", "CGHnormaliter", "charm", "ChIPpeakAnno", "ChIPQC", "ChIPXpress", "ChromHeatMap", "clipper", "cn.mops", "cogena", "ConsensusClusterPlus", "crlmm", "crossmeta", "cummeRbund", "cycle", "cytofkit", "CytoML", "ddCt", "DESeq2", "DeSousa2013", "destiny", "diffloop", "DOQTL", "easyRNASeq", "EBarrays", "ecolitk", "EGAD", "ensembldb", "erma", "esetVis", "ExiMiR", "farms", "ffpe", "FindMyFriends", "Fletcher2013a", "flowClust", "flowCore", "flowFP", "flowMatch", "flowMeans", "flowStats", "flowType", "flowUtils", "flowViz", "flowWorkspace", "FourCSeq", "frma", "frmaTools", "FunciSNP", "gCMAP", "gCrisprTools", "gcrma", "genbankr", "genefilter", "GeneMeta", "geneRecommender", "GeneRegionScan", "GeneSelectMMD", "GENESIS", "GenomicFeatures", "GenomicInteractions", "GEOsubmission", "gespeR", "GGBase", "ggbio", "GGtools", "girafe", "globaltest", "gmapR", "GOFunction", "GOstats", "gQTLstats", "GSRI", "GSVA", "Gviz", "Harshlight", "HEM", "HTqPCR", "HTSFilter", "IdMappingAnalysis", "IHWpaper", "imageHTS", "ImmuneSpaceR", "IsoGeneGUI", "JunctionSeq", "KEGGandMetacoreDzPathwaysGEO", "KEGGdzPathwaysGEO", "kimod", "lapmix", "LINC", "LiquidAssociation", "LVSmiRNA", "maanova", "MafDb.ESP6500SI.V2.SSA137", "makecdfenv", "maSigPro", "MAST", "mBPCR", "MCRestimate", "MeSHDbi", "metaArray", "methyAnalysis", "MethylAid", "methylumi", "MiChip", "MinimumDistance", "MiPP", "mmnet", "MmPalateMiRNA", "mogsa", "MoonlightR", "MoPS", "MSnID", "MultiAssayExperiment", "multiscan", "mzR", "NanoStringQCPro", "ncdfFlow", "npGSEA", "nucleR", "OGSA", "oligoClasses", "openCyto", "oposSOM", "oppar", "OrderedList", "OrganismDbi", "PAnnBuilder", "panp", "Pbase", "pbcmc", "PCpheno", "PharmacoGx", "phyloseq", "piano", "plateCore", "plethy", "plgem", "plier", "podkat", "ppiStats", "prada", "prebs", "proFIA", "pRoloc", "pRolocdata", "PROMISE", "ProteomicsAnnotationHubData", "PSEA", "psygenet2r", "puma", "pvac", "pvca", "pwOmics", "qcmetrics", "QDNAseq", "qpgraph", "QUALIFIER", "quantro", "QuasR", "qusage", "randPack", "readat", "ReadqPCR", "ReportingTools", "RforProteomics", "RGalaxy", "Rmagpie", "RMassBank", "rMAT", "rols", "ropls", "ROTS", "rqubic", "Rtreemix", "RUVnormalize", "SAGx", "scran", "SeqVarTools", "ShortRead", "sigsquared", "SimBindProfiles", "simpleaffy", "SLGI", "SMITE", "SNPchip", "SomaticSignatures", "spkTools", "splicegear", "STATegRa", "subSeq", "switchde", "synapter", "TCGAbiolinks", "TEQC", "TFBSTools", "timecourse", "ToPASeq", "TPP", "TSSi", "twilight", "uSORT", "VanillaICE", "VariantAnnotation", "VariantFiltering", "VariantTools", "wateRmelon", "XBSeq", "XDE", "yri1kgv" ], "suggestsMe": [ "betr", "BiocCaseStudies", "BiocCheck", "BiocGenerics", "breastCancerMAINZ", "breastCancerNKI", "breastCancerTRANSBIG", "breastCancerUNT", "breastCancerUPP", "breastCancerVDX", "BSgenome", "ccTutorial", "CellMapper", "cellTree", "clustComp", "CountClust", "DAPAR", "DART", "dyebiasexamples", "epivizr", "epivizrStandalone", "farms", "genefu", "GenomicRanges", "GlobalAncova", "GSAR", "Heatplus", "interactiveDisplay", "kebabs", "les", "limma", "mammaPrintData", "mAPKLData", "messina", "msa", "multiClust", "nem", "OSAT", "pkgDepTools", "rheumaticConditionWOLLBOLD", "ROC", "RTCGA", "SeqArray", "seventyGeneData", "survcomp", "TargetScore", "tkWidgets", "TypeInfo", "vbmp", "widgetTools", "yeastExpData", "yeastRNASeq" ] }, "biobroom": { "Package": "biobroom", "Version": "1.6.0", "Depends": [ "R (>= 3.0.0)", "broom" ], "Imports": [ "dplyr", "tidyr", "Biobase" ], "Suggests": [ "limma", "DESeq2", "airway", "ggplot2", "plyr", "GenomicRanges", "testthat", "magrittr", "edgeR", "qvalue", "knitr", "data.table", "MSnbase", "SummarizedExperiment" ], "License": "LGPL", "MD5sum": "ad38a2b50d66222735fd3080057714c6", "NeedsCompilation": "no", "Title": "Turn Bioconductor objects into tidy data frames", "Description": "This package contains methods for converting standard objects constructed by bioinformatics packages, especially those in Bioconductor, and converting them to tidy data. It thus serves as a complement to the broom package, and follows the same the tidy, augment, glance division of tidying methods. Tidying data makes it easy to recombine, reshape and visualize bioinformatics analyses.", "biocViews": [ "DataImport", "DifferentialExpression", "GeneExpression", "MultipleComparison", "Proteomics", "Regression", "Software" ], "Author": "Andrew J. Bass, David G. Robinson, Steve Lianoglou, Emily Nelson, John D. Storey, with contributions from Laurent Gatto", "Maintainer": "John D. Storey and Andrew J. Bass ", "URL": "https://github.com/StoreyLab/biobroom", "VignetteBuilder": "knitr", "BugReports": "https://github.com/StoreyLab/biobroom/issues", "source.ver": "src/contrib/biobroom_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/biobroom_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/biobroom_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/biobroom_1.6.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/biobroom/inst/doc/biobroom_vignette.R" ], "htmlDocs": [ "vignettes/biobroom/inst/doc/biobroom_vignette.html" ], "htmlTitles": [ "Vignette Title" ] }, "bioCancer": { "Package": "bioCancer", "Version": "1.2.0", "Depends": [ "magrittr (>= 1.5)", "ggplot2 (>= 1.0.0)", "lubridate (>= 1.3.3)", "tidyr (>= 0.3.1)", "cgdsr", "RCurl", "XML" ], "Imports": [ "dplyr (>= 0.4.3)", "htmlwidgets", "Biobase", "geNetClassifier", "AnnotationFuncs", "org.Hs.eg.db", "DOSE", "clusterProfiler", "reactome.db", "ReactomePA", "plyr", "grDevices", "stats", "utils", "DiagrammeR(>= 0.7)", "visNetwork", "car", "MASS (>= 7.3)", "gridExtra (>= 2.0.0)", "AlgDesign (>= 1.1.7.3)", "psych (>= 1.4.8.11)", "GPArotation (>= 2014.11.1)", "wordcloud (>= 2.5)", "markdown (>= 0.7.4)", "knitr (>= 1.8)", "ggdendro (>= 0.1.17)", "broom (>= 0.3.7)", "pryr (>= 0.1)", "shiny (>= 0.13.2)", "jsonlite (>= 0.9.17)", "shinyAce (>= 0.1)", "DT (>= 0.1)", "readr (>= 0.1.1)", "data.tree(>= 0.2.1)", "yaml(>= 2.1.13)", "scales(>= 0.2.5)", "curl(>= 0.9.1)", "covr (>= 1.2.0)", "stringr (>= 1.0)", "tibble" ], "Suggests": [ "BiocStyle", "rmarkdown", "testthat (>= 0.10.0)" ], "License": "AGPL-3 | file LICENSE", "MD5sum": "7b5503c7f612e6c928d42005a31f1c2e", "NeedsCompilation": "no", "Title": "Interactive Multi-Omics Cancers Data Visualization and Analysis", "Description": "bioCancer is a Shiny App to visualize and analyse interactively Multi-Assays of Cancer Genomic Data.", "biocViews": [ "DataRepresentation", "GUI", "GeneExpression", "GeneTarget", "MultipleComparison", "Network", "Pathways", "Reactome", "Software", "Visualization" ], "Author": "Karim Mezhoud [aut, cre]", "Maintainer": "Karim Mezhoud ", "URL": "http://kmezhoud.github.io/bioCancer", "VignetteBuilder": "knitr", "BugReports": "https://github.com/kmezhoud/bioCancer/issues", "source.ver": "src/contrib/bioCancer_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/bioCancer_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/bioCancer_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/bioCancer_1.2.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/bioCancer/inst/doc/bioCancer.R" ], "htmlDocs": [ "vignettes/bioCancer/inst/doc/bioCancer.html" ], "htmlTitles": [ "bioCancer: Interactive Multi-OMICS Cancers Data Visualization and Analysis" ] }, "BiocCaseStudies": { "Package": "BiocCaseStudies", "Version": "1.36.0", "Depends": [ "tools", "methods", "utils", "Biobase" ], "Suggests": [ "affy (>= 1.17.3)", "affyPLM (>= 1.15.1)", "affyQCReport (>= 1.17.0)", "ALL (>= 1.4.3)", "annaffy (>= 1.11.1)", "annotate (>= 1.17.3)", "AnnotationDbi (>= 1.1.6)", "apComplex (>= 2.5.0)", "Biobase (>= 1.17.5)", "bioDist (>= 1.11.3)", "biocGraph (>= 1.1.1)", "biomaRt (>= 1.13.5)", "CCl4 (>= 1.0.6)", "CLL (>= 1.2.4)", "Category (>= 2.5.0)", "class (>= 7.2-38)", "cluster (>= 1.11.9)", "convert (>= 1.15.0)", "gcrma (>= 2.11.1)", "genefilter (>= 1.17.6)", "geneplotter (>= 1.17.2)", "GO.db (>= 2.0.2)", "GOstats (>= 2.5.0)", "graph (>= 1.17.4)", "GSEABase (>= 1.1.13)", "hgu133a.db (>= 2.0.2)", "hgu95av2.db", "hgu95av2cdf (>= 2.0.0)", "hgu95av2probe (>= 2.0.0)", "hopach (>= 1.13.0)", "KEGG.db (>= 2.0.2)", "kohonen (>= 2.0.2)", "lattice (>= 0.17.2)", "latticeExtra (>= 0.3-1)", "limma (>= 2.13.1)", "MASS (>= 7.2-38)", "MLInterfaces (>= 1.13.17)", "multtest (>= 1.19.0)", "org.Hs.eg.db (>= 2.0.2)", "ppiStats (>= 1.5.4)", "randomForest (>= 4.5-20)", "RBGL (>= 1.15.6)", "RColorBrewer (>= 1.0-2)", "Rgraphviz (>= 1.17.11)", "vsn (>= 3.4.0)", "weaver (>= 1.5.0)", "xtable (>= 1.5-2)", "yeastExpData (>= 0.9.11)" ], "License": "Artistic-2.0", "MD5sum": "bb296f75a0b0676e2dfe002e03f7c91a", "NeedsCompilation": "no", "Title": "BiocCaseStudies: Support for the Case Studies Monograph", "Description": "Software and data to support the case studies.", "biocViews": [ "Infrastructure", "Software" ], "Author": "R. Gentleman, W. Huber, F. Hahne, M. Morgan, S. Falcon", "Maintainer": "Bioconductor Package Maintainer ", "source.ver": "src/contrib/BiocCaseStudies_1.36.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BiocCaseStudies_1.36.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BiocCaseStudies_1.36.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BiocCaseStudies_1.36.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false }, "BiocCheck": { "Package": "BiocCheck", "Version": "1.10.1", "Depends": [ "R (>= 3.3.0)" ], "Imports": [ "biocViews (>= 1.33.7)", "BiocInstaller", "graph", "httr", "tools", "optparse", "codetools", "methods" ], "Suggests": [ "RUnit", "BiocGenerics", "Biobase", "RJSONIO", "rmarkdown", "knitr", "devtools (>= 1.4.1)" ], "Enhances": [ "codetoolsBioC" ], "License": "Artistic-2.0", "MD5sum": "a41b2f9ac73d5f23eb34010b26d73702", "NeedsCompilation": "no", "Title": "Bioconductor-specific package checks", "Description": "Executes Bioconductor-specific package checks.", "biocViews": [ "Infrastructure", "Software" ], "Author": "Bioconductor Package Maintainer [aut, cre]", "Maintainer": "Bioconductor Package Maintainer ", "URL": "https://github.com/Bioconductor/BiocCheck/issues", "VignetteBuilder": "knitr", "source.ver": "src/contrib/BiocCheck_1.10.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BiocCheck_1.10.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BiocCheck_1.10.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BiocCheck_1.10.1.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/BiocCheck/inst/doc/BiocCheck.R" ], "htmlDocs": [ "vignettes/BiocCheck/inst/doc/BiocCheck.html" ], "htmlTitles": [ "BiocCheck" ], "importsMe": [ "ExperimentHubData" ], "suggestsMe": [ "CNPBayes", "curatedMetagenomicData" ] }, "BiocGenerics": { "Package": "BiocGenerics", "Version": "0.20.0", "Depends": [ "methods", "utils", "graphics", "stats", "parallel" ], "Imports": [ "methods", "utils", "graphics", "stats", "parallel" ], "Suggests": [ "Biobase", "S4Vectors", "IRanges", "GenomicRanges", "AnnotationDbi", "oligoClasses", "oligo", "affyPLM", "flowClust", "affy", "DESeq2", "MSnbase", "annotate", "RUnit" ], "License": "Artistic-2.0", "MD5sum": "acb8cb2256a0aca5ac0d66c4ce30a9da", "NeedsCompilation": "no", "Title": "S4 generic functions for Bioconductor", "Description": "S4 generic functions needed by many Bioconductor packages.", "biocViews": [ "Infrastructure", "Software" ], "Author": "The Bioconductor Dev Team", "Maintainer": "Bioconductor Package Maintainer ", "source.ver": "src/contrib/BiocGenerics_0.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BiocGenerics_0.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BiocGenerics_0.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BiocGenerics_0.20.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "dependsOnMe": [ "ACME", "affy", "affyPLM", "altcdfenvs", "AnnotationDbi", "AnnotationForge", "AnnotationHub", "ASpli", "beadarray", "bioassayR", "Biobase", "Biostrings", "BSgenome", "bsseq", "Cardinal", "Category", "categoryCompare", "ChAMPdata", "chipseq", "ChIPseqR", "ChromHeatMap", "cleanUpdTSeq", "codelink", "consensusSeekeR", "copynumber", "CRISPRseek", "cummeRbund", "DESeq", "dexus", "ensembldb", "ensemblVEP", "ExperimentHub", "ExperimentHubData", "FEM", "flowQ", "geneplotter", "GenomeInfoDb", "genomeIntervals", "GenomicAlignments", "GenomicFeatures", "GenomicFiles", "GenomicRanges", "Genominator", "genoset", "ggbio", "girafe", "graph", "GSEABase", "GUIDEseq", "HDF5Array", "HelloRanges", "htSeqTools", "interactiveDisplay", "interactiveDisplayBase", "IRanges", "MBASED", "MeSHDbi", "meshr", "methyAnalysis", "MineICA", "minfi", "MLInterfaces", "MotifDb", "MotIV", "MSnbase", "multtest", "oligo", "OrganismDbi", "pandaR", "Pbase", "PICS", "plethy", "PSICQUIC", "PWMEnrich", "RareVariantVis", "REDseq", "Repitools", "rMAT", "RNAprobR", "RnBeads", "RPA", "rsbml", "S4Vectors", "scsR", "shinyMethyl", "ShortRead", "simpleaffy", "simulatorZ", "soGGi", "TEQC", "tigre", "topGO", "UNDO", "UniProt.ws", "VanillaICE", "VariantAnnotation", "VariantFiltering", "xcms", "XVector", "yamss" ], "importsMe": [ "affycoretools", "AllelicImbalance", "AneuFinder", "annmap", "annotate", "AnnotationDbi", "AnnotationHubData", "ArrayExpressHTS", "bamsignals", "biocGraph", "Biostrings", "biosvd", "biovizBase", "BiSeq", "blima", "BrowserViz", "BrowserVizDemo", "BSgenome", "BubbleTree", "bumphunter", "casper", "cgdv17", "cghMCR", "ChemmineDrugs", "ChemmineOB", "ChemmineR", "ChIPComp", "chipenrich.data", "ChIPpeakAnno", "ChIPQC", "ChIPseeker", "chipseq", "cn.mops", "CNEr", "CNPBayes", "cobindR", "compEpiTools", "crlmm", "crossmeta", "csaw", "cummeRbund", "curatedCRCData", "curatedOvarianData", "ddCt", "DESeq2", "destiny", "DEXSeq", "diffHic", "DirichletMultinomial", "DOQTL", "DRIMSeq", "DrugVsDisease", "easyRNASeq", "EBImage", "EDASeq", "eiR", "eisa", "ELMER", "epigenomix", "epivizrStandalone", "erma", "FamAgg", "fastseg", "ffpe", "FindMyFriends", "flowBin", "flowClust", "flowCore", "flowFP", "flowQ", "FlowSOM", "flowStats", "flowWorkspace", "fmcsR", "frma", "FunciSNP", "gCMAPWeb", "genbankr", "geneAttribution", "GenomicAlignments", "GenomicInteractions", "GenomicTuples", "genotypeeval", "GenVisR", "GGBase", "GGtools", "goseq", "GOTHiC", "gQTLBase", "gQTLstats", "GSVA", "Gviz", "gwascat", "hiReadsProcessor", "hopach", "HTSeqGenie", "IHW", "IHWpaper", "INSPEcT", "intansv", "InteractionSet", "IONiseR", "isomiRs", "IVAS", "JunctionSeq", "KCsmart", "KEGGandMetacoreDzPathwaysGEO", "KEGGdzPathwaysGEO", "LOLA", "LVSmiRNA", "M3D", "MAST", "matter", "MEAL", "metaMS", "MethylAid", "methylPipe", "methylumi", "MinimumDistance", "MiRaGE", "mogsa", "monocle", "motifbreakR", "msa", "MultiAssayExperiment", "MultiDataSet", "MutationalPatterns", "mzR", "NarrowPeaks", "ncdfFlow", "npGSEA", "nucleR", "oligoClasses", "parglms", "pbcmc", "pcaMethods", "pdInfoBuilder", "phyloseq", "piano", "PING", "plrs", "podkat", "prada", "ProCoNA", "profileScoreDist", "pRoloc", "pwOmics", "qsea", "QuasR", "R3CPET", "R453Plus1Toolbox", "RCAS", "RCyjs", "RCytoscape", "recoup", "REDseq", "RefNet", "ReportingTools", "RGalaxy", "RGSEA", "RiboProfiling", "Ringo", "rMAT", "roar", "Rqc", "rqubic", "Rsamtools", "rsbml", "rtracklayer", "scater", "scran", "SGSeq", "signeR", "simpleaffy", "SLGI", "SNPhood", "SNPlocs.Hsapiens.dbSNP144.GRCh37", "SNPlocs.Hsapiens.dbSNP144.GRCh38", "snpStats", "spliceSites", "SplicingGraphs", "sscu", "STAN", "Streamer", "SummarizedExperiment", "systemPipeR", "systemPipeRdata", "TarSeqQC", "TFBSTools", "transcriptR", "TransView", "triform", "TSSi", "TVTB", "unifiedWMWqPCR", "uSORT", "VariantTools", "wavClusteR", "XDE", "XtraSNPlocs.Hsapiens.dbSNP144.GRCh37", "XtraSNPlocs.Hsapiens.dbSNP144.GRCh38", "XVector" ], "suggestsMe": [ "acde", "AIMS", "ArrayTV", "ASSET", "BaalChIP", "baySeq", "bigmelon", "bigmemoryExtras", "BiocCheck", "BiocInstaller", "BiocParallel", "BiocStyle", "biocViews", "biosigner", "BiRewire", "CAFE", "CAMERA", "CancerSubtypes", "CAnD", "CausalR", "ccrepe", "CellNOptR", "CexoR", "ChIPXpress", "CHRONOS", "CINdex", "clipper", "clonotypeR", "clustComp", "CNORfeeder", "CNORfuzzy", "CNVPanelizer", "coMET", "ConnectivityMap", "cosmiq", "COSNet", "cpvSNP", "cytofkit", "DAPAR", "DBChIP", "DEGreport", "DEsubs", "DMRcaller", "DMRcate", "ENCODExplorer", "ENmix", "fCCAC", "FGNet", "flowCL", "flowQB", "FlowRepositoryR", "focalCall", "gCMAP", "gdsfmt", "GEM", "GENE.E", "GeneNetworkBuilder", "GeneOverlap", "geneplast", "geneRxCluster", "GENESIS", "geNetClassifier", "genomation", "GEOquery", "GMRP", "GOstats", "GraphPAC", "GreyListChIP", "grndata", "GWASTools", "h5vc", "Harman", "HarmanData", "hiAnnotator", "hierGWAS", "hypergraph", "iCARE", "iClusterPlus", "illuminaio", "InPAS", "INPower", "IPO", "kebabs", "KEGGREST", "ldblock", "LINC", "mAPKL", "massiR", "MatrixRider", "MBttest", "mdgsa", "Mergeomics", "MeSH.Aca.eg.db", "MeSH.Aga.PEST.eg.db", "MeSH.Ame.eg.db", "MeSH.Aml.eg.db", "MeSH.Ana.eg.db", "MeSH.Ani.FGSC.eg.db", "MeSH.AOR.db", "MeSH.Ath.eg.db", "MeSH.Bfl.eg.db", "MeSH.Bsu.168.eg.db", "MeSH.Bsu.TUB10.eg.db", "MeSH.Bta.eg.db", "MeSH.Cal.SC5314.eg.db", "MeSH.Cbr.eg.db", "MeSH.Cel.eg.db", "MeSH.Cfa.eg.db", "MeSH.Cin.eg.db", "MeSH.Cja.eg.db", "MeSH.Cpo.eg.db", "MeSH.Cre.eg.db", "MeSH.Dan.eg.db", "MeSH.db", "MeSH.Dda.3937.eg.db", "MeSH.Ddi.AX4.eg.db", "MeSH.Der.eg.db", "MeSH.Dgr.eg.db", "MeSH.Dme.eg.db", "MeSH.Dmo.eg.db", "MeSH.Dpe.eg.db", "MeSH.Dre.eg.db", "MeSH.Dse.eg.db", "MeSH.Dsi.eg.db", "MeSH.Dvi.eg.db", "MeSH.Dya.eg.db", "MeSH.Eco.55989.eg.db", "MeSH.Eco.CFT073.eg.db", "MeSH.Eco.ED1a.eg.db", "MeSH.Eco.HS.eg.db", "MeSH.Eco.IAI1.eg.db", "MeSH.Eco.IAI39.eg.db", "MeSH.Eco.K12.DH10B.eg.db", "MeSH.Eco.K12.MG1655.eg.db", "MeSH.Eco.O127.H6.E2348.69.eg.db", "MeSH.Eco.O157.H7.EDL933.eg.db", "MeSH.Eco.O157.H7.Sakai.eg.db", "MeSH.Eco.S88.eg.db", "MeSH.Eco.UMN026.eg.db", "MeSH.Eqc.eg.db", "MeSH.Gga.eg.db", "MeSH.Gma.eg.db", "MeSH.Hsa.eg.db", "MeSH.Laf.eg.db", "MeSH.Lma.eg.db", "MeSH.Mdo.eg.db", "MeSH.Mes.eg.db", "MeSH.Mga.eg.db", "MeSH.Miy.eg.db", "MeSH.Mml.eg.db", "MeSH.Mmu.eg.db", "MeSH.Mtr.eg.db", "MeSH.Nle.eg.db", "MeSH.Oan.eg.db", "MeSH.Ocu.eg.db", "MeSH.Oni.eg.db", "MeSH.Osa.eg.db", "MeSH.Pab.eg.db", "MeSH.Pae.PAO1.eg.db", "MeSH.PCR.db", "MeSH.Pfa.3D7.eg.db", "MeSH.Pto.eg.db", "MeSH.Ptr.eg.db", "MeSH.Rno.eg.db", "MeSH.Sau.USA300TCH1516.eg.db", "MeSH.Sce.S288c.eg.db", "MeSH.Sco.A32.eg.db", "MeSH.Sil.eg.db", "MeSH.Spo.972h.eg.db", "MeSH.Spu.eg.db", "MeSH.Ssc.eg.db", "MeSH.Syn.eg.db", "MeSH.Tbr.9274.eg.db", "MeSH.Tgo.ME49.eg.db", "MeSH.Tgu.eg.db", "MeSH.Vvi.eg.db", "MeSH.Xla.eg.db", "MeSH.Xtr.eg.db", "MeSH.Zma.eg.db", "Metab", "MetaboSignal", "metagene", "metagenomeSeq", "metaseqR", "MetCirc", "miRcomp", "mirIntegrator", "miRLAB", "Mirsynergy", "motifStack", "MSnID", "multiClust", "MultiMed", "netbenchmark", "netbiov", "NetSAM", "nondetects", "nucleoSim", "OncoScore", "PAA", "Path2PPI", "PathNet", "pathview", "pepXMLTab", "PGA", "PhenStat", "Prize", "proBAMr", "proFIA", "proteoQC", "PureCN", "qpgraph", "quantro", "QuartPAC", "RBGL", "rBiopaxParser", "Rcade", "rcellminer", "rCGH", "Rcpi", "RCy3", "RGraph2js", "Rgraphviz", "rgsepd", "riboSeqR", "ROntoTools", "ropls", "RTN", "rTRM", "sangerseqR", "SANTA", "sapFinder", "segmentSeq", "SeqArray", "seqPattern", "seqTools", "SeqVarTools", "SICtools", "sigsquared", "SIMAT", "similaRpeak", "SIMLR", "SNPRelate", "SpacePAC", "specL", "STATegRa", "STRINGdb", "TCC", "TIN", "ToPASeq", "trackViewer", "traseR", "TRONCO", "Uniquorn" ] }, "biocGraph": { "Package": "biocGraph", "Version": "1.36.0", "Depends": [ "Rgraphviz", "graph" ], "Imports": [ "Rgraphviz", "geneplotter", "graph", "BiocGenerics", "methods" ], "Suggests": [ "fibroEset", "geneplotter", "hgu95av2.db" ], "License": "Artistic-2.0", "MD5sum": "fe5acce159a60fa7e212add3639b6377", "NeedsCompilation": "no", "Title": "Graph examples and use cases in Bioinformatics", "Description": "This package provides examples and code that make use of the different graph related packages produced by Bioconductor.", "biocViews": [ "GraphAndNetwork", "Software", "Visualization" ], "Author": "Li Long , Robert Gentleman , Seth Falcon Florian Hahne ", "Maintainer": "Florian Hahne ", "source.ver": "src/contrib/biocGraph_1.36.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/biocGraph_1.36.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/biocGraph_1.36.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/biocGraph_1.36.0.tgz", "vignettes": [ "vignettes/biocGraph/inst/doc/biocGraph.pdf", "vignettes/biocGraph/inst/doc/layingOutPathways.pdf" ], "vignetteTitles": [ "Examples of plotting graphs Using Rgraphviz", "HOWTO layout pathways" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/biocGraph/inst/doc/biocGraph.R", "vignettes/biocGraph/inst/doc/layingOutPathways.R" ], "importsMe": [ "EnrichmentBrowser" ], "suggestsMe": [ "BiocCaseStudies" ] }, "BiocInstaller": { "Package": "BiocInstaller", "Version": "1.24.0", "Depends": [ "R (>= 3.3.0)" ], "Suggests": [ "devtools", "RUnit", "BiocGenerics" ], "License": "Artistic-2.0", "MD5sum": "dc96d52b89e1eb030e276236dcd5de7e", "NeedsCompilation": "no", "Title": "Install/Update Bioconductor, CRAN, and github Packages", "Description": "This package is used to install and update Bioconductor, CRAN, and (some) github packages.", "biocViews": [ "Infrastructure", "Software" ], "Author": "Dan Tenenbaum and Biocore Team", "Maintainer": "Bioconductor Package Maintainer ", "source.ver": "src/contrib/BiocInstaller_1.24.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BiocInstaller_1.24.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BiocInstaller_1.24.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BiocInstaller_1.24.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "importsMe": [ "affy", "affylmGUI", "AnnotationHub", "AnnotationHubData", "BiocCheck", "ccmap", "ChIPpeakAnno", "crisprseekplus", "crossmeta", "curatedMetagenomicData", "ExperimentHub", "ExperimentHubData", "gcrma", "limmaGUI", "oligoClasses", "OrganismDbi", "ProteomicsAnnotationHubData", "psygenet2r", "QuasR", "RforProteomics", "webbioc" ], "suggestsMe": [ "BSgenome", "curatedMetagenomicData", "GOSemSim", "KEGGlincs", "metaseqR", "pkgDepTools", "recoup", "RNAseqData.HNRNPC.bam.chr14" ] }, "BiocParallel": { "Package": "BiocParallel", "Version": "1.8.2", "Depends": [ "methods" ], "Imports": [ "stats", "utils", "futile.logger", "parallel", "snow" ], "Suggests": [ "BiocGenerics", "tools", "foreach", "BatchJobs", "BBmisc", "doParallel", "Rmpi", "GenomicRanges", "RNAseqData.HNRNPC.bam.chr14", "Rsamtools", "GenomicAlignments", "ShortRead", "codetools", "RUnit", "BiocStyle", "knitr" ], "License": "GPL-2 | GPL-3", "MD5sum": "658584e80b945be76e9a357cf39112dc", "NeedsCompilation": "no", "Title": "Bioconductor facilities for parallel evaluation", "Description": "This package provides modified versions and novel implementation of functions for parallel evaluation, tailored to use with Bioconductor objects.", "biocViews": [ "Infrastructure", "Software" ], "Author": "Bioconductor Package Maintainer [cre], Martin Morgan [aut], Valerie Obenchain [aut], Michel Lang [aut], Ryan Thompson [aut]", "Maintainer": "Bioconductor Package Maintainer ", "URL": "https://github.com/Bioconductor/BiocParallel", "VignetteBuilder": "knitr", "BugReports": "https://github.com/Bioconductor/BiocParallel/issues", "source.ver": "src/contrib/BiocParallel_1.8.2.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BiocParallel_1.8.2.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BiocParallel_1.8.2.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BiocParallel_1.8.2.tgz", "vignettes": [ "vignettes/BiocParallel/inst/doc/Errors_Logs_And_Debugging.pdf", "vignettes/BiocParallel/inst/doc/Introduction_To_BiocParallel.pdf" ], "vignetteTitles": [ "Errors, Logs and Debugging", "Introduction to BiocParallel" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/BiocParallel/inst/doc/Errors_Logs_And_Debugging.R", "vignettes/BiocParallel/inst/doc/Introduction_To_BiocParallel.R" ], "dependsOnMe": [ "bacon", "ClassifyR", "consensusSeekeR", "CopywriteR", "csaw", "DEXSeq", "doppelgangR", "GenomicFiles", "hiReadsProcessor", "INSPEcT", "MBASED", "metagene", "MSnbase", "Oscope", "PCAN", "pRoloc", "Rqc", "scran", "ShortRead", "SigCheck" ], "importsMe": [ "ALDEx2", "ChIPQC", "contiBAIT", "cpvSNP", "CRISPRseek", "CrispRVariants", "dcGSA", "derfinder", "DESeq2", "DiffBind", "DOSE", "DRIMSeq", "easyRNASeq", "EMDomics", "fgsea", "FindMyFriends", "flowcatchR", "gCrisprTools", "GenoGAM", "GenomicAlignments", "genotypeeval", "gmapR", "GUIDEseq", "h5vc", "HTSeqGenie", "HTSFilter", "IHWpaper", "InPAS", "JunctionSeq", "LowMACA", "MethylAid", "motifbreakR", "pbcmc", "proFIA", "qpgraph", "qsea", "QuasR", "recount", "regsplice", "Rsamtools", "RUVcorr", "scde", "SNPhood", "soGGi", "synapter", "TarSeqQC", "TFBSTools", "TVTB", "VariantFiltering", "VariantTools", "xcms" ], "suggestsMe": [ "chimera", "curatedMetagenomicData", "DEGreport", "erma", "MethylAidData", "oneChannelGUI", "SeqArray", "systemPipeR", "tofsims" ] }, "BiocStyle": { "Package": "BiocStyle", "Version": "2.2.1", "Imports": [ "stats", "utils" ], "Suggests": [ "base64enc", "knitr (>= 1.12)", "rmarkdown (>= 1.2)", "BiocGenerics", "RUnit", "yaml", "htmltools" ], "License": "Artistic-2.0", "MD5sum": "82c6a1476060fc3e183f27868b5410c1", "NeedsCompilation": "no", "Title": "Standard styles for vignettes and other Bioconductor documents", "Description": "Provides standard formatting styles for Bioconductor PDF and HTML documents. Package vignettes illustrate use and functionality.", "biocViews": [ "Software" ], "Author": "Andrzej Oleś, Martin Morgan, Wolfgang Huber", "Maintainer": "Bioconductor Package Maintainer ", "URL": "https://github.com/Bioconductor/BiocStyle", "VignetteBuilder": "knitr", "BugReports": "https://github.com/Bioconductor/BiocStyle/issues", "source.ver": "src/contrib/BiocStyle_2.2.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BiocStyle_2.2.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BiocStyle_2.2.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BiocStyle_2.2.1.tgz", "vignettes": [ "vignettes/BiocStyle/inst/doc/LatexStyle.pdf", "vignettes/BiocStyle/inst/doc/LatexStyle2.pdf" ], "vignetteTitles": [ "Bioconductor LaTeX Style", "Bioconductor LaTeX Style 2.0" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/BiocStyle/inst/doc/HtmlStyle.R", "vignettes/BiocStyle/inst/doc/LatexStyle.R", "vignettes/BiocStyle/inst/doc/LatexStyle2.R" ], "htmlDocs": [ "vignettes/BiocStyle/inst/doc/HtmlStyle.html" ], "htmlTitles": [ "Bioconductor style for HTML documents" ], "importsMe": [ "BubbleTree", "PathoStat", "Rqc" ], "suggestsMe": [ "ABAData", "ABAEnrichment", "affycoretools", "AllelicImbalance", "AMOUNTAIN", "AneuFinder", "AnnotationDbi", "AnnotationForge", "AnnotationHub", "AnnotationHubData", "annotatr", "arrayQualityMetrics", "ASGSCA", "ASpli", "BaalChIP", "bacon", "bamsignals", "BayesPeak", "baySeq", "beadarray", "BeadDataPackR", "BgeeDB", "bigmelon", "bigmemoryExtras", "bioassayR", "bioCancer", "BiocParallel", "BiocWorkflowTools", "biomaRt", "biomformat", "biosigner", "BitSeq", "blima", "blimaTestingData", "BPRMeth", "BrowserViz", "BrowserVizDemo", "bsseq", "CAFE", "CancerInSilico", "CAnD", "Cardinal", "CardinalWorkflows", "ccrepe", "cellity", "CellMapper", "CellMapperData", "cellTree", "CexoR", "ChemmineDrugs", "ChemmineOB", "ChemmineR", "Chicago", "ChIPComp", "chipenrich", "ChIPpeakAnno", "ChIPQC", "ChIPseeker", "chromstaR", "ClassifyR", "cleanUpdTSeq", "cleaver", "clipper", "clusterExperiment", "clusterProfiler", "ClusterSignificance", "CNEr", "CNPBayes", "coMET", "compcodeR", "CONFESS", "consensusSeekeR", "contiBAIT", "conumee", "CopyhelpeR", "CopywriteR", "CoRegNet", "COSMIC.67", "cosmiq", "CountClust", "covRNA", "cpvSNP", "CRISPRseek", "CrispRVariants", "ctsGE", "curatedBladderData", "curatedCRCData", "curatedMetagenomicData", "curatedOvarianData", "CVE", "dada2", "dagLogo", "DAPAR", "DChIPRep", "DEFormats", "DEGreport", "derfinder", "derfinderHelper", "derfinderPlot", "DESeq2", "DEXSeq", "DiffBind", "DmelSGI", "DNABarcodes", "doppelgangR", "DOSE", "DRIMSeq", "dSimer", "DSS", "dupRadar", "easyRNASeq", "EBImage", "EDASeq", "EGSEA", "eiR", "ELMER", "ELMER.data", "EmpiricalBrownsMethod", "EnrichmentBrowser", "ensembldb", "epivizr", "epivizrData", "epivizrServer", "epivizrStandalone", "erma", "EWCE", "ExperimentHub", "ExperimentHubData", "FamAgg", "fCCAC", "fCI", "FindMyFriends", "flowcatchR", "flowMap", "FlowSOM", "fmcsR", "FourCSeq", "furrowSeg", "genbankr", "genefilter", "GeneOverlap", "geneplast", "geneXtendeR", "GenoGAM", "GenomeInfoDb", "GenomicAlignments", "GenomicFeatures", "GenomicFiles", "GenomicInteractions", "GenomicRanges", "GenomicTuples", "genoset", "GenVisR", "GeuvadisTranscriptExpr", "ggbio", "Glimma", "GMRP", "GOexpress", "GoogleGenomics", "GOpro", "GOSemSim", "gQTLBase", "gQTLstats", "graphite", "GreyListChIP", "GRmetrics", "groHMM", "GSAR", "GSE62944", "GUIDEseq", "Gviz", "Harman", "HarmanData", "HD2013SGI", "HDF5Array", "HelloRanges", "HelloRangesData", "Hiiragi2013", "HiTC", "hpar", "HTSFilter", "HumanAffyData", "iGC", "IHW", "IHWpaper", "illuminaio", "imageHTS", "Imetagene", "immunoClust", "InPAS", "INSPEcT", "InteractionSet", "IONiseR", "isomiRs", "IVAS", "JctSeqData", "JunctionSeq", "Linnorm", "LowMACA", "lpsymphony", "M3D", "mAPKL", "MatrixRider", "matter", "MBASED", "MBttest", "mdgsa", "MEAL", "MEDIPS", "meshes", "messina", "MetaboSignal", "metagene", "MethPed", "MethylAid", "MethylAidData", "MethylMix", "minfi", "minionSummaryData", "miRcomp", "missMethyl", "MMDiff2", "MODA", "mogsa", "MoonlightR", "motifbreakR", "motifStack", "mQTL.NMR", "MSnbase", "MSnID", "msPurity", "msqc1", "MultiAssayExperiment", "MutationalPatterns", "mygene", "myvariant", "mzR", "NanoStringDiff", "NanoStringQCPro", "NarrowPeaks", "netbiov", "nethet", "netprioR", "nondetects", "normr", "npGSEA", "nucleoSim", "oligo", "omicade4", "OmicsMarkeR", "OncoScore", "OncoSimulR", "OperaMate", "Oscope", "PAA", "PANTHER.db", "PanVizGenerator", "parathyroidSE", "PasillaTranscriptExpr", "Path2PPI", "paxtoolsr", "Pbase", "pcaExplorer", "PCAN", "PCHiCdata", "PGA", "PGPC", "philr", "phyloseq", "Pi", "Pigengene", "plethy", "Polyfit", "pqsfinder", "profileScoreDist", "pRoloc", "pRolocGUI", "PROPER", "Prostar", "ProteomicsAnnotationHubData", "proteoQC", "PSEA", "PureCN", "PWMEnrich", "qcmetrics", "QDNAseq", "qpgraph", "qsea", "quantro", "QuasR", "R3CPET", "rain", "Rcade", "rcellminer", "rcellminerData", "rCGH", "RCyjs", "rDGIdb", "ReactomePA", "recount", "recoup", "RefNet", "regioneR", "regionReport", "regsplice", "ReQON", "RforProteomics", "rfPred", "RGraph2js", "RGSEA", "rhdf5", "Rhtslib", "RiboProfiling", "riboSeqR", "RNAprobR", "rnaseqcomp", "RnaSeqSampleSize", "RnaSeqSampleSizeData", "Rnits", "rols", "ropls", "rpx", "Rsamtools", "RTCGAToolbox", "RUVcorr", "RUVSeq", "sangerseqR", "sapFinder", "scater", "SCLCBam", "scran", "scRNAseq", "segmentSeq", "seqPattern", "seqplots", "SeqVarTools", "SGSeq", "shinyMethyl", "ShortRead", "SigCheck", "SigFuge", "similaRpeak", "SIMLR", "simulatorZ", "sincell", "Single.mTEC.Transcriptomes", "SNPediaR", "SNPhood", "SNPhoodData", "soGGi", "specL", "SpidermiR", "SPLINTER", "SSPA", "STAN", "StarBioTrek", "STATegRa", "statTarget", "SummarizedExperiment", "sva", "SVAPLSseq", "switchde", "synapter", "systemPipeR", "systemPipeRdata", "TCGAbiolinks", "TFBSTools", "tigre", "TimerQuant", "TPP", "tracktables", "trackViewer", "transcriptR", "traseR", "TRONCO", "TurboNorm", "TVTB", "variancePartition", "VariantAnnotation", "VariantFiltering", "vsn", "wavClusteR", "XBSeq", "xcms", "yamss", "YAPSA", "yriMulti", "zebrafishRNASeq" ], "dependsOnMe": [ "curatedBreastData" ] }, "biocViews": { "Package": "biocViews", "Version": "1.42.0", "Depends": [ "R (>= 2.4.0)" ], "Imports": [ "Biobase", "graph (>= 1.9.26)", "methods", "RBGL (>= 1.13.5)", "tools", "utils", "XML", "RCurl", "RUnit" ], "Suggests": [ "BiocGenerics", "knitr" ], "License": "Artistic-2.0", "MD5sum": "d6a88cec44b6863829c88591a2863d74", "NeedsCompilation": "no", "Title": "Categorized views of R package repositories", "Description": "structures for vocabularies and narratives of views", "biocViews": [ "Infrastructure", "Software" ], "Author": "VJ Carey , BJ Harshfield , S Falcon , Sonali Arora", "Maintainer": "Bioconductor Package Maintainer ", "URL": "http://www.bioconductor.org/packages/release/BiocViews.html", "source.ver": "src/contrib/biocViews_1.42.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/biocViews_1.42.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/biocViews_1.42.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/biocViews_1.42.0.tgz", "vignettes": [ "vignettes/biocViews/inst/doc/createReposHtml.pdf", "vignettes/biocViews/inst/doc/HOWTO-BCV.pdf" ], "vignetteTitles": [ "biocViews-CreateRepositoryHTML", "biocViews-HOWTO" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/biocViews/inst/doc/createReposHtml.R", "vignettes/biocViews/inst/doc/HOWTO-BCV.R" ], "dependsOnMe": [ "Risa" ], "importsMe": [ "BiocCheck", "RforProteomics" ] }, "BiocWorkflowTools": { "Package": "BiocWorkflowTools", "Version": "1.0.0", "Depends": [ "R (>= 3.3)" ], "Imports": [ "rmarkdown", "tools", "stringr", "httr", "knitr", "utils" ], "Suggests": [ "BiocStyle" ], "License": "MIT + file LICENSE", "MD5sum": "8dcb30527f1bf9752b13538928e2d3e4", "NeedsCompilation": "no", "Title": "Tools to aid the development of Bioconductor Workflow packages", "Description": "Provides functions to ease the transition between Rmarkdown and LaTeX documents when authoring a Bioconductor Workflow.", "biocViews": [ "ReportWriting", "Software" ], "Author": "Mike Smith [aut, cre]", "Maintainer": "Mike Smith ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/BiocWorkflowTools_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BiocWorkflowTools_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BiocWorkflowTools_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BiocWorkflowTools_1.0.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/BiocWorkflowTools/inst/doc/Generate_F1000_Latex.R" ], "htmlDocs": [ "vignettes/BiocWorkflowTools/inst/doc/Generate_F1000_Latex.html" ], "htmlTitles": [ "Converting Rmarkdown to F1000Research LaTeX Format" ] }, "bioDist": { "Package": "bioDist", "Version": "1.46.0", "Depends": [ "R (>= 2.0)", "methods", "Biobase", "KernSmooth" ], "Suggests": [ "locfit" ], "License": "Artistic-2.0", "MD5sum": "de8934d0577aeda7f1fe6be24022f581", "NeedsCompilation": "no", "Title": "Different distance measures", "Description": "A collection of software tools for calculating distance measures.", "biocViews": [ "Classification", "Clustering", "Software" ], "Author": "B. Ding, R. Gentleman and Vincent Carey", "Maintainer": "Bioconductor Package Maintainer ", "source.ver": "src/contrib/bioDist_1.46.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/bioDist_1.46.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/bioDist_1.46.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/bioDist_1.46.0.tgz", "vignettes": [ "vignettes/bioDist/inst/doc/bioDist.pdf" ], "vignetteTitles": [ "bioDist Introduction" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/bioDist/inst/doc/bioDist.R" ], "dependsOnMe": [ "flowQ" ], "suggestsMe": [ "BiocCaseStudies" ] }, "biomaRt": { "Package": "biomaRt", "Version": "2.30.0", "Depends": [ "methods" ], "Imports": [ "utils", "XML", "RCurl", "AnnotationDbi" ], "Suggests": [ "annotate", "BiocStyle", "knitr", "rmarkdown" ], "License": "Artistic-2.0", "MD5sum": "755c380b1af0d577881bc152fc11418e", "NeedsCompilation": "no", "Title": "Interface to BioMart databases (e.g. Ensembl, COSMIC, Wormbase and Gramene)", "Description": "In recent years a wealth of biological data has become available in public data repositories. Easy access to these valuable data resources and firm integration with data analysis is needed for comprehensive bioinformatics data analysis. biomaRt provides an interface to a growing collection of databases implementing the BioMart software suite (http://www.biomart.org). The package enables retrieval of large amounts of data in a uniform way without the need to know the underlying database schemas or write complex SQL queries. Examples of BioMart databases are Ensembl, COSMIC, Uniprot, HGNC, Gramene, Wormbase and dbSNP mapped to Ensembl. These major databases give biomaRt users direct access to a diverse set of data and enable a wide range of powerful online queries from gene annotation to database mining.", "biocViews": [ "Annotation", "Software" ], "Author": "Steffen Durinck , Wolfgang Huber", "Maintainer": "Steffen Durinck ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/biomaRt_2.30.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/biomaRt_2.30.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/biomaRt_2.30.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/biomaRt_2.30.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/biomaRt/inst/doc/biomaRt.R" ], "htmlDocs": [ "vignettes/biomaRt/inst/doc/biomaRt.html" ], "htmlTitles": [ "The biomaRt users guide" ], "dependsOnMe": [ "chromPlot", "coMET", "customProDB", "dagLogo", "domainsignatures", "DrugVsDisease", "genefu", "GenomeGraphs", "MineICA", "PSICQUIC", "Roleswitch", "Sushi", "VegaMC" ], "importsMe": [ "ArrayExpressHTS", "BadRegionFinder", "ChIPpeakAnno", "CHRONOS", "cobindR", "customProDB", "DEXSeq", "diffloop", "DOQTL", "easyRNASeq", "EDASeq", "EWCE", "GenomicFeatures", "GenVisR", "gespeR", "GOexpress", "Gviz", "HTSanalyzeR", "IdMappingRetrieval", "isobar", "KEGGprofile", "MEDIPS", "MetaboSignal", "metaseqR", "methyAnalysis", "MGFR", "OncoScore", "oposSOM", "Pbase", "pcaExplorer", "PGA", "phenoTest", "pRoloc", "psygenet2r", "pwOmics", "R453Plus1Toolbox", "RCAS", "recoup", "rgsepd", "RNAither", "RnaSeqSampleSize", "scater", "seq2pathway", "SeqGSEA", "SPLINTER", "TCGAbiolinks", "yarn" ], "suggestsMe": [ "AnnotationForge", "bioassayR", "BiocCaseStudies", "ccTutorial", "cellTree", "chromstaR", "DEGreport", "GeneAnswers", "Genominator", "h5vc", "leeBamViews", "LINC", "massiR", "MineICA", "MiRaGE", "MutationalPatterns", "oligo", "oligo", "oneChannelGUI", "OrganismDbi", "paxtoolsr", "piano", "Pigengene", "pqsfinder", "R3CPET", "Rcade", "RforProteomics", "RIPSeeker", "RnaSeqTutorial", "RnBeads", "rTANDEM", "rTRM", "ShortRead", "SIM", "sincell", "systemPipeR", "trackViewer" ] }, "biomformat": { "Package": "biomformat", "Version": "1.2.0", "Depends": [ "R (>= 3.2)", "methods" ], "Imports": [ "plyr (>= 1.8)", "jsonlite (>= 0.9.16)", "Matrix (>= 1.2)", "rhdf5" ], "Suggests": [ "testthat (>= 0.10)", "knitr (>= 1.10)", "BiocStyle (>= 1.6)", "rmarkdown (>= 0.7)" ], "License": "GPL-2", "MD5sum": "0a418f48c731375953ff7389b9b6f7a0", "NeedsCompilation": "no", "Title": "An interface package for the BIOM file format", "Description": "This is an R package for interfacing with the BIOM format. This package includes basic tools for reading biom-format files, accessing and subsetting data tables from a biom object (which is more complex than a single table), as well as limited support for writing a biom-object back to a biom-format file. The design of this API is intended to match the python API and other tools included with the biom-format project, but with a decidedly \"R flavor\" that should be familiar to R users. This includes S4 classes and methods, as well as extensions of common core functions/methods.", "biocViews": [ "DataImport", "Metagenomics", "Microbiome", "Software" ], "Author": "Paul J. McMurdie and Joseph N Paulson ", "Maintainer": "Paul J. McMurdie ", "URL": "https://github.com/joey711/biomformat/, http://biom-format.org/", "VignetteBuilder": "knitr", "BugReports": "https://github.com/joey711/biomformat/issues", "source.ver": "src/contrib/biomformat_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/biomformat_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/biomformat_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/biomformat_1.2.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/biomformat/inst/doc/biomformat.R" ], "htmlDocs": [ "vignettes/biomformat/inst/doc/biomformat.html" ], "htmlTitles": [ "The biomformat package Vignette" ], "importsMe": [ "phyloseq" ], "suggestsMe": [ "metagenomeSeq" ] }, "BioMVCClass": { "Package": "BioMVCClass", "Version": "1.42.0", "Depends": [ "R (>= 2.1.0)", "methods", "MVCClass", "Biobase", "graph", "Rgraphviz" ], "License": "LGPL", "MD5sum": "27cfd9f3eb8cb174b80cde9211212662", "NeedsCompilation": "no", "Title": "Model-View-Controller (MVC) Classes That Use Biobase", "Description": "Creates classes used in model-view-controller (MVC) design", "biocViews": [ "GraphAndNetwork", "Infrastructure", "Software", "Visualization" ], "Author": "Elizabeth Whalen", "Maintainer": "Elizabeth Whalen ", "source.ver": "src/contrib/BioMVCClass_1.42.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BioMVCClass_1.42.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BioMVCClass_1.42.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BioMVCClass_1.42.0.tgz", "vignettes": [ "vignettes/BioMVCClass/inst/doc/BioMVCClass.pdf" ], "vignetteTitles": [ "BioMVCClass" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false }, "biomvRCNS": { "Package": "biomvRCNS", "Version": "1.14.0", "Depends": [ "IRanges", "GenomicRanges", "Gviz" ], "Imports": [ "methods", "mvtnorm" ], "Suggests": [ "cluster", "parallel", "GenomicFeatures", "dynamicTreeCut", "Rsamtools", "TxDb.Hsapiens.UCSC.hg19.knownGene" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "2b3735da7e23e679324e43fc0612a136", "NeedsCompilation": "yes", "Title": "Copy Number study and Segmentation for multivariate biological data", "Description": "In this package, a Hidden Semi Markov Model (HSMM) and one homogeneous segmentation model are designed and implemented for segmentation genomic data, with the aim of assisting in transcripts detection using high throughput technology like RNA-seq or tiling array, and copy number analysis using aCGH or sequencing.", "biocViews": [ "CopyNumberVariation", "Genetics", "Microarray", "Sequencing", "Software", "Visualization", "aCGH" ], "Author": "Yang Du", "Maintainer": "Yang Du ", "source.ver": "src/contrib/biomvRCNS_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/biomvRCNS_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/biomvRCNS_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/biomvRCNS_1.14.0.tgz", "vignettes": [ "vignettes/biomvRCNS/inst/doc/biomvRCNS.pdf" ], "vignetteTitles": [ "biomvRCNS package introduction" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/biomvRCNS/inst/doc/biomvRCNS.R" ] }, "BioNet": { "Package": "BioNet", "Version": "1.34.0", "Depends": [ "R (>= 2.10.0)", "graph", "RBGL" ], "Imports": [ "igraph (>= 1.0.1)", "AnnotationDbi", "Biobase" ], "Suggests": [ "rgl", "impute", "DLBCL", "genefilter", "xtable", "ALL", "limma", "hgu95av2.db", "XML" ], "License": "GPL (>= 2)", "MD5sum": "496cab983cb666713a0fadd273b18716", "NeedsCompilation": "no", "Title": "Routines for the functional analysis of biological networks", "Description": "This package provides functions for the integrated analysis of protein-protein interaction networks and the detection of functional modules. Different datasets can be integrated into the network by assigning p-values of statistical tests to the nodes of the network. E.g. p-values obtained from the differential expression of the genes from an Affymetrix array are assigned to the nodes of the network. By fitting a beta-uniform mixture model and calculating scores from the p-values, overall scores of network regions can be calculated and an integer linear programming algorithm identifies the maximum scoring subnetwork.", "biocViews": [ "DataImport", "DifferentialExpression", "GeneExpression", "GraphAndNetwork", "Microarray", "Network", "NetworkEnrichment", "Software" ], "Author": "Marcus Dittrich and Daniela Beisser", "Maintainer": "Marcus Dittrich ", "URL": "http://bionet.bioapps.biozentrum.uni-wuerzburg.de/", "source.ver": "src/contrib/BioNet_1.34.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BioNet_1.34.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BioNet_1.34.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BioNet_1.34.0.tgz", "vignettes": [ "vignettes/BioNet/inst/doc/Tutorial.pdf" ], "vignetteTitles": [ "BioNet Tutorial" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/BioNet/inst/doc/Tutorial.R" ], "importsMe": [ "HTSanalyzeR", "SMITE" ], "suggestsMe": [ "SANTA" ] }, "BioQC": { "Package": "BioQC", "Version": "1.2.0", "Depends": [ "Rcpp", "Biobase" ], "Suggests": [ "testthat" ], "License": "LGPL (>=2)", "Archs": "i386, x64", "MD5sum": "744a89ffea606a4d885885ebb4f9461c", "NeedsCompilation": "yes", "Title": "Detect tissue heterogeneity in expression profiles with gene sets", "Description": "BioQC performs quality control of high-throughput expression data based on tissue gene signatures", "biocViews": [ "GeneExpression", "QualityControl", "Software", "StatisticalMethod" ], "Author": "Jitao David Zhang , with inputs from Laura Badi", "Maintainer": "Jitao David Zhang ", "source.ver": "src/contrib/BioQC_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BioQC_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BioQC_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BioQC_1.2.0.tgz", "vignettes": [ "vignettes/BioQC/inst/doc/bioqc.pdf" ], "vignetteTitles": [ "BioQC: The kidney expression example" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/BioQC/inst/doc/bioqc.R" ] }, "BioSeqClass": { "Package": "BioSeqClass", "Version": "1.32.0", "Depends": [ "R (>= 2.10)", "scatterplot3d" ], "Imports": [ "Biostrings", "ipred", "e1071", "klaR", "randomForest", "class", "tree", "nnet", "rpart", "party", "foreign", "Biobase", "utils", "stats", "grDevices" ], "Suggests": [ "scatterplot3d" ], "License": "LGPL (>= 2.0)", "MD5sum": "0d0fe76b8d487dfd09c3b5c2299f61bb", "NeedsCompilation": "no", "Title": "Classification for Biological Sequences", "Description": "Extracting Features from Biological Sequences and Building Classification Model", "biocViews": [ "Classification", "Software" ], "Author": "Li Hong sysptm@gmail.com", "Maintainer": "Li Hong ", "source.ver": "src/contrib/BioSeqClass_1.32.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BioSeqClass_1.32.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BioSeqClass_1.32.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BioSeqClass_1.32.0.tgz", "vignettes": [ "vignettes/BioSeqClass/inst/doc/BioSeqClass.pdf" ], "vignetteTitles": [ "Using the BioSeqClass Package" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/BioSeqClass/inst/doc/BioSeqClass.R" ] }, "biosigner": { "Package": "biosigner", "Version": "1.2.4", "Imports": [ "methods", "e1071", "randomForest", "ropls", "Biobase" ], "Suggests": [ "BioMark", "RUnit", "BiocGenerics", "BiocStyle", "golubEsets", "hu6800.db", "knitr", "rmarkdown" ], "License": "CeCILL", "MD5sum": "243a987abbd4141baf960e82deb3a1b1", "NeedsCompilation": "no", "Title": "Signature discovery from omics data", "Description": "Feature selection is critical in omics data analysis to extract restricted and meaningful molecular signatures from complex and high-dimension data, and to build robust classifiers. This package implements a new method to assess the relevance of the variables for the prediction performances of the classifier. The approach can be run in parallel with the PLS-DA, Random Forest, and SVM binary classifiers. The signatures and the corresponding 'restricted' models are returned, enabling future predictions on new datasets. A Galaxy implementation of the package is available within the Workflow4metabolomics.org online infrastructure for computational metabolomics.", "biocViews": [ "Classification", "FeatureExtraction", "Lipidomics", "Metabolomics", "Proteomics", "Software", "Transcriptomics" ], "Author": "Philippe Rinaudo , Etienne Thevenot ", "Maintainer": "Philippe Rinaudo , Etienne Thevenot ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/biosigner_1.2.4.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/biosigner_1.2.4.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/biosigner_1.2.4.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/biosigner_1.2.4.tgz", "vignettes": [ "vignettes/biosigner/inst/doc/biosigner-vignette.pdf" ], "vignetteTitles": [ "Vignette Title" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/biosigner/inst/doc/biosigner-vignette.R" ] }, "Biostrings": { "Package": "Biostrings", "Version": "2.42.1", "Depends": [ "R (>= 2.8.0)", "methods", "BiocGenerics (>= 0.15.6)", "S4Vectors (>= 0.11.1)", "IRanges (>= 2.5.27)", "XVector (>= 0.11.6)" ], "Imports": [ "graphics", "methods", "stats", "utils", "BiocGenerics", "IRanges", "XVector" ], "LinkingTo": [ "S4Vectors", "IRanges", "XVector" ], "Suggests": [ "BSgenome (>= 1.13.14)", "BSgenome.Celegans.UCSC.ce2 (>= 1.3.11)", "BSgenome.Dmelanogaster.UCSC.dm3 (>= 1.3.11)", "BSgenome.Hsapiens.UCSC.hg18", "drosophila2probe", "hgu95av2probe", "hgu133aprobe", "GenomicFeatures (>= 1.3.14)", "hgu95av2cdf", "affy (>= 1.41.3)", "affydata (>= 1.11.5)", "RUnit" ], "Enhances": [ "Rmpi" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "f26d6153248ece91637251dd5a7a1da1", "NeedsCompilation": "yes", "Title": "String objects representing biological sequences, and matching algorithms", "Description": "Memory efficient string containers, string matching algorithms, and other utilities, for fast manipulation of large biological sequences or sets of sequences.", "biocViews": [ "Alignment", "DataImport", "DataRepresentation", "Genetics", "Infrastructure", "SequenceMatching", "Sequencing", "Software" ], "Author": "H. Pagès, P. Aboyoun, R. Gentleman, and S. DebRoy", "Maintainer": "H. Pagès ", "source.ver": "src/contrib/Biostrings_2.42.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Biostrings_2.42.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Biostrings_2.42.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Biostrings_2.42.1.tgz", "vignettes": [ "vignettes/Biostrings/inst/doc/Biostrings2Classes.pdf", "vignettes/Biostrings/inst/doc/BiostringsQuickOverview.pdf", "vignettes/Biostrings/inst/doc/matchprobes.pdf", "vignettes/Biostrings/inst/doc/MultipleAlignments.pdf", "vignettes/Biostrings/inst/doc/PairwiseAlignments.pdf" ], "vignetteTitles": [ "A short presentation of the basic classes defined in Biostrings 2", "Biostrings Quick Overview", "Handling probe sequence information", "Multiple Alignments", "Pairwise Sequence Alignments" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Biostrings/inst/doc/Biostrings2Classes.R", "vignettes/Biostrings/inst/doc/matchprobes.R", "vignettes/Biostrings/inst/doc/MultipleAlignments.R", "vignettes/Biostrings/inst/doc/PairwiseAlignments.R" ], "dependsOnMe": [ "altcdfenvs", "Basic4Cseq", "BRAIN", "BSgenome", "ChIPpeakAnno", "ChIPsim", "cleaver", "CODEX", "CRISPRseek", "DECIPHER", "deepSNV", "FDb.FANTOM4.promoters.hg19", "GeneRegionScan", "GenomicAlignments", "genphen", "GOTHiC", "harbChIP", "HelloRanges", "hiReadsProcessor", "iPAC", "JASPAR2014", "kebabs", "MethTargetedNGS", "methVisual", "minfi", "MotifDb", "motifRG", "motifStack", "msa", "muscle", "oligo", "oneChannelGUI", "pcaGoPromoter", "pd.ag", "pd.aragene.1.0.st", "pd.aragene.1.1.st", "pd.ath1.121501", "pd.barley1", "pd.bovgene.1.0.st", "pd.bovgene.1.1.st", "pd.bovine", "pd.bsubtilis", "pd.cangene.1.0.st", "pd.cangene.1.1.st", "pd.canine", "pd.canine.2", "pd.celegans", "pd.chicken", "pd.chigene.1.0.st", "pd.chigene.1.1.st", "pd.chogene.2.0.st", "pd.chogene.2.1.st", "pd.citrus", "pd.clariom.d.human", "pd.clariom.s.human", "pd.clariom.s.human.ht", "pd.clariom.s.mouse", "pd.clariom.s.mouse.ht", "pd.clariom.s.rat", "pd.clariom.s.rat.ht", "pd.cotton", "pd.cyngene.1.0.st", "pd.cyngene.1.1.st", "pd.cyrgene.1.0.st", "pd.cyrgene.1.1.st", "pd.cytogenetics.array", "pd.drogene.1.0.st", "pd.drogene.1.1.st", "pd.drosgenome1", "pd.drosophila.2", "pd.e.coli.2", "pd.ecoli", "pd.ecoli.asv2", "pd.elegene.1.0.st", "pd.elegene.1.1.st", "pd.equgene.1.0.st", "pd.equgene.1.1.st", "pd.felgene.1.0.st", "pd.felgene.1.1.st", "pd.fingene.1.0.st", "pd.fingene.1.1.st", "pd.genomewidesnp.5", "pd.genomewidesnp.6", "pd.guigene.1.0.st", "pd.guigene.1.1.st", "pd.hc.g110", "pd.hg.focus", "pd.hg.u133.plus.2", "pd.hg.u133a", "pd.hg.u133a.2", "pd.hg.u133a.tag", "pd.hg.u133b", "pd.hg.u219", "pd.hg.u95a", "pd.hg.u95av2", "pd.hg.u95b", "pd.hg.u95c", "pd.hg.u95d", "pd.hg.u95e", "pd.hg18.60mer.expr", "pd.ht.hg.u133.plus.pm", "pd.ht.hg.u133a", "pd.ht.mg.430a", "pd.hta.2.0", "pd.hu6800", "pd.huex.1.0.st.v2", "pd.hugene.1.0.st.v1", "pd.hugene.1.1.st.v1", "pd.hugene.2.0.st", "pd.hugene.2.1.st", "pd.maize", "pd.mapping250k.nsp", "pd.mapping250k.sty", "pd.mapping50k.hind240", "pd.mapping50k.xba240", "pd.margene.1.0.st", "pd.margene.1.1.st", "pd.medgene.1.0.st", "pd.medgene.1.1.st", "pd.medicago", "pd.mg.u74a", "pd.mg.u74av2", "pd.mg.u74b", "pd.mg.u74bv2", "pd.mg.u74c", "pd.mg.u74cv2", "pd.mirna.1.0", "pd.mirna.2.0", "pd.mirna.3.0", "pd.mirna.4.0", "pd.moe430a", "pd.moe430b", "pd.moex.1.0.st.v1", "pd.mogene.1.0.st.v1", "pd.mogene.1.1.st.v1", "pd.mogene.2.0.st", "pd.mogene.2.1.st", "pd.mouse430.2", "pd.mouse430a.2", "pd.mta.1.0", "pd.mu11ksuba", "pd.mu11ksubb", "pd.nugo.hs1a520180", "pd.nugo.mm1a520177", "pd.ovigene.1.0.st", "pd.ovigene.1.1.st", "pd.pae.g1a", "pd.plasmodium.anopheles", "pd.poplar", "pd.porcine", "pd.porgene.1.0.st", "pd.porgene.1.1.st", "pd.rabgene.1.0.st", "pd.rabgene.1.1.st", "pd.rae230a", "pd.rae230b", "pd.raex.1.0.st.v1", "pd.ragene.1.0.st.v1", "pd.ragene.1.1.st.v1", "pd.ragene.2.0.st", "pd.ragene.2.1.st", "pd.rat230.2", "pd.rcngene.1.0.st", "pd.rcngene.1.1.st", "pd.rg.u34a", "pd.rg.u34b", "pd.rg.u34c", "pd.rhegene.1.0.st", "pd.rhegene.1.1.st", "pd.rhesus", "pd.rice", "pd.rjpgene.1.0.st", "pd.rjpgene.1.1.st", "pd.rn.u34", "pd.rta.1.0", "pd.rusgene.1.0.st", "pd.rusgene.1.1.st", "pd.s.aureus", "pd.soybean", "pd.soygene.1.0.st", "pd.soygene.1.1.st", "pd.sugar.cane", "pd.tomato", "pd.u133.x3p", "pd.vitis.vinifera", "pd.wheat", "pd.x.laevis.2", "pd.x.tropicalis", "pd.xenopus.laevis", "pd.yeast.2", "pd.yg.s98", "pd.zebgene.1.0.st", "pd.zebgene.1.1.st", "pd.zebrafish", "PGA", "pqsfinder", "PWMEnrich", "qrqc", "R453Plus1Toolbox", "R4RNA", "REDseq", "rGADEM", "RiboProfiling", "Roleswitch", "rRDP", "Rsamtools", "RSVSim", "sangerseqR", "SCAN.UPC", "scsR", "SELEX", "seqbias", "ShortRead", "SICtools", "spliceSites", "ssviz", "systemPipeR", "triplex", "waveTiling" ], "importsMe": [ "AffyCompatible", "AllelicImbalance", "alpine", "AneuFinder", "AnnotationHubData", "ArrayExpressHTS", "BBCAnalyzer", "BCRANK", "BEAT", "BioSeqClass", "biovizBase", "BSgenome", "charm", "ChIPseqR", "ChIPsim", "CNEr", "cobindR", "compEpiTools", "CrispRVariants", "customProDB", "dada2", "dagLogo", "diffHic", "DNAshapeR", "easyRNASeq", "EDASeq", "ensemblVEP", "eudysbiome", "FDb.InfiniumMethylation.hg18", "FDb.InfiniumMethylation.hg19", "FindMyFriends", "FourCSeq", "gcrma", "genbankr", "GeneRegionScan", "GenoGAM", "genomation", "GenomicAlignments", "GenomicFeatures", "GenVisR", "ggbio", "GGtools", "girafe", "gmapR", "GoogleGenomics", "GUIDEseq", "Gviz", "gwascat", "h5vc", "HiTC", "HTSeqGenie", "IONiseR", "KEGGREST", "LowMACA", "MADSEQ", "MafDb.ESP6500SI.V2.SSA137", "maftools", "MatrixRider", "MEDIPS", "MEDME", "metagenomeFeatures", "methVisual", "methylPipe", "microRNA", "MMDiff2", "motifbreakR", "motifRG", "MotIV", "MutationalPatterns", "oligoClasses", "OTUbase", "Pbase", "pd.081229.hg18.promoter.medip.hx1", "pd.2006.07.18.hg18.refseq.promoter", "pd.2006.07.18.mm8.refseq.promoter", "pd.2006.10.31.rn34.refseq.promoter", "pd.atdschip.tiling", "pd.charm.hg18.example", "pd.feinberg.hg18.me.hx1", "pd.feinberg.mm8.me.hx1", "pd.mirna.3.1", "pdInfoBuilder", "phyloseq", "podkat", "polyester", "proBAMr", "procoil", "ProteomicsAnnotationHubData", "PureCN", "Pviz", "qrqc", "qsea", "QuasR", "r3Cseq", "RCAS", "Rcpi", "REDseq", "Repitools", "rGADEM", "RNAprobR", "Rqc", "rSFFreader", "rtracklayer", "SeqArray", "seqPattern", "seqplots", "SGSeq", "signeR", "SNPhood", "soGGi", "SomaticSignatures", "SPLINTER", "sscu", "synapter", "TarSeqQC", "TFBSTools", "TVTB", "VariantAnnotation", "VariantFiltering", "VariantTools", "wavClusteR" ], "suggestsMe": [ "annotate", "AnnotationForge", "AnnotationHub", "BeadArrayUseCases", "CINdex", "CSAR", "exomeCopy", "GenomicFiles", "GenomicRanges", "genoset", "ggtree", "methylumi", "microRNA", "MiRaGE", "rpx", "rTRM", "SNPlocs.Hsapiens.dbSNP.20090506", "SNPlocs.Hsapiens.dbSNP.20100427", "SNPlocs.Hsapiens.dbSNP.20101109", "SNPlocs.Hsapiens.dbSNP.20110815", "SNPlocs.Hsapiens.dbSNP.20111119", "SNPlocs.Hsapiens.dbSNP.20120608", "SNPlocs.Hsapiens.dbSNP141.GRCh38", "SNPlocs.Hsapiens.dbSNP142.GRCh37", "SNPlocs.Hsapiens.dbSNP144.GRCh37", "SNPlocs.Hsapiens.dbSNP144.GRCh38", "XtraSNPlocs.Hsapiens.dbSNP144.GRCh37", "XtraSNPlocs.Hsapiens.dbSNP144.GRCh38", "XVector" ] }, "biosvd": { "Package": "biosvd", "Version": "2.10.0", "Depends": [ "R (>= 3.1.0)" ], "Imports": [ "BiocGenerics", "Biobase", "methods", "grid", "graphics", "NMF" ], "License": "Artistic-2.0", "MD5sum": "4ec9f72f211302ad494ece9cddbef887", "NeedsCompilation": "no", "Title": "Package for high-throughput data processing, outlier detection, noise removal and dynamic modeling", "Description": "The biosvd package contains functions to reduce the input data set from the feature x assay space to the reduced diagonalized eigenfeature x eigenassay space, with the eigenfeatures and eigenassays unique orthonormal superpositions of the features and assays, respectively. Results of SVD applied to the data can subsequently be inspected based on generated graphs, such as a heatmap of the eigenfeature x assay matrix and a bar plot with the eigenexpression fractions of all eigenfeatures. These graphs aid in deciding which eigenfeatures and eigenassays to filter out (i.e., eigenfeatures representing steady state, noise, or experimental artifacts; or when applied to the variance in the data, eigenfeatures representing steady-scale variance). After possible removal of steady state expression, steady-scale variance, noise and experimental artifacts, and after re-applying SVD to the normalized data, a summary html report of the eigensystem is generated, containing among others polar plots of the assays and features, a table with the list of features sortable according to their coordinates, radius and phase in the polar plot, and a visualization of the data sorted according to the two selected eigenfeatures and eigenassays with colored feature/assay annotation information when provided. This gives a global picture of the dynamics of expression/intensity levels, in which individual features and assays are classified in groups of similar regulation and function or similar cellular state and biological phenotype.", "biocViews": [ "Software", "TimeCourse", "Visualization" ], "Author": "Anneleen Daemen , Matthew Brauer ", "Maintainer": "Anneleen Daemen , Matthew Brauer ", "source.ver": "src/contrib/biosvd_2.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/biosvd_2.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/biosvd_2.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/biosvd_2.10.0.tgz", "vignettes": [ "vignettes/biosvd/inst/doc/biosvd.pdf" ], "vignetteTitles": [ "biosvd" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/biosvd/inst/doc/biosvd.R" ] }, "biovizBase": { "Package": "biovizBase", "Version": "1.22.0", "Depends": [ "R (>= 2.10)", "methods" ], "Imports": [ "grDevices", "stats", "scales", "Hmisc", "RColorBrewer", "dichromat", "BiocGenerics", "S4Vectors (>= 0.9.25)", "IRanges (>= 1.99.28)", "GenomeInfoDb (>= 1.5.14)", "GenomicRanges (>= 1.23.21)", "SummarizedExperiment", "Biostrings (>= 2.33.11)", "Rsamtools (>= 1.17.28)", "GenomicAlignments (>= 1.1.16)", "GenomicFeatures (>= 1.21.19)", "AnnotationDbi", "VariantAnnotation (>= 1.11.4)", "ensembldb (>= 1.3.8)" ], "Suggests": [ "BSgenome.Hsapiens.UCSC.hg19", "TxDb.Hsapiens.UCSC.hg19.knownGene", "BSgenome", "rtracklayer", "EnsDb.Hsapiens.v75", "RUnit" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "875dbe862dce07f529ac6d38b404a67b", "NeedsCompilation": "yes", "Title": "Basic graphic utilities for visualization of genomic data.", "Description": "The biovizBase package is designed to provide a set of utilities, color schemes and conventions for genomic data. It serves as the base for various high-level packages for biological data visualization. This saves development effort and encourages consistency.", "biocViews": [ "Infrastructure", "Preprocessing", "Software", "Visualization" ], "Author": "Tengfei Yin [aut], Michael Lawrence [aut, ths, cre], Dianne Cook [aut, ths], Johannes Rainer [ctb]", "Maintainer": "Michael Lawrence ", "source.ver": "src/contrib/biovizBase_1.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/biovizBase_1.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/biovizBase_1.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/biovizBase_1.22.0.tgz", "vignettes": [ "vignettes/biovizBase/inst/doc/intro.pdf" ], "vignetteTitles": [ "An Introduction to biovizBase" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/biovizBase/inst/doc/intro.R" ], "dependsOnMe": [ "CAFE", "qrqc" ], "importsMe": [ "BubbleTree", "ggbio", "Gviz", "Pviz", "qrqc", "Rqc" ], "suggestsMe": [ "CINdex", "derfinder", "derfinderPlot", "R3CPET", "regionReport" ] }, "BiRewire": { "Package": "BiRewire", "Version": "3.6.0", "Depends": [ "igraph", "slam", "tsne", "Matrix" ], "Suggests": [ "RUnit", "BiocGenerics" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "522862204f5fa13043de906fa165adb2", "NeedsCompilation": "yes", "Title": "High-performing routines for the randomization of a bipartite graph (or a binary event matrix), undirected and directed signed graph preserving degree distribution (or marginal totals)", "Description": "Fast functions for bipartite network rewiring through N consecutive switching steps (See References) and for the computation of the minimal number of switching steps to be performed in order to maximise the dissimilarity with respect to the original network. Includes functions for the analysis of the introduced randomness across the switching steps and several other routines to analyse the resulting networks and their natural projections. Extension to undirected networks and directed signed networks is also provided. Starting from version 1.9.7 a more precise bound (especially for small network) has been implemented. Starting from version 2.2.0 the analysis routine is more complete and a visual montioring of the underlying Markov Chain has been implemented. Starting from 3.6.0 the library can handle also matrices with NA (not for the directed signed graphs).", "biocViews": [ "Network", "Software" ], "Author": "Andrea Gobbi [aut], Francesco Iorio [aut], Giuseppe Jurman [cbt], Davide Albanese [cbt], Julio Saez-Rodriguez [cbt].", "Maintainer": "Andrea Gobbi ", "URL": "http://www.ebi.ac.uk/~iorio/BiRewire", "source.ver": "src/contrib/BiRewire_3.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BiRewire_3.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BiRewire_3.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BiRewire_3.6.0.tgz", "vignettes": [ "vignettes/BiRewire/inst/doc/BiRewire.pdf" ], "vignetteTitles": [ "BiRewire" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/BiRewire/inst/doc/BiRewire.R" ] }, "birta": { "Package": "birta", "Version": "1.18.0", "Depends": [ "limma", "MASS", "R(>= 2.10)", "Biobase", "methods" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "1a6fb7e278a5b40ecc8fe4bd48d86bc3", "NeedsCompilation": "yes", "Title": "Bayesian Inference of Regulation of Transcriptional Activity", "Description": "Expression levels of mRNA molecules are regulated by different processes, comprising inhibition or activation by transcription factors and post-transcriptional degradation by microRNAs. birta (Bayesian Inference of Regulation of Transcriptional Activity) uses the regulatory networks of TFs and miRNAs together with mRNA and miRNA expression data to predict switches in regulatory activity between two conditions. A Bayesian network is used to model the regulatory structure and Markov-Chain-Monte-Carlo is applied to sample the activity states.", "biocViews": [ "GeneExpression", "GraphAndNetwork", "Microarray", "Sequencing", "Software", "Transcription" ], "Author": "Benedikt Zacher, Khalid Abnaof, Stephan Gade, Erfan Younesi, Achim Tresch, Holger Froehlich", "Maintainer": "Benedikt Zacher , Holger Froehlich ", "source.ver": "src/contrib/birta_1.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/birta_1.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/birta_1.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/birta_1.18.0.tgz", "vignettes": [ "vignettes/birta/inst/doc/birta.pdf" ], "vignetteTitles": [ "Bayesian Inference of Regulation of Transcriptional Activity" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/birta/inst/doc/birta.R" ] }, "birte": { "Package": "birte", "Version": "1.10.0", "Depends": [ "R(>= 3.0.0)", "RcppArmadillo (>= 0.3.6.1)", "Rcpp" ], "Imports": [ "MASS", "limma(>= 3.22.0)", "glmnet", "Biobase", "nem", "graphics", "stats", "utils" ], "LinkingTo": [ "RcppArmadillo", "Rcpp" ], "Suggests": [ "knitr" ], "Enhances": [ "Rgraphviz" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "f73fdcb9eebc701bddec8d74a3ce4ff1", "NeedsCompilation": "yes", "Title": "Bayesian Inference of Regulatory Influence on Expression (biRte)", "Description": "Expression levels of mRNA molecules are regulated by different processes, comprising inhibition or activation by transcription factors and post-transcriptional degradation by microRNAs. biRte uses regulatory networks of TFs, miRNAs and possibly other factors, together with mRNA, miRNA and other available expression data to predict the relative influence of a regulator on the expression of its target genes. Inference is done in a Bayesian modeling framework using Markov-Chain-Monte-Carlo. A special feature is the possibility for follow-up network reverse engineering between active regulators.", "biocViews": [ "Bayesian", "GeneExpression", "Microarray", "Network", "NetworkInference", "Regression", "Sequencing", "Software", "Transcription" ], "Author": "Holger Froehlich, contributions by Benedikt Zacher", "Maintainer": "Holger Froehlich ", "SystemRequirements": "BLAS, LAPACK", "VignetteBuilder": "knitr", "source.ver": "src/contrib/birte_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/birte_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/birte_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/birte_1.10.0.tgz", "vignettes": [ "vignettes/birte/inst/doc/birte.pdf" ], "vignetteTitles": [ "Bayesian Inference of Regulation of Transcriptional Activity" ], "hasREADME": true, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/birte/inst/doc/birte.R" ] }, "BiSeq": { "Package": "BiSeq", "Version": "1.14.0", "Depends": [ "R (>= 2.15.2)", "methods", "S4Vectors", "IRanges (>= 1.17.24)", "GenomicRanges", "SummarizedExperiment (>= 0.2.0)", "Formula" ], "Imports": [ "methods", "BiocGenerics", "Biobase", "S4Vectors", "IRanges", "GenomeInfoDb", "GenomicRanges", "SummarizedExperiment", "rtracklayer", "parallel", "betareg", "lokern", "Formula", "globaltest" ], "License": "LGPL-3", "MD5sum": "984d33fefaf5a5f9ceba50c31dc05b11", "NeedsCompilation": "no", "Title": "Processing and analyzing bisulfite sequencing data", "Description": "The BiSeq package provides useful classes and functions to handle and analyze targeted bisulfite sequencing (BS) data such as reduced-representation bisulfite sequencing (RRBS) data. In particular, it implements an algorithm to detect differentially methylated regions (DMRs). The package takes already aligned BS data from one or multiple samples.", "biocViews": [ "DNAMethylation", "Genetics", "MethylSeq", "Sequencing", "Software" ], "Author": "Katja Hebestreit, Hans-Ulrich Klein", "Maintainer": "Katja Hebestreit ", "source.ver": "src/contrib/BiSeq_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BiSeq_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BiSeq_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BiSeq_1.14.0.tgz", "vignettes": [ "vignettes/BiSeq/inst/doc/BiSeq.pdf" ], "vignetteTitles": [ "An Introduction to BiSeq" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/BiSeq/inst/doc/BiSeq.R" ], "importsMe": [ "M3D" ], "dependsOnMe": [ "RRBSdata" ] }, "BitSeq": { "Package": "BitSeq", "Version": "1.18.0", "Depends": [ "Rsamtools", "zlibbioc" ], "Imports": [ "S4Vectors", "IRanges" ], "LinkingTo": [ "Rsamtools (>= 1.19.38)", "zlibbioc" ], "Suggests": [ "edgeR", "DESeq", "BiocStyle" ], "License": "Artistic-2.0 + file LICENSE", "Archs": "i386, x64", "MD5sum": "dce0c422d52acc8d223f3e2e9a65e3bc", "NeedsCompilation": "yes", "Title": "Transcript expression inference and differential expression analysis for RNA-seq data", "Description": "The BitSeq package is targeted for transcript expression analysis and differential expression analysis of RNA-seq data in two stage process. In the first stage it uses Bayesian inference methodology to infer expression of individual transcripts from individual RNA-seq experiments. The second stage of BitSeq embraces the differential expression analysis of transcript expression. Providing expression estimates from replicates of multiple conditions, Log-Normal model of the estimates is used for inferring the condition mean transcript expression and ranking the transcripts based on the likelihood of differential expression.", "biocViews": [ "AlternativeSplicing", "Bayesian", "DifferentialExpression", "DifferentialSplicing", "GeneExpression", "RNASeq", "Sequencing", "Software", "Transcription" ], "Author": "Peter Glaus, Antti Honkela and Magnus Rattray", "Maintainer": "Antti Honkela , Panagiotis Papastamoulis ", "source.ver": "src/contrib/BitSeq_1.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BitSeq_1.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BitSeq_1.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BitSeq_1.18.0.tgz", "vignettes": [ "vignettes/BitSeq/inst/doc/BitSeq.pdf" ], "vignetteTitles": [ "BitSeq User Guide" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/BitSeq/inst/doc/BitSeq.R" ] }, "blima": { "Package": "blima", "Version": "1.8.0", "Depends": [ "R(>= 3.0.0)" ], "Imports": [ "beadarray(>= 2.0.0)", "Biobase(>= 2.0.0)", "BiocGenerics", "grDevices", "stats", "graphics" ], "Suggests": [ "xtable", "blimaTestingData", "BiocStyle", "illuminaHumanv4.db", "lumi" ], "License": "GPL-3", "MD5sum": "4ce94a0cfdbe1ab393f8dc26fec2fc6d", "NeedsCompilation": "no", "Title": "Package for the preprocessing and analysis of the Illumina microarrays on the detector (bead) level.", "Description": "Package blima includes several algorithms for the preprocessing of Illumina microarray data. It focuses to the bead level analysis and provides novel approach to the quantile normalization of the vectors of unequal lengths. It provides variety of the methods for background correction including background subtraction, RMA like convolution and background outlier removal. It also implements variance stabilizing transformation on the bead level. There are also implemented methods for data summarization. It also provides the methods for performing T-tests on the detector (bead) level and on the probe level for differential expression testing.", "biocViews": [ "Microarray", "Normalization", "Preprocessing", "Software" ], "Author": "Vojtech Kulvait", "Maintainer": "Vojtech Kulvait ", "URL": "https://bitbucket.org/kulvait/blima", "source.ver": "src/contrib/blima_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/blima_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/blima_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/blima_1.8.0.tgz", "vignettes": [ "vignettes/blima/inst/doc/blima.pdf" ], "vignetteTitles": [ "blima.pdf" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/blima/inst/doc/blima.R" ], "suggestsMe": [ "blimaTestingData" ] }, "BPRMeth": { "Package": "BPRMeth", "Version": "1.0.0", "Depends": [ "R (>= 3.3.0)", "GenomicRanges" ], "Imports": [ "assertthat", "methods", "MASS", "doParallel", "parallel", "e1071", "earth", "foreach", "randomForest", "stats", "IRanges", "S4Vectors", "data.table", "graphics" ], "Suggests": [ "testthat", "knitr", "rmarkdown", "BiocStyle" ], "License": "GPL-3", "MD5sum": "cb3a0f973c01ebd83416a0af5c0a015d", "NeedsCompilation": "no", "Title": "Model higher-order methylation profiles", "Description": "BPRMeth package uses the Binomial Probit Regression likelihood to model methylation profiles and extract higher order features. These features quantitate precisely notions of shape of a methylation profile. Using these higher order features across promoter-proximal regions, we construct a powerful predictor of gene expression. Also, these features are used to cluster proximal-promoter regions using the EM algorithm.", "biocViews": [ "Bayesian", "Clustering", "Coverage", "DNAMethylation", "Epigenetics", "FeatureExtraction", "GeneExpression", "GeneRegulation", "Genetics", "KEGG", "RNASeq", "Regression", "Sequencing", "Software" ], "Author": "Chantriolnt-Andreas Kapourani [aut, cre]", "Maintainer": "Chantriolnt-Andreas Kapourani ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/BPRMeth_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BPRMeth_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BPRMeth_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BPRMeth_1.0.0.tgz", "vignettes": [ "vignettes/BPRMeth/inst/doc/BPRMeth_vignette.pdf" ], "vignetteTitles": [ "An Introduction to the BPR method" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/BPRMeth/inst/doc/BPRMeth_vignette.R" ] }, "BRAIN": { "Package": "BRAIN", "Version": "1.20.0", "Depends": [ "R (>= 2.8.1)", "PolynomF", "Biostrings", "lattice" ], "License": "GPL-2", "MD5sum": "1d682d252effda8da5e6c99491ed103c", "NeedsCompilation": "no", "Title": "Baffling Recursive Algorithm for Isotope distributioN calculations", "Description": "Package for calculating aggregated isotopic distribution and exact center-masses for chemical substances (in this version composed of C, H, N, O and S). This is an implementation of the BRAIN algorithm described in the paper by J. Claesen, P. Dittwald, T. Burzykowski and D. Valkenborg.", "biocViews": [ "MassSpectrometry", "Proteomics", "Software" ], "Author": "Piotr Dittwald, with contributions of Dirk Valkenborg and Jurgen Claesen", "Maintainer": "Piotr Dittwald ", "source.ver": "src/contrib/BRAIN_1.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BRAIN_1.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BRAIN_1.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BRAIN_1.20.0.tgz", "vignettes": [ "vignettes/BRAIN/inst/doc/BRAIN-vignette.pdf" ], "vignetteTitles": [ "BRAIN Usage" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/BRAIN/inst/doc/BRAIN-vignette.R" ], "suggestsMe": [ "cleaver", "RforProteomics" ] }, "BrainStars": { "Package": "BrainStars", "Version": "1.18.0", "Depends": [ "RCurl", "Biobase", "methods" ], "Imports": [ "RJSONIO", "Biobase" ], "License": "Artistic-2.0", "MD5sum": "65bf1f87e989f3e5d46af518648f4f38", "NeedsCompilation": "no", "Title": "query gene expression data and plots from BrainStars (B*)", "Description": "This package can search and get gene expression data and plots from BrainStars (B*). BrainStars is a quantitative expression database of the adult mouse brain. The database has genome-wide expression profile at 51 adult mouse CNS regions.", "biocViews": [ "DataImport", "Microarray", "OneChannel", "Software" ], "Author": "Itoshi NIKAIDO ", "Maintainer": "Itoshi NIKAIDO ", "source.ver": "src/contrib/BrainStars_1.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BrainStars_1.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BrainStars_1.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BrainStars_1.18.0.tgz", "vignettes": [ "vignettes/BrainStars/inst/doc/BrainStars.pdf" ], "vignetteTitles": [ "BrainStars" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/BrainStars/inst/doc/BrainStars.R" ] }, "bridge": { "Package": "bridge", "Version": "1.38.0", "Depends": [ "R (>= 1.9.0)", "rama" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "e62e414d84ea1948d375d7377cc6ce59", "NeedsCompilation": "yes", "Title": "Bayesian Robust Inference for Differential Gene Expression", "Description": "Test for differentially expressed genes with microarray data. This package can be used with both cDNA microarrays or Affymetrix chip. The packge fits a robust Bayesian hierarchical model for testing for differential expression. Outliers are modeled explicitly using a $t$-distribution. The model includes an exchangeable prior for the variances which allow different variances for the genes but still shrink extreme empirical variances. Our model can be used for testing for differentially expressed genes among multiple samples, and can distinguish between the different possible patterns of differential expression when there are three or more samples. Parameter estimation is carried out using a novel version of Markov Chain Monte Carlo that is appropriate when the model puts mass on subspaces of the full parameter space.", "biocViews": [ "DifferentialExpression", "Microarray", "OneChannel", "Software", "TwoChannel" ], "Author": "Raphael Gottardo", "Maintainer": "Raphael Gottardo ", "source.ver": "src/contrib/bridge_1.38.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/bridge_1.38.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/bridge_1.38.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/bridge_1.38.0.tgz", "vignettes": [ "vignettes/bridge/inst/doc/bridge.pdf" ], "vignetteTitles": [ "bridge Tutorial" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/bridge/inst/doc/bridge.R" ] }, "BridgeDbR": { "Package": "BridgeDbR", "Version": "1.8.0", "Depends": [ "R (>= 3.3.0)", "rJava" ], "Imports": [ "RCurl" ], "Suggests": [ "testthat" ], "License": "AGPL-3", "MD5sum": "a72b70f5961994fc82171b9b2bb2c162", "NeedsCompilation": "no", "Title": "Code for using BridgeDb identifier mapping framework from within R", "Description": "Use BridgeDb functions and load identifier mapping databases in R", "biocViews": [ "Annotation", "Software" ], "Author": "Christ Leemans , Egon Willighagen , Anwesha Bohler , Lars Eijssen ", "Maintainer": "Egon Willighagen ", "URL": "https://github.com/bridgedb/BridgeDb, https://github.com/BiGCAT-UM/bridgedb-r", "BugReports": "https://github.com/BiGCAT-UM/bridgedb-r/issues", "source.ver": "src/contrib/BridgeDbR_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BridgeDbR_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BridgeDbR_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BridgeDbR_1.8.0.tgz", "vignettes": [ "vignettes/BridgeDbR/inst/doc/tutorial.pdf" ], "vignetteTitles": [ "tutorial" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/BridgeDbR/inst/doc/tutorial.R" ] }, "BrowserViz": { "Package": "BrowserViz", "Version": "1.6.0", "Depends": [ "R (>= 3.2.1)", "jsonlite (>= 0.9.15)", "httpuv(>= 1.3.2)" ], "Imports": [ "methods", "BiocGenerics" ], "Suggests": [ "RUnit", "BiocStyle" ], "License": "GPL-2", "MD5sum": "f49f37928052af3f4bfe20919241b6e6", "NeedsCompilation": "no", "Title": "BrowserViz: interactive R/browser graphics using websockets and JSON", "Description": "Interactvive graphics in a web browser from R, using websockets and JSON.", "biocViews": [ "Software", "ThirdPartyClient", "Visualization" ], "Author": "Paul Shannon", "Maintainer": "Paul Shannon ", "source.ver": "src/contrib/BrowserViz_1.6.0.tar.gz", "vignettes": [ "vignettes/BrowserViz/inst/doc/BrowserViz.pdf" ], "vignetteTitles": [ "BrowserViz" ], "hasREADME": true, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/BrowserViz/inst/doc/BrowserViz.R" ], "dependsOnMe": [ "BrowserVizDemo", "RCyjs" ] }, "BrowserVizDemo": { "Package": "BrowserVizDemo", "Version": "1.6.0", "Depends": [ "R (>= 3.2.3)", "BrowserViz", "Rcpp (>= 0.11.5)", "jsonlite (>= 0.9.15)", "httpuv(>= 1.3.2)" ], "Imports": [ "methods", "BiocGenerics" ], "Suggests": [ "RUnit", "BiocStyle" ], "License": "GPL-2", "MD5sum": "ad34f1187c303335438431f0f8ef56af", "NeedsCompilation": "no", "Title": "BrowserVizDemo: How to subclass BrowserViz", "Description": "A BrowserViz subclassing example, xy plotting in the browser using d3.", "biocViews": [ "Software", "ThirdPartyClient", "Visualization" ], "Author": "Paul Shannon", "Maintainer": "Paul Shannon ", "source.ver": "src/contrib/BrowserVizDemo_1.6.0.tar.gz", "vignettes": [ "vignettes/BrowserVizDemo/inst/doc/BrowserVizDemo.pdf" ], "vignetteTitles": [ "BrowserVizDemo" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/BrowserVizDemo/inst/doc/BrowserVizDemo.R" ] }, "BSgenome": { "Package": "BSgenome", "Version": "1.42.0", "Depends": [ "R (>= 2.8.0)", "methods", "BiocGenerics (>= 0.13.8)", "S4Vectors (>= 0.9.36)", "IRanges (>= 2.1.33)", "GenomeInfoDb (>= 1.3.19)", "GenomicRanges (>= 1.23.15)", "Biostrings (>= 2.35.3)", "rtracklayer (>= 1.25.8)" ], "Imports": [ "methods", "utils", "stats", "BiocGenerics", "S4Vectors", "IRanges", "XVector", "GenomeInfoDb", "GenomicRanges", "Biostrings", "Rsamtools", "rtracklayer" ], "Suggests": [ "BiocInstaller", "Biobase", "BSgenome.Celegans.UCSC.ce2", "BSgenome.Hsapiens.UCSC.hg38", "BSgenome.Hsapiens.UCSC.hg38.masked", "BSgenome.Mmusculus.UCSC.mm10", "BSgenome.Rnorvegicus.UCSC.rn5", "TxDb.Hsapiens.UCSC.hg38.knownGene", "TxDb.Mmusculus.UCSC.mm10.knownGene", "SNPlocs.Hsapiens.dbSNP141.GRCh38", "XtraSNPlocs.Hsapiens.dbSNP141.GRCh38", "hgu95av2probe", "RUnit" ], "License": "Artistic-2.0", "MD5sum": "ee6db342fe767fc8092ce88c0d5d15cc", "NeedsCompilation": "no", "Title": "Infrastructure for Biostrings-based genome data packages and support for efficient SNP representation", "Description": "Infrastructure shared by all the Biostrings-based genome data packages", "biocViews": [ "Annotation", "DataRepresentation", "Genetics", "Infrastructure", "SNP", "SequenceMatching", "Software" ], "Author": "Hervé Pagès", "Maintainer": "H. Pagès ", "source.ver": "src/contrib/BSgenome_1.42.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BSgenome_1.42.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BSgenome_1.42.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BSgenome_1.42.0.tgz", "vignettes": [ "vignettes/BSgenome/inst/doc/BSgenomeForge.pdf", "vignettes/BSgenome/inst/doc/GenomeSearching.pdf" ], "vignetteTitles": [ "How to forge a BSgenome data package", "Efficient genome searching with Biostrings and the BSgenome data packages" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/BSgenome/inst/doc/BSgenomeForge.R", "vignettes/BSgenome/inst/doc/GenomeSearching.R" ], "dependsOnMe": [ "BSgenome.Alyrata.JGI.v1", "BSgenome.Amellifera.BeeBase.assembly4", "BSgenome.Amellifera.UCSC.apiMel2", "BSgenome.Amellifera.UCSC.apiMel2.masked", "BSgenome.Athaliana.TAIR.04232008", "BSgenome.Athaliana.TAIR.TAIR9", "BSgenome.Btaurus.UCSC.bosTau3", "BSgenome.Btaurus.UCSC.bosTau3.masked", "BSgenome.Btaurus.UCSC.bosTau4", "BSgenome.Btaurus.UCSC.bosTau4.masked", "BSgenome.Btaurus.UCSC.bosTau6", "BSgenome.Btaurus.UCSC.bosTau6.masked", "BSgenome.Btaurus.UCSC.bosTau8", "BSgenome.Celegans.UCSC.ce10", "BSgenome.Celegans.UCSC.ce11", "BSgenome.Celegans.UCSC.ce2", "BSgenome.Celegans.UCSC.ce6", "BSgenome.Cfamiliaris.UCSC.canFam2", "BSgenome.Cfamiliaris.UCSC.canFam2.masked", "BSgenome.Cfamiliaris.UCSC.canFam3", "BSgenome.Cfamiliaris.UCSC.canFam3.masked", "BSgenome.Dmelanogaster.UCSC.dm2", "BSgenome.Dmelanogaster.UCSC.dm2.masked", "BSgenome.Dmelanogaster.UCSC.dm3", "BSgenome.Dmelanogaster.UCSC.dm3.masked", "BSgenome.Dmelanogaster.UCSC.dm6", "BSgenome.Drerio.UCSC.danRer10", "BSgenome.Drerio.UCSC.danRer5", "BSgenome.Drerio.UCSC.danRer5.masked", "BSgenome.Drerio.UCSC.danRer6", "BSgenome.Drerio.UCSC.danRer6.masked", "BSgenome.Drerio.UCSC.danRer7", "BSgenome.Drerio.UCSC.danRer7.masked", "BSgenome.Ecoli.NCBI.20080805", "BSgenome.Gaculeatus.UCSC.gasAcu1", "BSgenome.Gaculeatus.UCSC.gasAcu1.masked", "BSgenome.Ggallus.UCSC.galGal3", "BSgenome.Ggallus.UCSC.galGal3.masked", "BSgenome.Ggallus.UCSC.galGal4", "BSgenome.Ggallus.UCSC.galGal4.masked", "BSgenome.Ggallus.UCSC.galGal5", "BSgenome.Hsapiens.1000genomes.hs37d5", "BSgenome.Hsapiens.NCBI.GRCh38", "BSgenome.Hsapiens.UCSC.hg17", "BSgenome.Hsapiens.UCSC.hg17.masked", "BSgenome.Hsapiens.UCSC.hg18", "BSgenome.Hsapiens.UCSC.hg18.masked", "BSgenome.Hsapiens.UCSC.hg19", "BSgenome.Hsapiens.UCSC.hg19.masked", "BSgenome.Hsapiens.UCSC.hg38", "BSgenome.Hsapiens.UCSC.hg38.masked", "BSgenome.Mfascicularis.NCBI.5.0", "BSgenome.Mfuro.UCSC.musFur1", "BSgenome.Mmulatta.UCSC.rheMac2", "BSgenome.Mmulatta.UCSC.rheMac2.masked", "BSgenome.Mmulatta.UCSC.rheMac3", "BSgenome.Mmulatta.UCSC.rheMac3.masked", "BSgenome.Mmulatta.UCSC.rheMac8", "BSgenome.Mmusculus.UCSC.mm10", "BSgenome.Mmusculus.UCSC.mm10.masked", "BSgenome.Mmusculus.UCSC.mm8", "BSgenome.Mmusculus.UCSC.mm8.masked", "BSgenome.Mmusculus.UCSC.mm9", "BSgenome.Mmusculus.UCSC.mm9.masked", "BSgenome.Osativa.MSU.MSU7", "BSgenome.Ptroglodytes.UCSC.panTro2", "BSgenome.Ptroglodytes.UCSC.panTro2.masked", "BSgenome.Ptroglodytes.UCSC.panTro3", "BSgenome.Ptroglodytes.UCSC.panTro3.masked", "BSgenome.Ptroglodytes.UCSC.panTro5", "BSgenome.Rnorvegicus.UCSC.rn4", "BSgenome.Rnorvegicus.UCSC.rn4.masked", "BSgenome.Rnorvegicus.UCSC.rn5", "BSgenome.Rnorvegicus.UCSC.rn5.masked", "BSgenome.Rnorvegicus.UCSC.rn6", "BSgenome.Scerevisiae.UCSC.sacCer1", "BSgenome.Scerevisiae.UCSC.sacCer2", "BSgenome.Scerevisiae.UCSC.sacCer3", "BSgenome.Sscrofa.UCSC.susScr3", "BSgenome.Sscrofa.UCSC.susScr3.masked", "BSgenome.Tgondii.ToxoDB.7.0", "BSgenome.Tguttata.UCSC.taeGut1", "BSgenome.Tguttata.UCSC.taeGut1.masked", "BSgenome.Tguttata.UCSC.taeGut2", "BSgenome.Vvinifera.URGI.IGGP12Xv0", "BSgenome.Vvinifera.URGI.IGGP12Xv2", "BSgenome.Vvinifera.URGI.IGGP8X", "CAGEr", "cleanUpdTSeq", "GOTHiC", "HelloRanges", "htSeqTools", "leeBamViews", "MEDIPS", "motifRG", "REDseq", "regioneR", "rGADEM", "SNPlocs.Hsapiens.dbSNP.20090506", "SNPlocs.Hsapiens.dbSNP.20120608", "SNPlocs.Hsapiens.dbSNP141.GRCh38", "SNPlocs.Hsapiens.dbSNP142.GRCh37", "SNPlocs.Hsapiens.dbSNP144.GRCh37", "SNPlocs.Hsapiens.dbSNP144.GRCh38", "XtraSNPlocs.Hsapiens.dbSNP141.GRCh38", "XtraSNPlocs.Hsapiens.dbSNP144.GRCh37", "XtraSNPlocs.Hsapiens.dbSNP144.GRCh38" ], "importsMe": [ "AllelicImbalance", "BEAT", "BSgenome.Alyrata.JGI.v1", "BSgenome.Amellifera.BeeBase.assembly4", "BSgenome.Amellifera.UCSC.apiMel2", "BSgenome.Amellifera.UCSC.apiMel2.masked", "BSgenome.Athaliana.TAIR.04232008", "BSgenome.Athaliana.TAIR.TAIR9", "BSgenome.Btaurus.UCSC.bosTau3", "BSgenome.Btaurus.UCSC.bosTau3.masked", "BSgenome.Btaurus.UCSC.bosTau4", "BSgenome.Btaurus.UCSC.bosTau4.masked", "BSgenome.Btaurus.UCSC.bosTau6", "BSgenome.Btaurus.UCSC.bosTau6.masked", "BSgenome.Btaurus.UCSC.bosTau8", "BSgenome.Celegans.UCSC.ce10", "BSgenome.Celegans.UCSC.ce11", "BSgenome.Celegans.UCSC.ce2", "BSgenome.Celegans.UCSC.ce6", "BSgenome.Cfamiliaris.UCSC.canFam2", "BSgenome.Cfamiliaris.UCSC.canFam2.masked", "BSgenome.Cfamiliaris.UCSC.canFam3", "BSgenome.Cfamiliaris.UCSC.canFam3.masked", "BSgenome.Dmelanogaster.UCSC.dm2", "BSgenome.Dmelanogaster.UCSC.dm2.masked", "BSgenome.Dmelanogaster.UCSC.dm3", "BSgenome.Dmelanogaster.UCSC.dm3.masked", "BSgenome.Dmelanogaster.UCSC.dm6", "BSgenome.Drerio.UCSC.danRer10", "BSgenome.Drerio.UCSC.danRer5", "BSgenome.Drerio.UCSC.danRer5.masked", "BSgenome.Drerio.UCSC.danRer6", "BSgenome.Drerio.UCSC.danRer6.masked", "BSgenome.Drerio.UCSC.danRer7", "BSgenome.Drerio.UCSC.danRer7.masked", "BSgenome.Ecoli.NCBI.20080805", "BSgenome.Gaculeatus.UCSC.gasAcu1", "BSgenome.Gaculeatus.UCSC.gasAcu1.masked", "BSgenome.Ggallus.UCSC.galGal3", "BSgenome.Ggallus.UCSC.galGal3.masked", "BSgenome.Ggallus.UCSC.galGal4", "BSgenome.Ggallus.UCSC.galGal4.masked", "BSgenome.Ggallus.UCSC.galGal5", "BSgenome.Hsapiens.NCBI.GRCh38", "BSgenome.Hsapiens.UCSC.hg17", "BSgenome.Hsapiens.UCSC.hg17.masked", "BSgenome.Hsapiens.UCSC.hg18", "BSgenome.Hsapiens.UCSC.hg18.masked", "BSgenome.Hsapiens.UCSC.hg19", "BSgenome.Hsapiens.UCSC.hg19.masked", "BSgenome.Hsapiens.UCSC.hg38", "BSgenome.Hsapiens.UCSC.hg38.masked", "BSgenome.Mfascicularis.NCBI.5.0", "BSgenome.Mfuro.UCSC.musFur1", "BSgenome.Mmulatta.UCSC.rheMac2", "BSgenome.Mmulatta.UCSC.rheMac2.masked", "BSgenome.Mmulatta.UCSC.rheMac3", "BSgenome.Mmulatta.UCSC.rheMac3.masked", "BSgenome.Mmulatta.UCSC.rheMac8", "BSgenome.Mmusculus.UCSC.mm10", "BSgenome.Mmusculus.UCSC.mm10.masked", "BSgenome.Mmusculus.UCSC.mm8", "BSgenome.Mmusculus.UCSC.mm8.masked", "BSgenome.Mmusculus.UCSC.mm9", "BSgenome.Mmusculus.UCSC.mm9.masked", "BSgenome.Osativa.MSU.MSU7", "BSgenome.Ptroglodytes.UCSC.panTro2", "BSgenome.Ptroglodytes.UCSC.panTro2.masked", "BSgenome.Ptroglodytes.UCSC.panTro3", "BSgenome.Ptroglodytes.UCSC.panTro3.masked", "BSgenome.Ptroglodytes.UCSC.panTro5", "BSgenome.Rnorvegicus.UCSC.rn4", "BSgenome.Rnorvegicus.UCSC.rn4.masked", "BSgenome.Rnorvegicus.UCSC.rn5", "BSgenome.Rnorvegicus.UCSC.rn5.masked", "BSgenome.Rnorvegicus.UCSC.rn6", "BSgenome.Scerevisiae.UCSC.sacCer1", "BSgenome.Scerevisiae.UCSC.sacCer2", "BSgenome.Scerevisiae.UCSC.sacCer3", "BSgenome.Sscrofa.UCSC.susScr3", "BSgenome.Sscrofa.UCSC.susScr3.masked", "BSgenome.Tgondii.ToxoDB.7.0", "BSgenome.Tguttata.UCSC.taeGut1", "BSgenome.Tguttata.UCSC.taeGut1.masked", "BSgenome.Tguttata.UCSC.taeGut2", "BSgenome.Vvinifera.URGI.IGGP12Xv0", "BSgenome.Vvinifera.URGI.IGGP12Xv2", "BSgenome.Vvinifera.URGI.IGGP8X", "charm", "ChIPpeakAnno", "cobindR", "CRISPRseek", "crisprseekplus", "diffHic", "fitCons.UCSC.hg19", "genomation", "ggbio", "gmapR", "GreyListChIP", "GUIDEseq", "Gviz", "hiAnnotator", "InPAS", "MADSEQ", "MafDb.1Kgenomes.phase1.hs37d5", "MafDb.1Kgenomes.phase3.hs37d5", "MafDb.ESP6500SI.V2.SSA137.GRCh38", "MafDb.ESP6500SI.V2.SSA137.hs37d5", "MafDb.ExAC.r0.3.1.nonTCGA.snvs.hs37d5", "MafDb.ExAC.r0.3.1.snvs.hs37d5", "MethylSeekR", "MMDiff2", "motifbreakR", "phastCons100way.UCSC.hg19", "phastCons100way.UCSC.hg38", "phastCons7way.UCSC.hg38", "PING", "podkat", "qsea", "QuasR", "R453Plus1Toolbox", "regioneR", "Repitools", "seqplots", "signeR", "SNPlocs.Hsapiens.dbSNP.20090506", "SNPlocs.Hsapiens.dbSNP.20120608", "SNPlocs.Hsapiens.dbSNP141.GRCh38", "SNPlocs.Hsapiens.dbSNP142.GRCh37", "SNPlocs.Hsapiens.dbSNP144.GRCh37", "SNPlocs.Hsapiens.dbSNP144.GRCh38", "TFBSTools", "VariantAnnotation", "VariantFiltering", "VariantTools", "XtraSNPlocs.Hsapiens.dbSNP141.GRCh38", "XtraSNPlocs.Hsapiens.dbSNP144.GRCh37", "XtraSNPlocs.Hsapiens.dbSNP144.GRCh38" ], "suggestsMe": [ "Biostrings", "biovizBase", "chipseq", "easyRNASeq", "GeneRegionScan", "GenomeInfoDb", "GenomicAlignments", "GenomicFeatures", "GenomicRanges", "genoset", "metaseqR", "MiRaGE", "MutationalPatterns", "oneChannelGUI", "QDNAseq", "recoup", "rtracklayer", "SNPlocs.Hsapiens.dbSNP.20100427", "SNPlocs.Hsapiens.dbSNP.20101109", "SNPlocs.Hsapiens.dbSNP.20110815", "SNPlocs.Hsapiens.dbSNP.20111119", "spliceR", "waveTiling" ] }, "bsseq": { "Package": "bsseq", "Version": "1.10.0", "Depends": [ "R (>= 3.3)", "methods", "BiocGenerics", "GenomicRanges (>= 1.23.7)", "SummarizedExperiment (>= 0.1.1)", "parallel", "limma" ], "Imports": [ "IRanges (>= 2.5.17)", "GenomeInfoDb", "scales", "stats", "graphics", "Biobase", "locfit", "gtools", "data.table", "S4Vectors", "R.utils (>= 2.0.0)", "matrixStats (>= 0.50.0)", "permute" ], "Suggests": [ "RUnit", "bsseqData", "BiocStyle", "knitr" ], "License": "Artistic-2.0", "MD5sum": "97479d9c6dffabe933fa057a8cd9c0e7", "NeedsCompilation": "no", "Title": "Analyze, manage and store bisulfite sequencing data", "Description": "A collection of tools for analyzing and visualizing bisulfite sequencing data.", "biocViews": [ "DNAMethylation", "Software" ], "Author": "Kasper Daniel Hansen [aut, cre], Peter Hickey [ctb]", "Maintainer": "Kasper Daniel Hansen ", "URL": "https://github.com/kasperdanielhansen/bsseq", "VignetteBuilder": "knitr", "BugReports": "https://github.com/kasperdanielhansen/bsseq/issues", "source.ver": "src/contrib/bsseq_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/bsseq_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/bsseq_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/bsseq_1.10.0.tgz", "vignettes": [ "vignettes/bsseq/inst/doc/bsseq_analysis.pdf", "vignettes/bsseq/inst/doc/bsseq.pdf" ], "vignetteTitles": [ "Analyzing WGBS with bsseq", "The bsseq user's guide" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/bsseq/inst/doc/bsseq_analysis.R", "vignettes/bsseq/inst/doc/bsseq.R" ], "dependsOnMe": [ "bsseqData", "DSS" ] }, "BubbleTree": { "Package": "BubbleTree", "Version": "2.4.0", "Depends": [ "R (>= 3.2.1)", "IRanges", "GenomicRanges", "plyr", "dplyr", "magrittr" ], "Imports": [ "BiocGenerics (>= 0.7.5)", "BiocStyle", "Biobase", "ggplot2", "WriteXLS", "gtools", "RColorBrewer", "limma", "grid", "gtable", "gridExtra", "biovizBase", "rainbow", "e1071" ], "Suggests": [ "methods", "knitr", "rmarkdown" ], "License": "LGPL (>= 3)", "MD5sum": "59daaf28e87fbdbf14b4484188941345", "NeedsCompilation": "no", "Title": "BubbleTree: an intuitive visualization to elucidate tumoral aneuploidy and clonality in somatic mosaicism using next generation sequencing data", "Description": "CNV analysis in groups of tumor samples (Publication Pending).", "biocViews": [ "CopyNumberVariation", "Coverage", "Sequencing", "Software" ], "Author": "Wei Zhu , Michael Kuziora , Todd Creasy , Brandon Higgs ", "Maintainer": "Todd Creasy , Wei Zhu ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/BubbleTree_2.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BubbleTree_2.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BubbleTree_2.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BubbleTree_2.4.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/BubbleTree/inst/doc/BubbleTree-vignette.R" ], "htmlDocs": [ "vignettes/BubbleTree/inst/doc/BubbleTree-vignette.html" ], "htmlTitles": [ "BubbleTree Tutorial" ] }, "BufferedMatrix": { "Package": "BufferedMatrix", "Version": "1.38.0", "Depends": [ "R (>= 2.6.0)", "methods" ], "License": "LGPL (>= 2)", "Archs": "i386, x64", "MD5sum": "8ca8f7aa73052f605e7991d522982382", "NeedsCompilation": "yes", "Title": "A matrix data storage object held in temporary files", "Description": "A tabular style data object where most data is stored outside main memory. A buffer is used to speed up access to data.", "biocViews": [ "Infrastructure", "Software" ], "Author": "Benjamin Milo Bolstad ", "Maintainer": "Benjamin Milo Bolstad ", "URL": "https://github.com/bmbolstad/BufferedMatrix", "source.ver": "src/contrib/BufferedMatrix_1.38.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BufferedMatrix_1.38.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BufferedMatrix_1.38.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BufferedMatrix_1.38.0.tgz", "vignettes": [ "vignettes/BufferedMatrix/inst/doc/BufferedMatrix.pdf" ], "vignetteTitles": [ "BufferedMatrix: Introduction" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/BufferedMatrix/inst/doc/BufferedMatrix.R" ], "dependsOnMe": [ "BufferedMatrixMethods" ] }, "BufferedMatrixMethods": { "Package": "BufferedMatrixMethods", "Version": "1.38.0", "Depends": [ "R (>= 2.6.0)", "BufferedMatrix (>= 1.3.0)", "methods" ], "LinkingTo": [ "BufferedMatrix" ], "Suggests": [ "affyio", "affy" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "ae4c0bea5940df6c4f4beef02e0d8e16", "NeedsCompilation": "yes", "Title": "Microarray Data related methods that utlize BufferedMatrix objects", "Description": "Microarray analysis methods that use BufferedMatrix objects", "biocViews": [ "Infrastructure", "Software" ], "Author": "B. M. Bolstad ", "Maintainer": "B. M. Bolstad ", "URL": "https://github.bom/bmbolstad/BufferedMatrixMethods", "source.ver": "src/contrib/BufferedMatrixMethods_1.38.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BufferedMatrixMethods_1.38.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BufferedMatrixMethods_1.38.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BufferedMatrixMethods_1.38.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false }, "bumphunter": { "Package": "bumphunter", "Version": "1.14.0", "Depends": [ "R (>= 2.10)", "S4Vectors (>= 0.9.25)", "IRanges (>= 2.3.23)", "GenomeInfoDb", "GenomicRanges", "foreach", "iterators", "methods", "parallel", "locfit" ], "Imports": [ "matrixStats", "limma", "doRNG", "BiocGenerics", "utils", "GenomicFeatures", "AnnotationDbi" ], "Suggests": [ "testthat", "RUnit", "doParallel", "org.Hs.eg.db", "TxDb.Hsapiens.UCSC.hg19.knownGene" ], "License": "Artistic-2.0", "MD5sum": "90190b1412e78f8f3cd6cb81e3ee51fe", "NeedsCompilation": "no", "Title": "Bump Hunter", "Description": "Tools for finding bumps in genomic data", "biocViews": [ "DNAMethylation", "Epigenetics", "Infrastructure", "MultipleComparison", "Software" ], "Author": "Rafael A. Irizarry [cre, aut], Martin Aryee [aut], Kasper Daniel Hansen [aut], Hector Corrada Bravo [aut], Shan Andrews [ctb], Andrew E. Jaffe [ctb], Harris Jaffee [ctb], Leonardo Collado-Torres [ctb]", "Maintainer": "Rafael A. Irizarry ", "URL": "https://github.com/ririzarr/bumphunter", "source.ver": "src/contrib/bumphunter_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/bumphunter_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/bumphunter_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/bumphunter_1.14.0.tgz", "vignettes": [ "vignettes/bumphunter/inst/doc/bumphunter.pdf" ], "vignetteTitles": [ "The bumphunter user's guide" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/bumphunter/inst/doc/bumphunter.R" ], "dependsOnMe": [ "minfi" ], "importsMe": [ "ChAMP", "derfinder" ], "suggestsMe": [ "derfinderPlot", "epivizrData", "regionReport" ] }, "BUS": { "Package": "BUS", "Version": "1.30.0", "Depends": [ "R (>= 2.3.0)", "minet" ], "Imports": [ "stats", "infotheo" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "323b7ba9e6185e4bcf66742ca26d4712", "NeedsCompilation": "yes", "Title": "Gene network reconstruction", "Description": "This package can be used to compute associations among genes (gene-networks) or between genes and some external traits (i.e. clinical).", "biocViews": [ "Preprocessing", "Software" ], "Author": "Yin Jin, Hesen Peng, Lei Wang, Raffaele Fronza, Yuanhua Liu and Christine Nardini", "Maintainer": "Yuanhua Liu ", "source.ver": "src/contrib/BUS_1.30.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/BUS_1.30.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/BUS_1.30.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/BUS_1.30.0.tgz", "vignettes": [ "vignettes/BUS/inst/doc/bus.pdf" ], "vignetteTitles": [ "bus.pdf" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/BUS/inst/doc/bus.R" ] }, "CAFE": { "Package": "CAFE", "Version": "1.10.0", "Depends": [ "R (>= 2.10)", "biovizBase", "GenomicRanges", "IRanges", "ggbio" ], "Imports": [ "affy", "ggplot2", "annotate", "grid", "gridExtra", "tcltk", "Biobase" ], "Suggests": [ "RUnit", "BiocGenerics", "BiocStyle" ], "License": "GPL-3", "MD5sum": "83524731a059e100a6617716e27b5e8c", "NeedsCompilation": "no", "Title": "Chromosmal Aberrations Finder in Expression data", "Description": "Detection and visualizations of gross chromosomal aberrations using Affymetrix expression microarrays as input", "biocViews": [ "GeneExpression", "GeneSetEnrichment", "Microarray", "OneChannel", "Software" ], "Author": "Sander Bollen", "Maintainer": "Sander Bollen ", "source.ver": "src/contrib/CAFE_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CAFE_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CAFE_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CAFE_1.10.0.tgz", "vignettes": [ "vignettes/CAFE/inst/doc/CAFE-manual.pdf" ], "vignetteTitles": [ "Manual" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CAFE/inst/doc/CAFE-manual.R" ] }, "CAGEr": { "Package": "CAGEr", "Version": "1.16.0", "Depends": [ "methods", "R (>= 2.15.0)", "BSgenome" ], "Imports": [ "utils", "Rsamtools", "GenomicRanges (>= 1.23.16)", "IRanges (>= 2.5.27)", "data.table", "beanplot", "rtracklayer", "som", "VGAM" ], "Suggests": [ "BSgenome.Drerio.UCSC.danRer7", "FANTOM3and4CAGE" ], "Enhances": [ "parallel" ], "License": "GPL-3", "MD5sum": "02b2054c835d58b48c02dded002661da", "NeedsCompilation": "no", "Title": "Analysis of CAGE (Cap Analysis of Gene Expression) sequencing data for precise mapping of transcription start sites and promoterome mining", "Description": "Preprocessing of CAGE sequencing data, identification and normalization of transcription start sites and downstream analysis of transcription start sites clusters (promoters).", "biocViews": [ "Clustering", "FunctionalGenomics", "GeneExpression", "Normalization", "Preprocessing", "Sequencing", "Software", "Transcription", "Visualization" ], "Author": "Vanja Haberle, Department of Biology, University of Bergen, Norway ", "Maintainer": "Vanja Haberle ", "source.ver": "src/contrib/CAGEr_1.16.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CAGEr_1.16.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CAGEr_1.16.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CAGEr_1.16.0.tgz", "vignettes": [ "vignettes/CAGEr/inst/doc/CAGEr.pdf" ], "vignetteTitles": [ "CAGEr" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CAGEr/inst/doc/CAGEr.R" ], "suggestsMe": [ "seqPattern" ] }, "CALIB": { "Package": "CALIB", "Version": "1.40.0", "Depends": [ "R (>= 2.10)", "limma", "methods" ], "Imports": [ "limma", "methods", "graphics", "stats", "utils" ], "License": "LGPL", "Archs": "i386, x64", "MD5sum": "f4f73cdbdb1211417c14a42fd96e9819", "NeedsCompilation": "yes", "Title": "Calibration model for estimating absolute expression levels from microarray data", "Description": "This package contains functions for normalizing spotted microarray data, based on a physically motivated calibration model. The model parameters and error distributions are estimated from external control spikes.", "biocViews": [ "Microarray", "Preprocessing", "Software", "TwoChannel" ], "Author": "Hui Zhao, Kristof Engelen, Bart De Moor and Kathleen Marchal", "Maintainer": "Hui Zhao ", "source.ver": "src/contrib/CALIB_1.40.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CALIB_1.40.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CALIB_1.40.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CALIB_1.40.0.tgz", "vignettes": [ "vignettes/CALIB/inst/doc/quickstart.pdf" ], "vignetteTitles": [ "CALIB Overview" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CALIB/inst/doc/quickstart.R" ] }, "CAMERA": { "Package": "CAMERA", "Version": "1.30.0", "Depends": [ "R (>= 2.1.0)", "methods", "Biobase", "xcms (>= 1.13.5)" ], "Imports": [ "methods", "xcms", "RBGL", "graph", "graphics", "grDevices", "stats", "utils", "Hmisc", "igraph" ], "Suggests": [ "faahKO", "RUnit", "BiocGenerics" ], "Enhances": [ "Rmpi", "snow" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "aed35cf1c221c691fd10f3b780afa491", "NeedsCompilation": "yes", "Title": "Collection of annotation related methods for mass spectrometry data", "Description": "Annotation of peaklists generated by xcms, rule based annotation of isotopes and adducts, isotope validation, EIC correlation based tagging of unknown adducts and fragments", "biocViews": [ "MassSpectrometry", "Metabolomics", "Software" ], "Author": "Carsten Kuhl, Ralf Tautenhahn, Hendrik Treutler, Steffen Neumann {ckuhl|htreutle|sneumann}@ipb-halle.de, rtautenh@scripps.edu", "Maintainer": "Steffen Neumann ", "URL": "http://msbi.ipb-halle.de/msbi/CAMERA/", "BugReports": "https://github.com/sneumann/CAMERA/issues/new", "source.ver": "src/contrib/CAMERA_1.30.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CAMERA_1.30.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CAMERA_1.30.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CAMERA_1.30.0.tgz", "vignettes": [ "vignettes/CAMERA/inst/doc/CAMERA.pdf", "vignettes/CAMERA/inst/doc/compoundQuantilesVignette.pdf", "vignettes/CAMERA/inst/doc/IsotopeDetectionVignette.pdf" ], "vignetteTitles": [ "Molecule Identification with CAMERA", "Isotope pattern validation with CAMERA", "Isotope pattern validation with CAMERA" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CAMERA/inst/doc/CAMERA.R" ], "dependsOnMe": [ "flagme", "IPO", "LOBSTAHS", "MAIT", "metaMS", "PtH2O2lipids" ], "suggestsMe": [ "mtbls2", "RMassBank", "ropls" ] }, "canceR": { "Package": "canceR", "Version": "1.6.0", "Depends": [ "R (>= 3.3)", "tcltk", "tcltk2", "cgdsr" ], "Imports": [ "GSEABase", "GSEAlm", "tkrplot", "geNetClassifier", "RUnit", "Formula", "rpart", "survival", "Biobase", "phenoTest", "circlize", "plyr", "graphics", "stats", "utils" ], "Suggests": [ "testthat (>= 0.10.0)", "R.rsp" ], "License": "GPL-2", "MD5sum": "2fb494e8b95b676e588be6e6dfcc0427", "NeedsCompilation": "no", "Title": "A Graphical User Interface for accessing and modeling the Cancer Genomics Data of MSKCC.", "Description": "The package is user friendly interface based on the cgdsr and other modeling packages to explore, compare, and analyse all available Cancer Data (Clinical data, Gene Mutation, Gene Methylation, Gene Expression, Protein Phosphorylation, Copy Number Alteration) hosted by the Computational Biology Center at Memorial-Sloan-Kettering Cancer Center (MSKCC).", "biocViews": [ "GUI", "GeneExpression", "Software" ], "Author": "Karim Mezhoud. Nuclear Safety & Security Department. Nuclear Science Center of Tunisia.", "Maintainer": "Karim Mezhoud ", "VignetteBuilder": "R.rsp", "source.ver": "src/contrib/canceR_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/canceR_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/canceR_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/canceR_1.6.0.tgz", "vignettes": [ "vignettes/canceR/inst/doc/canceR.pdf" ], "vignetteTitles": [ "canceR Vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false }, "cancerclass": { "Package": "cancerclass", "Version": "1.18.0", "Depends": [ "R (>= 2.14.0)", "Biobase", "binom", "methods", "stats" ], "Suggests": [ "cancerdata" ], "License": "GPL 3", "Archs": "i386, x64", "MD5sum": "95b0c12dcf733504c8121d56ec23dfa3", "NeedsCompilation": "yes", "Title": "Development and validation of diagnostic tests from high-dimensional molecular data", "Description": "The classification protocol starts with a feature selection step and continues with nearest-centroid classification. The accurarcy of the predictor can be evaluated using training and test set validation, leave-one-out cross-validation or in a multiple random validation protocol. Methods for calculation and visualization of continuous prediction scores allow to balance sensitivity and specificity and define a cutoff value according to clinical requirements.", "biocViews": [ "Cancer", "Classification", "Microarray", "Software", "Visualization" ], "Author": "Jan Budczies, Daniel Kosztyla", "Maintainer": "Daniel Kosztyla ", "source.ver": "src/contrib/cancerclass_1.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/cancerclass_1.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/cancerclass_1.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/cancerclass_1.18.0.tgz", "vignettes": [ "vignettes/cancerclass/inst/doc/vignette_cancerclass.pdf" ], "vignetteTitles": [ "Cancerclass: An R package for development and validation of diagnostic tests from high-dimensional molecular data" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/cancerclass/inst/doc/vignette_cancerclass.R" ] }, "CancerInSilico": { "Package": "CancerInSilico", "Version": "1.0.0", "Depends": [ "Rcpp" ], "Imports": [ "methods", "grDevices", "graphics", "stats" ], "LinkingTo": [ "Rcpp", "testthat", "BH" ], "Suggests": [ "testthat", "knitr", "rmarkdown", "BiocStyle" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "c539849498418c8fd835bcfb6d918825", "NeedsCompilation": "yes", "Title": "An R interface for computational modeling of tumor progression", "Description": "The CancerInSilico package provides an R interface for running mathematical models of tumor progresson. This package has the underlying models implemented in C++ and the output and analysis features implemented in R.", "biocViews": [ "BiomedicalInformatics", "CellBiology", "MathematicalBiology", "Software", "SystemsBiology" ], "Author": "Thomas D. Sherman, Raymond Cheng, Elana J. Fertig", "Maintainer": "Thomas D. Sherman , Elana J. Fertig ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/CancerInSilico_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CancerInSilico_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CancerInSilico_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CancerInSilico_1.0.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/CancerInSilico/inst/doc/CancerInSilico.R" ], "htmlDocs": [ "vignettes/CancerInSilico/inst/doc/CancerInSilico.html" ], "htmlTitles": [ "The CancerInSilico Package" ] }, "CancerMutationAnalysis": { "Package": "CancerMutationAnalysis", "Version": "1.16.0", "Depends": [ "R (>= 2.10.0)", "qvalue" ], "Imports": [ "AnnotationDbi", "limma", "methods", "stats" ], "Suggests": [ "KEGG.db" ], "License": "GPL (>= 2) + file LICENSE", "Archs": "i386, x64", "MD5sum": "9145336eec31622a363ede12599cc95c", "NeedsCompilation": "yes", "Title": "Cancer mutation analysis", "Description": "This package implements gene and gene-set level analysis methods for somatic mutation studies of cancer. The gene-level methods distinguish between driver genes (which play an active role in tumorigenesis) and passenger genes (which are mutated in tumor samples, but have no role in tumorigenesis) and incorporate a two-stage study design. The gene-set methods implement a patient-oriented approach, which calculates gene-set scores for each sample, then combines them across samples; a gene-oriented approach which uses the Wilcoxon test is also provided for comparison.", "biocViews": [ "Genetics", "Software" ], "Author": "Giovanni Parmigiani, Simina M. Boca", "Maintainer": "Simina M. Boca ", "source.ver": "src/contrib/CancerMutationAnalysis_1.16.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CancerMutationAnalysis_1.16.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CancerMutationAnalysis_1.16.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CancerMutationAnalysis_1.16.0.tgz", "vignettes": [ "vignettes/CancerMutationAnalysis/inst/doc/CancerMutationAnalysis.pdf" ], "vignetteTitles": [ "CancerMutationAnalysisTutorial" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/CancerMutationAnalysis/inst/doc/CancerMutationAnalysis.R" ] }, "CancerSubtypes": { "Package": "CancerSubtypes", "Version": "1.0.0", "Depends": [ "R (>= 3.3)", "sigclust", "NMF" ], "Imports": [ "SNFtool", "iCluster", "survival", "cluster", "impute", "limma", "ConsensusClusterPlus", "grDevices" ], "Suggests": [ "BiocGenerics", "knitr", "RTCGA.mRNA", "RTCGA.clinical" ], "License": "GPL (>= 2)", "MD5sum": "76c3f5ba3867a1fd7980bd8d44fe0042", "NeedsCompilation": "no", "Title": "Cancer subtypes identification, validation and visualization based on genomic data", "Description": "CancerSubtypes integrates the current common computational biology methods for cancer subtypes identification and provides a standardized framework for cancer subtype analysis based on the genomic datasets.", "biocViews": [ "Clustering", "GeneExpression", "Software", "Visualization" ], "Author": "Taosheng Xu, Thuc Le", "Maintainer": "Taosheng Xu", "VignetteBuilder": "knitr", "source.ver": "src/contrib/CancerSubtypes_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CancerSubtypes_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CancerSubtypes_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CancerSubtypes_1.0.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CancerSubtypes/inst/doc/CancerSubtypes-vignette.R" ], "htmlDocs": [ "vignettes/CancerSubtypes/inst/doc/CancerSubtypes-vignette.html" ], "htmlTitles": [ "CancerSubtypes" ] }, "CAnD": { "Package": "CAnD", "Version": "1.6.0", "Imports": [ "methods", "ggplot2", "reshape" ], "Suggests": [ "RUnit", "BiocGenerics", "BiocStyle" ], "License": "Artistic-2.0", "MD5sum": "e34d6801e9b60779b42c9a448869dd67", "NeedsCompilation": "no", "Title": "Perform Chromosomal Ancestry Differences (CAnD) Analyses", "Description": "Functions to perform the CAnD test on a set of ancestry proportions. For a particular ancestral subpopulation, a user will supply the estimated ancestry proportion for each sample, and each chromosome or chromosomal segment of interest. A p-value for each chromosome as well as an overall CAnD p-value will be returned for each test. Plotting functions are also available.", "biocViews": [ "GeneticVariability", "Genetics", "SNP", "Software", "StatisticalMethod" ], "Author": "Caitlin McHugh, Timothy Thornton", "Maintainer": "Caitlin McHugh ", "source.ver": "src/contrib/CAnD_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CAnD_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CAnD_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CAnD_1.6.0.tgz", "vignettes": [ "vignettes/CAnD/inst/doc/CAnD.pdf" ], "vignetteTitles": [ "Detecting heterogenity in population structure across chromosomes with the \"CAnD\" package" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CAnD/inst/doc/CAnD.R" ] }, "caOmicsV": { "Package": "caOmicsV", "Version": "1.4.0", "Depends": [ "R (>= 3.2)", "igraph (>= 0.7.1)", "bc3net (>= 1.0.2)" ], "License": "GPL (>=2.0)", "MD5sum": "ee1466c53002a1b8b3fdcdb697ef106a", "NeedsCompilation": "no", "Title": "Visualization of multi-dimentional cancer genomics data", "Description": "caOmicsV package provides methods to visualize multi-dimentional cancer genomics data including of patient information, gene expressions, DNA methylations, DNA copy number variations, and SNP/mutations in matrix layout or network layout.", "biocViews": [ "Network", "RNASeq", "Software", "Visualization" ], "Author": "Henry Zhang", "Maintainer": "Henry Zhang ", "source.ver": "src/contrib/caOmicsV_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/caOmicsV_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/caOmicsV_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/caOmicsV_1.4.0.tgz", "vignettes": [ "vignettes/caOmicsV/inst/doc/Introduction_to_caOmicsV.pdf" ], "vignetteTitles": [ "Intrudoction_to_caOmicsV" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/caOmicsV/inst/doc/Introduction_to_caOmicsV.R" ] }, "Cardinal": { "Package": "Cardinal", "Version": "1.6.0", "Depends": [ "BiocGenerics", "Biobase", "graphics", "methods", "stats", "ProtGenerics" ], "Imports": [ "grid", "irlba", "lattice", "signal", "sp", "stats4", "utils" ], "Suggests": [ "BiocStyle", "testthat" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "a6941f365dd8c52c1acdd5dbd4c60e19", "NeedsCompilation": "yes", "Title": "A mass spectrometry imaging toolbox for statistical analysis", "Description": "Implements statistical & computational tools for analyzing mass spectrometry imaging datasets, including methods for efficient pre-processing, spatial segmentation, and classification.", "biocViews": [ "Classification", "Clustering", "ImagingMassSpectrometry", "Infrastructure", "Lipidomics", "MassSpectrometry", "Normalization", "Proteomics", "Software" ], "Author": "Kylie A. Bemis ", "Maintainer": "Kylie A. Bemis ", "URL": "http://www.cardinalmsi.org", "source.ver": "src/contrib/Cardinal_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Cardinal_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Cardinal_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Cardinal_1.6.0.tgz", "vignettes": [ "vignettes/Cardinal/inst/doc/Cardinal-development.pdf", "vignettes/Cardinal/inst/doc/Cardinal-walkthrough.pdf" ], "vignetteTitles": [ "Cardinal design and development", "Cardinal: Analytic tools for mass spectrometry imaging" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Cardinal/inst/doc/Cardinal-development.R", "vignettes/Cardinal/inst/doc/Cardinal-walkthrough.R" ], "suggestsMe": [ "matter" ], "dependsOnMe": [ "CardinalWorkflows" ] }, "casper": { "Package": "casper", "Version": "2.8.0", "Depends": [ "R (>= 2.14.1)", "Biobase", "IRanges", "methods", "GenomicRanges" ], "Imports": [ "BiocGenerics", "coda", "EBarrays", "gaga", "gtools", "GenomeInfoDb", "GenomicFeatures", "limma", "mgcv", "Rsamtools", "rtracklayer", "S4Vectors (>= 0.9.25)", "sqldf", "survival", "VGAM" ], "Enhances": [ "parallel" ], "License": "GPL (>=2)", "Archs": "i386, x64", "MD5sum": "95e9283aa9b61c9a1ddc6e4dc4eaaf9c", "NeedsCompilation": "yes", "Title": "Characterization of Alternative Splicing based on Paired-End Reads", "Description": "Infer alternative splicing from paired-end RNA-seq data. The model is based on counting paths across exons, rather than pairwise exon connections, and estimates the fragment size and start distributions non-parametrically, which improves estimation precision.", "biocViews": [ "DifferentialExpression", "GeneExpression", "RNASeq", "Sequencing", "Software", "Transcription" ], "Author": "David Rossell, Camille Stephan-Otto, Manuel Kroiss, Miranda Stobbe, Victor Pena", "Maintainer": "David Rossell ", "source.ver": "src/contrib/casper_2.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/casper_2.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/casper_2.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/casper_2.8.0.tgz", "vignettes": [ "vignettes/casper/inst/doc/casper.pdf", "vignettes/casper/inst/doc/DesignRNASeq.pdf" ], "vignetteTitles": [ "Manual for the casper library", "DesignRNASeq.pdf" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/casper/inst/doc/casper.R" ] }, "Category": { "Package": "Category", "Version": "2.40.0", "Depends": [ "methods", "stats4", "BiocGenerics", "AnnotationDbi", "Biobase", "Matrix" ], "Imports": [ "utils", "stats", "graph", "RBGL", "GSEABase", "genefilter", "annotate", "RSQLite" ], "Suggests": [ "EBarrays", "ALL", "Rgraphviz", "RColorBrewer", "xtable (>= 1.4-6)", "hgu95av2.db", "KEGG.db", "SNPchip", "geneplotter", "limma", "lattice", "RUnit", "org.Sc.sgd.db", "GOstats", "GO.db" ], "License": "Artistic-2.0", "MD5sum": "6041cfb6f7ef99dc72c35353b84f76f1", "NeedsCompilation": "no", "Title": "Category Analysis", "Description": "A collection of tools for performing category analysis.", "biocViews": [ "Annotation", "GO", "GeneSetEnrichment", "Pathways", "Software" ], "Author": "R. Gentleman with contributions from S. Falcon and D.Sarkar", "Maintainer": "Bioconductor Package Maintainer ", "source.ver": "src/contrib/Category_2.40.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Category_2.40.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Category_2.40.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Category_2.40.0.tgz", "vignettes": [ "vignettes/Category/inst/doc/Category.pdf", "vignettes/Category/inst/doc/ChromBand.pdf" ], "vignetteTitles": [ "Using Categories to Analyze Microarray Data", "Using Chromosome Bands as Categories" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Category/inst/doc/Category.R", "vignettes/Category/inst/doc/ChromBand.R" ], "dependsOnMe": [ "GOstats", "meshr", "PCpheno" ], "importsMe": [ "categoryCompare", "cellHTS2", "eisa", "gCMAP", "GOstats", "interactiveDisplay", "PCpheno", "phenoTest", "ppiStats", "RDAVIDWebService", "ReportingTools" ], "suggestsMe": [ "BiocCaseStudies", "GSEAlm", "miRLAB", "MmPalateMiRNA", "qpgraph", "RnBeads" ] }, "categoryCompare": { "Package": "categoryCompare", "Version": "1.18.0", "Depends": [ "R (>= 2.10)", "Biobase", "BiocGenerics (>= 0.13.8)" ], "Imports": [ "AnnotationDbi", "hwriter", "GSEABase", "Category (>= 2.33.1)", "GOstats", "annotate", "colorspace", "graph", "RCytoscape (>= 1.5.11)" ], "Suggests": [ "knitr", "methods", "GO.db", "KEGG.db", "estrogen", "org.Hs.eg.db", "hgu95av2.db", "limma", "affy", "genefilter" ], "License": "GPL-2", "MD5sum": "3e8e4147fabacb4235a24f37d2d80d47", "NeedsCompilation": "no", "Title": "Meta-analysis of high-throughput experiments using feature annotations", "Description": "Calculates significant annotations (categories) in each of two (or more) feature (i.e. gene) lists, determines the overlap between the annotations, and returns graphical and tabular data about the significant annotations and which combinations of feature lists the annotations were found to be significant. Interactive exploration is facilitated through the use of RCytoscape (heavily suggested).", "biocViews": [ "Annotation", "GO", "GeneExpression", "MultipleComparison", "Pathways", "Software" ], "Author": "Robert M. Flight ", "Maintainer": "Robert M. Flight ", "URL": "https://github.com/rmflight/categoryCompare", "SystemRequirements": "Cytoscape (>= 2.8.0) (if used for visualization of results, heavily suggested), CytoscapeRPC plugin (>= 1.8)", "VignetteBuilder": "knitr", "BugReports": "https://github.com/rmflight/categoryCompare/issues", "source.ver": "src/contrib/categoryCompare_1.18.0.tar.gz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/categoryCompare/inst/doc/categoryCompare_vignette.R" ], "htmlDocs": [ "vignettes/categoryCompare/inst/doc/categoryCompare_vignette.html" ], "htmlTitles": [ "categoryCompare: High-throughput data meta-analysis using gene annotations" ] }, "CausalR": { "Package": "CausalR", "Version": "1.6.0", "Depends": [ "R (>= 3.2)" ], "Imports": [ "igraph" ], "Suggests": [ "knitr", "RUnit", "BiocGenerics" ], "License": "GPL (>= 2)", "MD5sum": "8947f874e95f701ef3989792004d5f14", "NeedsCompilation": "no", "Title": "Causal Reasoning Methods", "Description": "Causal reasoning methods for biological networks, to enable regulator prediction and reconstruction of regulatory networks from high dimensional data.", "biocViews": [ "GraphAndNetwork", "Network", "Software" ], "Author": "Glyn Bradley, Steven Barrett, David Wiley, Bhushan Bonde, Peter Woollard, Chirag Mistry, David Riley, Mark Pipe", "Maintainer": "Glyn Bradley , Steven Barrett , Bhushan Bonde ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/CausalR_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CausalR_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CausalR_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CausalR_1.6.0.tgz", "vignettes": [ "vignettes/CausalR/inst/doc/CausalR.pdf" ], "vignetteTitles": [ "CausalR : an R Package for causal reasoning on networks" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CausalR/inst/doc/CausalR.R" ] }, "ccmap": { "Package": "ccmap", "Version": "1.0.0", "Imports": [ "AnnotationDbi (>= 1.34.4)", "BiocInstaller", "ccdata (>= 0.99.4)", "doParallel (>= 1.0.10)", "data.table (>= 1.9.6)", "foreach (>= 1.4.3)", "parallel (>= 3.3.1)", "xgboost (>= 0.4.4)" ], "Suggests": [ "crossmeta", "knitr", "rmarkdown", "testthat", "lydata" ], "License": "MIT + file LICENSE", "MD5sum": "b4806f5a1c078180ab4b785489eed2c3", "NeedsCompilation": "no", "Title": "Combination Connectivity Mapping", "Description": "Finds drugs and drug combinations that are predicted to reverse or mimic gene expression signatures. These drugs might reverse diseases or mimic healthy lifestyles.", "biocViews": [ "DifferentialExpression", "GeneExpression", "Microarray", "Software", "Transcription" ], "Author": "Alex Pickering", "Maintainer": "Alex Pickering ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/ccmap_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ccmap_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ccmap_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ccmap_1.0.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/ccmap/inst/doc/ccmap-vignette.R" ], "htmlDocs": [ "vignettes/ccmap/inst/doc/ccmap-vignette.html" ], "htmlTitles": [ "ccmap vignette" ] }, "CCPROMISE": { "Package": "CCPROMISE", "Version": "1.0.0", "Depends": [ "R (>= 3.3.0)", "stats", "methods", "CCP", "PROMISE", "Biobase", "GSEABase", "utils" ], "License": "GPL (>= 2)", "MD5sum": "425b3fe94f625fb550ea87d3c6edb8db", "NeedsCompilation": "no", "Title": "PROMISE analysis with Canonical Correlation for Two Forms of High Dimensional Genetic Data", "Description": "Perform Canonical correlation between two forms of high demensional genetic data, and associate the first compoent of each form of data with a specific biologically interesting pattern of associations with multiple endpoints. A probe level analysis is also implemented.", "biocViews": [ "GeneExpression", "Microarray", "Software" ], "Author": "Xueyuan Cao and Stanley.pounds ", "Maintainer": "Xueyuan Cao ", "source.ver": "src/contrib/CCPROMISE_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CCPROMISE_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CCPROMISE_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CCPROMISE_1.0.0.tgz", "vignettes": [ "vignettes/CCPROMISE/inst/doc/CCPROMISE.pdf" ], "vignetteTitles": [ "An introduction to CCPROMISE" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CCPROMISE/inst/doc/CCPROMISE.R" ] }, "ccrepe": { "Package": "ccrepe", "Version": "1.10.0", "Imports": [ "infotheo (>= 1.1)" ], "Suggests": [ "knitr", "BiocStyle", "BiocGenerics", "testthat" ], "License": "MIT + file LICENSE", "MD5sum": "da4367ca0043c3a52f63df8b2faa9ac1", "NeedsCompilation": "no", "Title": "ccrepe_and_nc.score", "Description": "The CCREPE (Compositionality Corrected by REnormalizaion and PErmutation) package is designed to assess the significance of general similarity measures in compositional datasets. In microbial abundance data, for example, the total abundances of all microbes sum to one; CCREPE is designed to take this constraint into account when assigning p-values to similarity measures between the microbes. The package has two functions: ccrepe: Calculates similarity measures, p-values and q-values for relative abundances of bugs in one or two body sites using bootstrap and permutation matrices of the data. nc.score: Calculates species-level co-variation and co-exclusion patterns based on an extension of the checkerboard score to ordinal data.", "biocViews": [ "Bioinformatics", "Metagenomics", "Software", "Statistics" ], "Author": "Emma Schwager ,Craig Bielski, George Weingart", "Maintainer": "Emma Schwager ,Craig Bielski, George Weingart", "VignetteBuilder": "knitr", "source.ver": "src/contrib/ccrepe_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ccrepe_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ccrepe_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ccrepe_1.10.0.tgz", "vignettes": [ "vignettes/ccrepe/inst/doc/ccrepe.pdf" ], "vignetteTitles": [ "ccrepe" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/ccrepe/inst/doc/ccrepe.R" ] }, "cellGrowth": { "Package": "cellGrowth", "Version": "1.18.0", "Depends": [ "R (>= 2.12.0)", "locfit (>= 1.5-4)" ], "Imports": [ "lattice" ], "License": "Artistic-2.0", "MD5sum": "43a2e554c0eb496731704ef98e54f72f", "NeedsCompilation": "no", "Title": "Fitting cell population growth models", "Description": "This package provides functionalities for the fitting of cell population growth models on experimental OD curves.", "biocViews": [ "CellBasedAssays", "DataImport", "MicrotitrePlateAssay", "Software", "TimeCourse", "Visualization" ], "Author": "Julien Gagneur , Andreas Neudecker ", "Maintainer": "Julien Gagneur ", "source.ver": "src/contrib/cellGrowth_1.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/cellGrowth_1.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/cellGrowth_1.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/cellGrowth_1.18.0.tgz", "vignettes": [ "vignettes/cellGrowth/inst/doc/cellGrowth.pdf" ], "vignetteTitles": [ "Overview of the cellGrowth package." ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/cellGrowth/inst/doc/cellGrowth.R" ] }, "cellHTS2": { "Package": "cellHTS2", "Version": "2.38.0", "Depends": [ "R (>= 2.10)", "RColorBrewer", "Biobase", "methods", "genefilter", "splots", "vsn", "hwriter", "locfit", "grid" ], "Imports": [ "prada", "GSEABase", "Category", "stats4" ], "Suggests": [ "ggplot2" ], "License": "Artistic-2.0", "MD5sum": "32ecdc85d57208a21bfe397ab75e1ccf", "NeedsCompilation": "no", "Title": "Analysis of cell-based screens - revised version of cellHTS", "Description": "This package provides tools for the analysis of high-throughput assays that were performed in microtitre plate formats (including but not limited to 384-well plates). The functionality includes data import and management, normalisation, quality assessment, replicate summarisation and statistical scoring. A webpage that provides a detailed graphical overview over the data and analysis results is produced. In our work, we have applied the package to RNAi screens on fly and human cells, and for screens of yeast libraries. See ?cellHTS2 for a brief introduction.", "biocViews": [ "CellBasedAssays", "Preprocessing", "Software", "Visualization" ], "Author": "Ligia Bras, Wolfgang Huber , Michael Boutros , Gregoire Pau , Florian Hahne ", "Maintainer": "Joseph Barry ", "URL": "http://www.dkfz.de/signaling, http://www.ebi.ac.uk/huber", "source.ver": "src/contrib/cellHTS2_2.38.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/cellHTS2_2.38.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/cellHTS2_2.38.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/cellHTS2_2.38.0.tgz", "vignettes": [ "vignettes/cellHTS2/inst/doc/cellhts2.pdf", "vignettes/cellHTS2/inst/doc/cellhts2Complete.pdf", "vignettes/cellHTS2/inst/doc/twoChannels.pdf", "vignettes/cellHTS2/inst/doc/twoWay.pdf" ], "vignetteTitles": [ "Main vignette: End-to-end analysis of cell-based screens", "Main vignette (complete version): End-to-end analysis of cell-based screens", "Supplement: multi-channel assays", "Supplement: enhancer-suppressor screens" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/cellHTS2/inst/doc/cellhts2.R", "vignettes/cellHTS2/inst/doc/cellhts2Complete.R", "vignettes/cellHTS2/inst/doc/twoChannels.R", "vignettes/cellHTS2/inst/doc/twoWay.R" ], "dependsOnMe": [ "coRNAi", "imageHTS", "staRank" ], "importsMe": [ "gespeR", "HTSanalyzeR", "RNAinteract" ], "suggestsMe": [ "bioassayR", "prada" ] }, "cellity": { "Package": "cellity", "Version": "1.2.0", "Depends": [ "R (>= 3.3)" ], "Imports": [ "AnnotationDbi", "e1071", "ggplot2", "graphics", "grDevices", "grid", "mvoutlier", "org.Hs.eg.db", "org.Mm.eg.db", "robustbase", "stats", "topGO", "utils" ], "Suggests": [ "BiocStyle", "caret", "knitr", "testthat", "rmarkdown" ], "License": "GPL (>= 2)", "MD5sum": "5296a8721dbfb2ec0b7f326304f4316a", "NeedsCompilation": "no", "Title": "Quality Control for Single-Cell RNA-seq Data", "Description": "A support vector machine approach to identifying and filtering low quality cells from single-cell RNA-seq datasets.", "biocViews": [ "DimensionReduction", "GeneExpression", "Normalization", "Preprocessing", "QualityControl", "RNASeq", "Sequencing", "Software", "SupportVectorMachine", "Transcriptomics", "Visualization" ], "Author": "Tomislav Illicic, Davis McCarthy", "Maintainer": "Tomislav Ilicic ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/cellity_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/cellity_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/cellity_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/cellity_1.2.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/cellity/inst/doc/cellity_vignette.R" ], "htmlDocs": [ "vignettes/cellity/inst/doc/cellity_vignette.html" ], "htmlTitles": [ "An introduction to the cellity package" ] }, "CellMapper": { "Package": "CellMapper", "Version": "1.0.0", "Depends": [ "S4Vectors", "methods" ], "Imports": [ "stats", "utils" ], "Suggests": [ "CellMapperData", "Biobase", "HumanAffyData", "ALL", "BiocStyle", "ExperimentHub" ], "License": "Artistic-2.0", "MD5sum": "4142471434db4d8ad3a5860d48585bc6", "NeedsCompilation": "no", "Title": "Predict genes expressed selectively in specific cell types", "Description": "Infers cell type-specific expression based on co-expression similarity with known cell type marker genes. Can make accurate predictions using publicly available expression data, even when a cell type has not been isolated before.", "biocViews": [ "GeneExpression", "Microarray", "Software" ], "Author": "Brad Nelms", "Maintainer": "Brad Nelms ", "source.ver": "src/contrib/CellMapper_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CellMapper_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CellMapper_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CellMapper_1.0.0.tgz", "vignettes": [ "vignettes/CellMapper/inst/doc/CellMapper.pdf" ], "vignetteTitles": [ "CellMapper Vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CellMapper/inst/doc/CellMapper.R" ], "dependsOnMe": [ "CellMapperData" ] }, "CellNOptR": { "Package": "CellNOptR", "Version": "1.20.0", "Depends": [ "R (>= 2.15.0)", "RBGL", "graph", "methods", "hash", "ggplot2", "RCurl", "Rgraphviz", "XML" ], "Suggests": [ "RUnit", "BiocGenerics", "igraph" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "b0cbd1696dfd3f4fa515f9e1da2dfbc0", "NeedsCompilation": "yes", "Title": "Training of boolean logic models of signalling networks using prior knowledge networks and perturbation data.", "Description": "This package does optimisation of boolean logic networks of signalling pathways based on a previous knowledge network and a set of data upon perturbation of the nodes in the network.", "biocViews": [ "CellBasedAssays", "CellBiology", "Proteomics", "Software", "TimeCourse" ], "Author": "T.Cokelaer, F.Eduati, A.MacNamara, S.Schrier, C.Terfve", "Maintainer": "T.Cokelaer ", "SystemRequirements": "Graphviz version >= 2.2", "source.ver": "src/contrib/CellNOptR_1.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CellNOptR_1.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CellNOptR_1.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CellNOptR_1.20.0.tgz", "vignettes": [ "vignettes/CellNOptR/inst/doc/CellNOptR-vignette.pdf" ], "vignetteTitles": [ "Main vignette:Playing with networks using CellNOptR" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CellNOptR/inst/doc/CellNOptR-vignette.R" ], "dependsOnMe": [ "CNORdt", "CNORfeeder", "CNORfuzzy", "CNORode" ], "suggestsMe": [ "MEIGOR" ] }, "cellTree": { "Package": "cellTree", "Version": "1.4.0", "Depends": [ "R (>= 3.3)", "topGO" ], "Imports": [ "topicmodels", "slam", "maptpx", "igraph", "xtable", "gplots" ], "Suggests": [ "BiocStyle", "knitr", "HSMMSingleCell", "biomaRt", "org.Hs.eg.db", "Biobase", "tools" ], "License": "Artistic-2.0", "MD5sum": "2020b037bfd38a8d6d2bffebbe906883", "NeedsCompilation": "no", "Title": "Inference and visualisation of Single-Cell RNA-seq data as a hierarchical tree structure", "Description": "This packages computes a Latent Dirichlet Allocation (LDA) model of single-cell RNA-seq data and builds a compact tree modelling the relationship between individual cells over time or space.", "biocViews": [ "BiomedicalInformatics", "CellBiology", "Clustering", "FunctionalGenomics", "GO", "GeneExpression", "GeneSetEnrichment", "GraphAndNetwork", "Microarray", "RNASeq", "Sequencing", "Software", "SystemsBiology", "TimeCourse", "Visualization" ], "Author": "David duVerle [aut, cre], Koji Tsuda [aut]", "Maintainer": "David duVerle ", "URL": "http://tsudalab.org", "VignetteBuilder": "knitr", "source.ver": "src/contrib/cellTree_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/cellTree_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/cellTree_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/cellTree_1.4.0.tgz", "vignettes": [ "vignettes/cellTree/inst/doc/cellTree-vignette.pdf" ], "vignetteTitles": [ "Inference and visualisation of Single-Cell RNA-seq Data data as a hierarchical tree structure" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/cellTree/inst/doc/cellTree-vignette.R" ] }, "CexoR": { "Package": "CexoR", "Version": "1.12.0", "Depends": [ "R (>= 2.10.0)", "S4Vectors", "IRanges" ], "Imports": [ "Rsamtools", "GenomeInfoDb", "GenomicRanges", "rtracklayer", "idr", "RColorBrewer", "genomation" ], "Suggests": [ "RUnit", "BiocGenerics", "BiocStyle" ], "License": "Artistic-2.0 | GPL-2 + file LICENSE", "MD5sum": "e2f3605dc4a329e0565efd6021af7cae", "NeedsCompilation": "no", "Title": "An R package to uncover high-resolution protein-DNA interactions in ChIP-exo replicates", "Description": "Strand specific peak-pair calling in ChIP-exo replicates. The cumulative Skellam distribution function (package 'skellam') is used to detect significant normalised count differences of opposed sign at each DNA strand (peak-pairs). Irreproducible discovery rate for overlapping peak-pairs across biological replicates is estimated using the package 'idr'.", "biocViews": [ "Genetics", "Sequencing", "Software", "Transcription" ], "Author": "Pedro Madrigal ", "Maintainer": "Pedro Madrigal ", "source.ver": "src/contrib/CexoR_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CexoR_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CexoR_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CexoR_1.12.0.tgz", "vignettes": [ "vignettes/CexoR/inst/doc/CexoR.pdf" ], "vignetteTitles": [ "CexoR Vignette" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/CexoR/inst/doc/CexoR.R" ] }, "CFAssay": { "Package": "CFAssay", "Version": "1.8.0", "Depends": [ "R (>= 2.10.0)" ], "License": "LGPL", "MD5sum": "dcf02c3606894d7a8b7f455eef489050", "NeedsCompilation": "no", "Title": "Statistical analysis for the Colony Formation Assay", "Description": "The package provides functions for calculation of linear-quadratic cell survival curves and for ANOVA of experimental 2-way designs along with the colony formation assay.", "biocViews": [ "CellBasedAssays", "CellBiology", "Regression", "Software", "Survival" ], "Author": "Herbert Braselmann", "Maintainer": "Herbert Braselmann ", "source.ver": "src/contrib/CFAssay_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CFAssay_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CFAssay_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CFAssay_1.8.0.tgz", "vignettes": [ "vignettes/CFAssay/inst/doc/cfassay.pdf" ], "vignetteTitles": [ "CFAssay" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CFAssay/inst/doc/cfassay.R" ] }, "CGEN": { "Package": "CGEN", "Version": "3.10.0", "Depends": [ "R (>= 2.10.1)", "survival", "mvtnorm" ], "Suggests": [ "cluster" ], "License": "GPL-2 + file LICENSE", "Archs": "i386, x64", "MD5sum": "1dd7f460221ac1ecfca5f62d091c381d", "NeedsCompilation": "yes", "Title": "An R package for analysis of case-control studies in genetic epidemiology", "Description": "An R package for analysis of case-control studies in genetic epidemiology.", "biocViews": [ "Clustering", "MultipleComparisons", "SNP", "Software" ], "Author": "Samsiddhi Bhattacharjee, Nilanjan Chatterjee, Summer Han and William Wheeler", "Maintainer": "William Wheeler ", "source.ver": "src/contrib/CGEN_3.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CGEN_3.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CGEN_3.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CGEN_3.10.0.tgz", "vignettes": [ "vignettes/CGEN/inst/doc/vignette_GxE.pdf", "vignettes/CGEN/inst/doc/vignette.pdf" ], "vignetteTitles": [ "CGEN Vignette", "CGEN Vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/CGEN/inst/doc/vignette_GxE.R", "vignettes/CGEN/inst/doc/vignette.R" ] }, "CGHbase": { "Package": "CGHbase", "Version": "1.34.0", "Depends": [ "R (>= 2.10)", "methods", "Biobase (>= 2.5.5)", "marray" ], "License": "GPL", "MD5sum": "a262b5d14abc5aade85e7f7f4ad68df2", "NeedsCompilation": "no", "Title": "CGHbase: Base functions and classes for arrayCGH data analysis.", "Description": "Contains functions and classes that are needed by arrayCGH packages.", "biocViews": [ "CopyNumberVariation", "Infrastructure", "Microarray", "Software" ], "Author": "Sjoerd Vosse, Mark van de Wiel", "Maintainer": "Mark van de Wiel ", "URL": "https://github.com/tgac-vumc/CGHbase", "BugReports": "https://github.com/tgac-vumc/CGHbase/issues", "source.ver": "src/contrib/CGHbase_1.34.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CGHbase_1.34.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CGHbase_1.34.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CGHbase_1.34.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "dependsOnMe": [ "CGHcall", "CGHnormaliter", "CGHregions", "GeneBreak", "sigaR" ], "importsMe": [ "CGHnormaliter", "plrs", "QDNAseq" ] }, "CGHcall": { "Package": "CGHcall", "Version": "2.36.0", "Depends": [ "R (>= 2.0.0)", "impute(>= 1.8.0)", "DNAcopy (>= 1.6.0)", "methods", "Biobase", "CGHbase (>= 1.15.1)", "snowfall" ], "License": "GPL (http://www.gnu.org/copyleft/gpl.html)", "MD5sum": "5f894c4a2fb24794fd149c4c8bcede00", "NeedsCompilation": "no", "Title": "Calling aberrations for array CGH tumor profiles.", "Description": "Calls aberrations for array CGH data using a six state mixture model as well as several biological concepts that are ignored by existing algorithms. Visualization of profiles is also provided.", "biocViews": [ "Microarray", "Preprocessing", "Software", "Visualization" ], "Author": "Mark van de Wiel, Sjoerd Vosse", "Maintainer": "Mark van de Wiel ", "source.ver": "src/contrib/CGHcall_2.36.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CGHcall_2.36.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CGHcall_2.36.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CGHcall_2.36.0.tgz", "vignettes": [ "vignettes/CGHcall/inst/doc/CGHcall.pdf" ], "vignetteTitles": [ "CGHcall" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CGHcall/inst/doc/CGHcall.R" ], "dependsOnMe": [ "CGHnormaliter", "focalCall", "GeneBreak" ], "importsMe": [ "CGHnormaliter", "QDNAseq" ], "suggestsMe": [ "sigaR" ] }, "cghMCR": { "Package": "cghMCR", "Version": "1.32.0", "Depends": [ "methods", "DNAcopy", "CNTools", "limma" ], "Imports": [ "BiocGenerics (>= 0.1.6)", "stats4" ], "License": "LGPL", "MD5sum": "a98a12d00a0fd1c65767ec7aad215bc6", "NeedsCompilation": "no", "Title": "Find chromosome regions showing common gains/losses", "Description": "This package provides functions to identify genomic regions of interests based on segmented copy number data from multiple samples.", "biocViews": [ "CopyNumberVariation", "Microarray", "Software" ], "Author": "J. Zhang and B. Feng", "Maintainer": "J. Zhang ", "source.ver": "src/contrib/cghMCR_1.32.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/cghMCR_1.32.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/cghMCR_1.32.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/cghMCR_1.32.0.tgz", "vignettes": [ "vignettes/cghMCR/inst/doc/findMCR.pdf" ], "vignetteTitles": [ "cghMCR findMCR" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/cghMCR/inst/doc/findMCR.R" ] }, "CGHnormaliter": { "Package": "CGHnormaliter", "Version": "1.28.0", "Depends": [ "CGHcall (>= 2.17.0)", "CGHbase (>= 1.15.0)" ], "Imports": [ "Biobase", "CGHbase", "CGHcall", "methods", "stats", "utils" ], "License": "GPL (>= 3)", "MD5sum": "3b717cdc24f4c96f27732f4637e1fa12", "NeedsCompilation": "no", "Title": "Normalization of array CGH data with imbalanced aberrations.", "Description": "Normalization and centralization of array comparative genomic hybridization (aCGH) data. The algorithm uses an iterative procedure that effectively eliminates the influence of imbalanced copy numbers. This leads to a more reliable assessment of copy number alterations (CNAs).", "biocViews": [ "Microarray", "Preprocessing", "Software" ], "Author": "Bart P.P. van Houte, Thomas W. Binsl, Hannes Hettling", "Maintainer": "Bart P.P. van Houte ", "source.ver": "src/contrib/CGHnormaliter_1.28.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CGHnormaliter_1.28.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CGHnormaliter_1.28.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CGHnormaliter_1.28.0.tgz", "vignettes": [ "vignettes/CGHnormaliter/inst/doc/CGHnormaliter.pdf" ], "vignetteTitles": [ "CGHnormaliter" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CGHnormaliter/inst/doc/CGHnormaliter.R" ] }, "CGHregions": { "Package": "CGHregions", "Version": "1.32.0", "Depends": [ "R (>= 2.0.0)", "methods", "Biobase", "CGHbase" ], "License": "GPL (http://www.gnu.org/copyleft/gpl.html)", "MD5sum": "9f73aa53b4706910c754d4e0ac5cd438", "NeedsCompilation": "no", "Title": "Dimension Reduction for Array CGH Data with Minimal Information Loss.", "Description": "Dimension Reduction for Array CGH Data with Minimal Information Loss", "biocViews": [ "CopyNumberVariation", "Microarray", "Software", "Visualization" ], "Author": "Sjoerd Vosse & Mark van de Wiel", "Maintainer": "Sjoerd Vosse ", "source.ver": "src/contrib/CGHregions_1.32.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CGHregions_1.32.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CGHregions_1.32.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CGHregions_1.32.0.tgz", "vignettes": [ "vignettes/CGHregions/inst/doc/CGHregions.pdf" ], "vignetteTitles": [ "CGHcall" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CGHregions/inst/doc/CGHregions.R" ], "suggestsMe": [ "ADaCGH2" ] }, "ChAMP": { "Package": "ChAMP", "Version": "2.6.4", "Depends": [ "R (>= 3.3)", "minfi", "ChAMPdata (>= 2.6.0)", "FEM (>= 3.1)", "DMRcate", "Illumina450ProbeVariants.db", "IlluminaHumanMethylationEPICmanifest" ], "Imports": [ "sva", "IlluminaHumanMethylation450kmanifest", "limma", "RPMM", "DNAcopy", "preprocessCore", "impute", "marray", "wateRmelon", "plyr", "goseq", "GenomicRanges", "RefFreeEWAS", "qvalue", "isva", "doParallel", "bumphunter", "quadprog", "shiny", "shinythemes", "plotly (>= 4.5.6)", "RColorBrewer", "dendextend", "matrixStats" ], "Suggests": [ "knitr", "rmarkdown" ], "License": "GPL-3", "MD5sum": "d457219a8550960881440f4a5f309ce8", "NeedsCompilation": "no", "Title": "Chip Analysis Methylation Pipeline for Illumina HumanMethylation450 and EPIC", "Description": "The package includes quality control metrics, a selection of normalization methods and novel methods to identify differentially methylated regions and to highlight copy number alterations.", "biocViews": [ "CopyNumber", "DNAMethylation", "MethylationArray", "Microarray", "Normalization", "Software", "TwoChannel" ], "Author": "Yuan Tian [cre,aut], Tiffany Morris [ctb], Lee Stirling [ctb], Andrew Feber [ctb], Andrew Teschendorff [ctb], Ankur Chakravarthy [ctb]", "Maintainer": "Yuan Tian ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/ChAMP_2.6.4.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ChAMP_2.6.4.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ChAMP_2.6.4.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ChAMP_2.6.4.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ChAMP/inst/doc/ChAMP.R" ], "htmlDocs": [ "vignettes/ChAMP/inst/doc/ChAMP.html" ], "htmlTitles": [ "ChAMP: The Chip Analysis Methylation Pipeline" ] }, "charm": { "Package": "charm", "Version": "2.20.0", "Depends": [ "R (>= 2.14.0)", "Biobase", "SQN", "fields", "RColorBrewer", "genefilter" ], "Imports": [ "BSgenome", "Biobase", "oligo (>= 1.11.31)", "oligoClasses(>= 1.17.39)", "ff", "preprocessCore", "methods", "stats", "Biostrings", "IRanges", "siggenes", "nor1mix", "gtools", "grDevices", "graphics", "utils", "limma", "parallel", "sva(>= 3.1.2)" ], "Suggests": [ "charmData", "BSgenome.Hsapiens.UCSC.hg18", "corpcor" ], "License": "LGPL (>= 2)", "MD5sum": "f07abc95197cfa50d86dd0aa599b2d56", "NeedsCompilation": "no", "Title": "Analysis of DNA methylation data from CHARM microarrays", "Description": "This package implements analysis tools for DNA methylation data generated using Nimblegen microarrays and the McrBC protocol. It finds differentially methylated regions between samples, calculates percentage methylation estimates and includes array quality assessment tools.", "biocViews": [ "DNAMethylation", "Microarray", "Software" ], "Author": "Martin Aryee, Peter Murakami, Harris Jaffee, Rafael Irizarry", "Maintainer": "Peter Murakami ", "source.ver": "src/contrib/charm_2.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/charm_2.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/charm_2.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/charm_2.20.0.tgz", "vignettes": [ "vignettes/charm/inst/doc/charm.pdf" ], "vignetteTitles": [ "charm Vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/charm/inst/doc/charm.R" ], "dependsOnMe": [ "charmData" ] }, "ChemmineOB": { "Package": "ChemmineOB", "Version": "1.12.0", "Depends": [ "R (>= 2.15.1)", "methods" ], "Imports": [ "BiocGenerics", "zlibbioc", "Rcpp (>= 0.11.0)" ], "LinkingTo": [ "BH", "Rcpp" ], "Suggests": [ "ChemmineR", "BiocStyle", "knitr", "knitcitations", "knitrBootstrap" ], "Enhances": [ "ChemmineR (>= 2.13.0)" ], "License": "file LICENSE", "Archs": "i386, x64", "MD5sum": "8e57220cd39c256edf683e6a05838080", "NeedsCompilation": "yes", "Title": "R interface to a subset of OpenBabel functionalities", "Description": "ChemmineOB provides an R interface to a subset of cheminformatics functionalities implemented by the OpelBabel C++ project. OpenBabel is an open source cheminformatics toolbox that includes utilities for structure format interconversions, descriptor calculations, compound similarity searching and more. ChemineOB aims to make a subset of these utilities available from within R. For non-developers, ChemineOB is primarily intended to be used from ChemmineR as an add-on package rather than used directly.", "biocViews": [ "BiomedicalInformatics", "CellBasedAssays", "Cheminformatics", "Clustering", "DataImport", "Infrastructure", "MicrotitrePlateAssay", "Pharmacogenetics", "Pharmacogenomics", "Proteomics", "Software", "Visualization" ], "Author": "Kevin Horan, Thomas Girke", "Maintainer": "Thomas Girke ", "URL": "https://github.com/girke-lab/ChemmineOB", "SystemRequirements": "OpenBabel (>= 2.3.1) with headers (http://openbabel.org).", "VignetteBuilder": "knitr", "source.ver": "src/contrib/ChemmineOB_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ChemmineOB_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ChemmineOB_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ChemmineOB_1.12.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": true, "hasLICENSE": true, "Rfiles": [ "vignettes/ChemmineOB/inst/doc/ChemmineOB.R" ], "htmlDocs": [ "vignettes/ChemmineOB/inst/doc/ChemmineOB.html" ], "htmlTitles": [ "ChemmineOB" ], "suggestsMe": [ "ChemmineR" ] }, "ChemmineR": { "Package": "ChemmineR", "Version": "2.26.1", "Depends": [ "R (>= 2.10.0)", "methods" ], "Imports": [ "rjson", "graphics", "stats", "RCurl", "DBI", "digest", "BiocGenerics", "Rcpp (>= 0.11.0)", "ggplot2" ], "LinkingTo": [ "Rcpp", "BH" ], "Suggests": [ "RSQLite", "scatterplot3d", "gplots", "fmcsR", "snow", "RPostgreSQL", "BiocStyle", "knitr", "knitcitations", "knitrBootstrap", "ChemmineOB (>= 1.3.8)", "ChemmineDrugs", "grid", "gridExtra", "png", "rmarkdown" ], "Enhances": [ "ChemmineOB" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "9506b97293cd1a9cff0c684a54d01fb5", "NeedsCompilation": "yes", "Title": "Cheminformatics Toolkit for R", "Description": "ChemmineR is a cheminformatics package for analyzing drug-like small molecule data in R. Its latest version contains functions for efficient processing of large numbers of molecules, physicochemical/structural property predictions, structural similarity searching, classification and clustering of compound libraries with a wide spectrum of algorithms. In addition, it offers visualization functions for compound clustering results and chemical structures.", "biocViews": [ "BiomedicalInformatics", "CellBasedAssays", "Cheminformatics", "Clustering", "DataImport", "Infrastructure", "MicrotitrePlateAssay", "Pharmacogenetics", "Pharmacogenomics", "Proteomics", "Software", "Visualization" ], "Author": "Y. Eddie Cao, Kevin Horan, Tyler Backman, Thomas Girke", "Maintainer": "Thomas Girke ", "URL": "https://github.com/girke-lab/ChemmineR", "SystemRequirements": "GNU make", "VignetteBuilder": "knitr", "source.ver": "src/contrib/ChemmineR_2.26.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ChemmineR_2.26.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ChemmineR_2.26.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ChemmineR_2.26.1.tgz", "hasREADME": true, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ChemmineR/inst/doc/ChemmineR.R" ], "htmlDocs": [ "vignettes/ChemmineR/inst/doc/ChemmineR.html" ], "htmlTitles": [ "ChemmineR" ], "dependsOnMe": [ "ChemmineDrugs", "eiR", "fmcsR", "PGPC" ], "importsMe": [ "bioassayR", "eiR", "fmcsR", "Rchemcpp", "Rcpi" ], "suggestsMe": [ "ChemmineOB" ] }, "Chicago": { "Package": "Chicago", "Version": "1.2.0", "Depends": [ "R (>= 3.2)", "data.table" ], "Imports": [ "matrixStats", "MASS", "Hmisc", "Delaporte", "methods", "grDevices", "graphics", "stats", "utils" ], "Suggests": [ "argparser", "BiocStyle", "knitr", "rmarkdown", "PCHiCdata", "testthat", "Rsamtools", "GenomicInteractions", "GenomicRanges", "IRanges", "AnnotationHub" ], "License": "Artistic-2.0", "MD5sum": "78fa42f33d5a730bcb6340309cc56f7e", "NeedsCompilation": "no", "Title": "CHiCAGO: Capture Hi-C Analysis of Genomic Organization", "Description": "A pipeline for analysing Capture Hi-C data.", "biocViews": [ "Epigenetics", "HiC", "Sequencing", "Software" ], "Author": "Jonathan Cairns, Paula Freire Pritchett, Steven Wingett, Mikhail Spivakov", "Maintainer": "Mikhail Spivakov ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/Chicago_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Chicago_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Chicago_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Chicago_1.2.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Chicago/inst/doc/Chicago.R" ], "htmlDocs": [ "vignettes/Chicago/inst/doc/Chicago.html" ], "htmlTitles": [ "CHiCAGO Vignette" ], "dependsOnMe": [ "PCHiCdata" ] }, "chimera": { "Package": "chimera", "Version": "1.16.0", "Depends": [ "Biobase", "GenomicRanges (>= 1.13.3)", "Rsamtools (>= 1.13.1)", "GenomicAlignments", "methods", "AnnotationDbi", "BSgenome.Hsapiens.UCSC.hg19", "TxDb.Hsapiens.UCSC.hg19.knownGene", "Homo.sapiens" ], "Suggests": [ "BiocParallel", "geneplotter" ], "Enhances": [ "Rsubread", "BSgenome.Mmusculus.UCSC.mm9", "TxDb.Mmusculus.UCSC.mm9.knownGene", "BSgenome.Mmusculus.UCSC.mm10", "TxDb.Mmusculus.UCSC.mm10.knownGene", "Mus.musculus", "BSgenome.Hsapiens.NCBI.GRCh38", "TxDb.Hsapiens.UCSC.hg38.knownGene" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "9a515d2e1f720db1a53c7645a3d1823d", "NeedsCompilation": "yes", "Title": "A package for secondary analysis of fusion products", "Description": "This package facilitates the characterisation of fusion products events. It allows to import fusion data results from the following fusion finders: chimeraScan, bellerophontes, deFuse, FusionFinder, FusionHunter, mapSplice, tophat-fusion, FusionMap, STAR, Rsubread, fusionCatcher.", "biocViews": [ "Infrastructure", "Software" ], "Author": "Raffaele A Calogero, Matteo Carrara, Marco Beccuti, Francesca Cordero", "Maintainer": "Raffaele A Calogero ", "SystemRequirements": "STAR, TopHat, bowtie and samtools are required for some functionalities", "source.ver": "src/contrib/chimera_1.16.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/chimera_1.16.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/chimera_1.16.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/chimera_1.16.0.tgz", "vignettes": [ "vignettes/chimera/inst/doc/chimera.pdf" ], "vignetteTitles": [ "chimera" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/chimera/inst/doc/chimera.R" ], "dependsOnMe": [ "oneChannelGUI" ] }, "ChIPComp": { "Package": "ChIPComp", "Version": "1.4.0", "Depends": [ "R (>= 3.2.0)", "GenomicRanges", "IRanges", "rtracklayer", "GenomeInfoDb", "S4Vectors" ], "Imports": [ "Rsamtools", "limma", "BSgenome.Hsapiens.UCSC.hg19", "BSgenome.Mmusculus.UCSC.mm9", "BiocGenerics" ], "Suggests": [ "BiocStyle", "RUnit" ], "License": "GPL", "Archs": "i386, x64", "MD5sum": "adfe34c38f4513f1c4f30d690690aab8", "NeedsCompilation": "yes", "Title": "Quantitative comparison of multiple ChIP-seq datasets", "Description": "ChIPComp detects differentially bound sharp binding sites across multiple conditions considering matching control.", "biocViews": [ "ChIPSeq", "Coverage", "DataImport", "Genetics", "MultipleComparison", "Sequencing", "Software", "Transcription" ], "Author": "Hao Wu, Li Chen, Zhaohui S.Qin, Chi Wang", "Maintainer": "Li Chen ", "source.ver": "src/contrib/ChIPComp_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ChIPComp_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ChIPComp_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ChIPComp_1.4.0.tgz", "vignettes": [ "vignettes/ChIPComp/inst/doc/ChIPComp.pdf" ], "vignetteTitles": [ "ChIPComp" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ChIPComp/inst/doc/ChIPComp.R" ] }, "chipenrich": { "Package": "chipenrich", "Version": "1.12.1", "Depends": [ "R (>= 3.1.0)" ], "Imports": [ "chipenrich.data", "GenomeInfoDb", "GenomicRanges", "grid", "IRanges", "lattice", "latticeExtra", "methods", "mgcv", "parallel", "plyr", "rms", "S4Vectors", "stringr" ], "Suggests": [ "BiocStyle", "devtools", "knitr", "rmarkdown", "roxygen2", "testthat" ], "License": "GPL-3", "MD5sum": "a9dd40d1d755fb8ff62d18857b8fae20", "NeedsCompilation": "no", "Title": "Gene Set Enrichment For ChIP-seq Peak Data", "Description": "ChIP-Enrich performs gene set enrichment testing using peaks called from a ChIP-seq experiment. The method empirically corrects for confounding factors such as the length of genes, and the mappability of the sequence surrounding genes.", "biocViews": [ "Bioinformatics", "Enrichment", "GeneSetEnrichment", "Software" ], "Author": "Ryan P. Welch [aut, cph], Chee Lee [aut], Raymond G. Cavalcante [aut, cre], Laura J. Scott [ths], Maureen A. Sartor [ths]", "Maintainer": "Raymond G. Cavalcante ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/chipenrich_1.12.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/chipenrich_1.12.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/chipenrich_1.12.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/chipenrich_1.12.1.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/chipenrich/inst/doc/chipenrich-vignette.R" ], "htmlDocs": [ "vignettes/chipenrich/inst/doc/chipenrich-vignette.html" ], "htmlTitles": [ "Vignette Title" ] }, "ChIPpeakAnno": { "Package": "ChIPpeakAnno", "Version": "3.8.9", "Depends": [ "R (>= 3.2)", "methods", "grid", "IRanges (>= 2.5.27)", "Biostrings", "GenomicRanges (>= 1.23.16)", "S4Vectors (>= 0.9.25)", "VennDiagram" ], "Imports": [ "BiocGenerics (>= 0.1.0)", "GO.db", "biomaRt", "BSgenome", "GenomicFeatures", "GenomeInfoDb", "matrixStats", "AnnotationDbi", "limma", "multtest", "RBGL", "graph", "BiocInstaller", "stats", "regioneR", "DBI", "ensembldb", "Biobase", "seqinr", "idr", "GenomicAlignments", "SummarizedExperiment", "Rsamtools" ], "Suggests": [ "reactome.db", "BSgenome.Ecoli.NCBI.20080805", "BSgenome.Hsapiens.UCSC.hg19", "org.Ce.eg.db", "org.Hs.eg.db", "BSgenome.Celegans.UCSC.ce10", "BSgenome.Drerio.UCSC.danRer7", "EnsDb.Hsapiens.v75", "EnsDb.Hsapiens.v79", "TxDb.Hsapiens.UCSC.hg19.knownGene", "TxDb.Hsapiens.UCSC.hg38.knownGene", "gplots", "BiocStyle", "rtracklayer", "knitr", "testthat", "trackViewer", "motifStack", "OrganismDbi" ], "License": "GPL (>= 2)", "MD5sum": "8acc2aac3e0055915667927ce53cb314", "NeedsCompilation": "no", "Title": "Batch annotation of the peaks identified from either ChIP-seq, ChIP-chip experiments or any experiments resulted in large number of chromosome ranges", "Description": "The package includes functions to retrieve the sequences around the peak, obtain enriched Gene Ontology (GO) terms, find the nearest gene, exon, miRNA or custom features such as most conserved elements and other transcription factor binding sites supplied by users. Starting 2.0.5, new functions have been added for finding the peaks with bi-directional promoters with summary statistics (peaksNearBDP), for summarizing the occurrence of motifs in peaks (summarizePatternInPeaks) and for adding other IDs to annotated peaks or enrichedGO (addGeneIDs). This package leverages the biomaRt, IRanges, Biostrings, BSgenome, GO.db, multtest and stat packages.", "biocViews": [ "Annotation", "ChIPSeq", "ChIPchip", "Software" ], "Author": "Lihua Julie Zhu, Jianhong Ou, Jun Yu, Herve Pages, Claude Gazin, Nathan Lawson, Ryan Thompson, Simon Lin, David Lapointe and Michael Green", "Maintainer": "Lihua Julie Zhu , Jianhong Ou ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/ChIPpeakAnno_3.8.9.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ChIPpeakAnno_3.8.9.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ChIPpeakAnno_3.8.9.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ChIPpeakAnno_3.8.9.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ChIPpeakAnno/inst/doc/ChIPpeakAnno.R", "vignettes/ChIPpeakAnno/inst/doc/pipeline.R", "vignettes/ChIPpeakAnno/inst/doc/quickStart.R" ], "htmlDocs": [ "vignettes/ChIPpeakAnno/inst/doc/ChIPpeakAnno.html", "vignettes/ChIPpeakAnno/inst/doc/pipeline.html", "vignettes/ChIPpeakAnno/inst/doc/quickStart.html" ], "htmlTitles": [ "ChIPpeakAnno Vignette", "ChIPpeakAnno Annotation Pipeline", "ChIPpeakAnno Quick Start" ], "dependsOnMe": [ "REDseq" ], "importsMe": [ "DChIPRep", "FunciSNP", "GUIDEseq", "REDseq" ], "suggestsMe": [ "oneChannelGUI", "R3CPET", "RIPSeeker" ] }, "ChIPQC": { "Package": "ChIPQC", "Version": "1.10.3", "Depends": [ "R (>= 3.0.0)", "ggplot2", "DiffBind", "GenomicRanges (>= 1.17.19)" ], "Imports": [ "BiocGenerics (>= 0.11.3)", "S4Vectors (>= 0.1.0)", "IRanges (>= 1.99.17)", "Rsamtools (>= 1.17.28)", "GenomicAlignments (>= 1.1.16)", "chipseq (>= 1.12.0)", "gtools", "BiocParallel", "methods", "reshape2", "Nozzle.R1", "Biobase", "grDevices", "stats", "utils", "GenomicFeatures", "TxDb.Hsapiens.UCSC.hg19.knownGene", "TxDb.Hsapiens.UCSC.hg18.knownGene", "TxDb.Mmusculus.UCSC.mm10.knownGene", "TxDb.Mmusculus.UCSC.mm9.knownGene", "TxDb.Hsapiens.UCSC.hg38.knownGene", "TxDb.Rnorvegicus.UCSC.rn4.ensGene", "TxDb.Celegans.UCSC.ce6.ensGene", "TxDb.Dmelanogaster.UCSC.dm3.ensGene" ], "Suggests": [ "BiocStyle" ], "License": "GPL (>= 3)", "MD5sum": "f6dcae1e75e32adf1ee800ab65b78e62", "NeedsCompilation": "no", "Title": "Quality metrics for ChIPseq data", "Description": "Quality metrics for ChIPseq data.", "biocViews": [ "ChIPSeq", "QualityControl", "ReportWriting", "Sequencing", "Software" ], "Author": "Tom Carroll, Wei Liu, Ines de Santiago, Rory Stark", "Maintainer": "Tom Carroll , Rory Stark ", "source.ver": "src/contrib/ChIPQC_1.10.3.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ChIPQC_1.10.3.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ChIPQC_1.10.3.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ChIPQC_1.10.3.tgz", "vignettes": [ "vignettes/ChIPQC/inst/doc/ChIPQC.pdf", "vignettes/ChIPQC/inst/doc/ChIPQCSampleReport.pdf" ], "vignetteTitles": [ "Assessing ChIP-seq sample quality with ChIPQC", "ChIPQCSampleReport.pdf" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ChIPQC/inst/doc/ChIPQC.R" ] }, "ChIPseeker": { "Package": "ChIPseeker", "Version": "1.10.3", "Depends": [ "R (>= 3.3.0)" ], "Imports": [ "AnnotationDbi", "BiocGenerics", "boot", "DOSE", "IRanges", "GenomeInfoDb", "GenomicRanges", "GenomicFeatures", "ggplot2 (>= 2.2.0)", "gplots", "graphics", "grDevices", "grid", "gridBase", "gtools", "methods", "plotrix", "dplyr", "parallel", "magrittr", "RColorBrewer", "rtracklayer", "S4Vectors (>= 0.9.25)", "stats", "TxDb.Hsapiens.UCSC.hg19.knownGene", "UpSetR", "utils" ], "Suggests": [ "clusterProfiler", "ReactomePA", "org.Hs.eg.db", "knitr", "BiocStyle", "rmarkdown", "testthat" ], "License": "Artistic-2.0", "MD5sum": "0df4a6b80103b0d51a991328c5028b8b", "NeedsCompilation": "no", "Title": "ChIPseeker for ChIP peak Annotation, Comparison, and Visualization", "Description": "This package implements functions to retrieve the nearest genes around the peak, annotate genomic region of the peak, statstical methods for estimate the significance of overlap among ChIP peak data sets, and incorporate GEO database for user to compare the own dataset with those deposited in database. The comparison can be used to infer cooperative regulation and thus can be used to generate hypotheses. Several visualization functions are implemented to summarize the coverage of the peak experiment, average profile and heatmap of peaks binding to TSS regions, genomic annotation, distance to TSS, and overlap of peaks or genes.", "biocViews": [ "Annotation", "ChIPSeq", "MultipleComparison", "Software", "Visualization" ], "Author": "Guangchuang Yu with contributions from Yun Yan, Herve Pages, Michael Kluge and Thomas Schwarzl.", "Maintainer": "Guangchuang Yu ", "URL": "https://guangchuangyu.github.io/ChIPseeker", "VignetteBuilder": "knitr", "BugReports": "https://github.com/GuangchuangYu/ChIPseeker/issues", "source.ver": "src/contrib/ChIPseeker_1.10.3.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ChIPseeker_1.10.3.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ChIPseeker_1.10.3.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ChIPseeker_1.10.3.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ChIPseeker/inst/doc/ChIPseeker.R" ], "htmlDocs": [ "vignettes/ChIPseeker/inst/doc/ChIPseeker.html" ], "htmlTitles": [ "ChIPseeker: an R package for ChIP peak Annotation, Comparison and Visualization" ] }, "chipseq": { "Package": "chipseq", "Version": "1.24.0", "Depends": [ "R (>= 2.10)", "methods", "BiocGenerics (>= 0.1.0)", "S4Vectors (>= 0.9.25)", "IRanges (>= 1.99.1)", "GenomicRanges (>= 1.17.7)", "ShortRead" ], "Imports": [ "methods", "stats", "lattice", "BiocGenerics", "IRanges", "GenomicRanges", "ShortRead" ], "Suggests": [ "BSgenome", "GenomicFeatures", "TxDb.Mmusculus.UCSC.mm9.knownGene" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "cd6d50d397fdcefc113ea188783347cf", "NeedsCompilation": "yes", "Title": "chipseq: A package for analyzing chipseq data", "Description": "Tools for helping process short read data for chipseq experiments", "biocViews": [ "ChIPSeq", "Coverage", "DataImport", "QualityControl", "Sequencing", "Software" ], "Author": "Deepayan Sarkar, Robert Gentleman, Michael Lawrence, Zizhen Yao", "Maintainer": "Bioconductor Package Maintainer ", "source.ver": "src/contrib/chipseq_1.24.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/chipseq_1.24.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/chipseq_1.24.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/chipseq_1.24.0.tgz", "vignettes": [ "vignettes/chipseq/inst/doc/Workflow.pdf" ], "vignetteTitles": [ "A Sample ChIP-Seq analysis workflow" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/chipseq/inst/doc/Workflow.R" ], "dependsOnMe": [ "PING" ], "importsMe": [ "ChIPQC", "CopywriteR", "HTSeqGenie", "soGGi", "transcriptR" ], "suggestsMe": [ "GenoGAM", "ggbio", "oneChannelGUI" ] }, "ChIPseqR": { "Package": "ChIPseqR", "Version": "1.28.0", "Depends": [ "R (>= 2.10.0)", "methods", "BiocGenerics", "S4Vectors (>= 0.9.25)" ], "Imports": [ "Biostrings", "fBasics", "GenomicRanges", "IRanges (>= 2.5.14)", "graphics", "grDevices", "HilbertVis", "ShortRead", "stats", "timsac", "utils" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "4baef922f50b1886e3ec605bfc80f82b", "NeedsCompilation": "yes", "Title": "Identifying Protein Binding Sites in High-Throughput Sequencing Data", "Description": "ChIPseqR identifies protein binding sites from ChIP-seq and nucleosome positioning experiments. The model used to describe binding events was developed to locate nucleosomes but should flexible enough to handle other types of experiments as well.", "biocViews": [ "ChIPSeq", "Infrastructure", "Software" ], "Author": "Peter Humburg", "Maintainer": "Peter Humburg ", "source.ver": "src/contrib/ChIPseqR_1.28.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ChIPseqR_1.28.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ChIPseqR_1.28.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ChIPseqR_1.28.0.tgz", "vignettes": [ "vignettes/ChIPseqR/inst/doc/Introduction.pdf" ], "vignetteTitles": [ "Introduction to ChIPseqR" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ChIPseqR/inst/doc/Introduction.R" ] }, "ChIPsim": { "Package": "ChIPsim", "Version": "1.28.0", "Depends": [ "Biostrings (>= 2.29.2)" ], "Imports": [ "IRanges", "XVector", "Biostrings", "ShortRead", "graphics", "methods", "stats", "utils" ], "Suggests": [ "actuar", "zoo" ], "License": "GPL (>= 2)", "MD5sum": "df47293f700bec0a0ddb202aca780b5c", "NeedsCompilation": "no", "Title": "Simulation of ChIP-seq experiments", "Description": "A general framework for the simulation of ChIP-seq data. Although currently focused on nucleosome positioning the package is designed to support different types of experiments.", "biocViews": [ "ChIPSeq", "Infrastructure", "Software" ], "Author": "Peter Humburg", "Maintainer": "Peter Humburg ", "source.ver": "src/contrib/ChIPsim_1.28.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ChIPsim_1.28.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ChIPsim_1.28.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ChIPsim_1.28.0.tgz", "vignettes": [ "vignettes/ChIPsim/inst/doc/ChIPsimIntro.pdf" ], "vignetteTitles": [ "Simulating ChIP-seq experiments" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ChIPsim/inst/doc/ChIPsimIntro.R" ] }, "ChIPXpress": { "Package": "ChIPXpress", "Version": "1.16.0", "Depends": [ "R (>= 2.10)", "ChIPXpressData" ], "Imports": [ "Biobase", "GEOquery", "frma", "affy", "bigmemory", "biganalytics" ], "Suggests": [ "mouse4302frmavecs", "mouse4302.db", "mouse4302cdf", "RUnit", "BiocGenerics" ], "License": "GPL(>=2)", "MD5sum": "7cdd1f61616ae752c547d316235eff0e", "NeedsCompilation": "no", "Title": "ChIPXpress: enhanced transcription factor target gene identification from ChIP-seq and ChIP-chip data using publicly available gene expression profiles", "Description": "ChIPXpress takes as input predicted TF bound genes from ChIPx data and uses a corresponding database of gene expression profiles downloaded from NCBI GEO to rank the TF bound targets in order of which gene is most likely to be functional TF target.", "biocViews": [ "ChIPSeq", "ChIPchip", "Software" ], "Author": "George Wu", "Maintainer": "George Wu ", "source.ver": "src/contrib/ChIPXpress_1.16.0.tar.gz", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ChIPXpress_1.16.0.tgz", "vignettes": [ "vignettes/ChIPXpress/inst/doc/ChIPXpress.pdf" ], "vignetteTitles": [ "ChIPXpress" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ChIPXpress/inst/doc/ChIPXpress.R" ] }, "chopsticks": { "Package": "chopsticks", "Version": "1.38.0", "Depends": [ "R(>= 2.10.0)", "survival", "methods" ], "Suggests": [ "hexbin" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "6340cd3f9c4ba39ac1197efd18373497", "NeedsCompilation": "yes", "Title": "The snp.matrix and X.snp.matrix classes", "Description": "Implements classes and methods for large-scale SNP association studies", "biocViews": [ "GeneticVariability", "Microarray", "SNP", "SNPsAndGeneticVariability", "Software" ], "Author": "Hin-Tak Leung ", "Maintainer": "Hin-Tak Leung ", "URL": "http://outmodedbonsai.sourceforge.net/", "source.ver": "src/contrib/chopsticks_1.38.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/chopsticks_1.38.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/chopsticks_1.38.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/chopsticks_1.38.0.tgz", "vignettes": [ "vignettes/chopsticks/inst/doc/chopsticks-vignette.pdf" ], "vignetteTitles": [ "snpMatrix" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/chopsticks/inst/doc/chopsticks-vignette.R" ] }, "chroGPS": { "Package": "chroGPS", "Version": "1.22.0", "Depends": [ "R (>= 3.1.0)", "GenomicRanges", "methods", "Biobase", "MASS", "graphics", "stats", "changepoint" ], "Imports": [ "cluster", "DPpackage", "ICSNP" ], "Enhances": [ "parallel", "XML", "rgl" ], "License": "GPL (>=2.14)", "MD5sum": "c772488eff7cc15dc83f4a321dd9cffd", "NeedsCompilation": "no", "Title": "chroGPS: visualizing the epigenome", "Description": "We provide intuitive maps to visualize the association between genetic elements, with emphasis on epigenetics. The approach is based on Multi-Dimensional Scaling. We provide several sensible distance metrics, and adjustment procedures to remove systematic biases typically observed when merging data obtained under different technologies or genetic backgrounds.", "biocViews": [ "Clustering", "Software", "Visualization" ], "Author": "Oscar Reina, David Rossell", "Maintainer": "Oscar Reina ", "source.ver": "src/contrib/chroGPS_1.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/chroGPS_1.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/chroGPS_1.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/chroGPS_1.22.0.tgz", "vignettes": [ "vignettes/chroGPS/inst/doc/chroGPS.pdf" ], "vignetteTitles": [ "Manual for the chroGPS library" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/chroGPS/inst/doc/chroGPS.R" ] }, "chromDraw": { "Package": "chromDraw", "Version": "2.4.0", "Depends": [ "R (>= 3.0.0)" ], "Imports": [ "Rcpp (>= 0.11.1)", "GenomicRanges (>= 1.17.46)" ], "LinkingTo": [ "Rcpp" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "328d1183bde0ca562853e58e3d9cce0a", "NeedsCompilation": "yes", "Title": "chromDraw is a R package for drawing the schemes of karyotypes in the linear and circular fashion.", "Description": "ChromDraw is a R package for drawing the schemes of karyotype(s) in the linear and circular fashion. It is possible to visualized cytogenetic marsk on the chromosomes. This tool has own input data format. Input data can be imported from the GenomicRanges data structure. This package can visualized the data in the BED file format. Here is requirement on to the first nine fields of the BED format. Output files format are *.eps and *.svg.", "biocViews": [ "Software" ], "Author": "Jan Janecka, Ing., Mgr. CEITEC Masaryk University", "Maintainer": "Jan Janecka ", "URL": "www.plantcytogenomics.org/chromDraw", "SystemRequirements": "Rtools (>= 3.1)", "source.ver": "src/contrib/chromDraw_2.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/chromDraw_2.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/chromDraw_2.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/chromDraw_2.4.0.tgz", "vignettes": [ "vignettes/chromDraw/inst/doc/chromDraw.pdf" ], "vignetteTitles": [ "chromDraw" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/chromDraw/inst/doc/chromDraw.R" ] }, "ChromHeatMap": { "Package": "ChromHeatMap", "Version": "1.28.0", "Depends": [ "R (>= 2.9.0)", "BiocGenerics (>= 0.3.2)", "annotate (>= 1.20.0)", "AnnotationDbi (>= 1.4.0)" ], "Imports": [ "Biobase (>= 2.17.8)", "graphics", "grDevices", "methods", "stats", "IRanges", "rtracklayer", "GenomicRanges" ], "Suggests": [ "ALL", "hgu95av2.db" ], "License": "Artistic-2.0", "MD5sum": "a410691c411d702c7e60249bdddabec5", "NeedsCompilation": "no", "Title": "Heat map plotting by genome coordinate", "Description": "The ChromHeatMap package can be used to plot genome-wide data (e.g. expression, CGH, SNP) along each strand of a given chromosome as a heat map. The generated heat map can be used to interactively identify probes and genes of interest.", "biocViews": [ "Software", "Visualization" ], "Author": "Tim F. Rayner", "Maintainer": "Tim F. Rayner ", "source.ver": "src/contrib/ChromHeatMap_1.28.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ChromHeatMap_1.28.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ChromHeatMap_1.28.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ChromHeatMap_1.28.0.tgz", "vignettes": [ "vignettes/ChromHeatMap/inst/doc/ChromHeatMap.pdf" ], "vignetteTitles": [ "Plotting expression data with ChromHeatMap" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ChromHeatMap/inst/doc/ChromHeatMap.R" ] }, "chromPlot": { "Package": "chromPlot", "Version": "1.2.0", "Depends": [ "stats", "utils", "graphics", "grDevices", "datasets", "base", "biomaRt", "GenomicRanges", "R (>= 3.3.0)" ], "Suggests": [ "qtl", "GenomicFeatures", "TxDb.Hsapiens.UCSC.hg19.knownGene" ], "License": "GPL (>= 2)", "MD5sum": "ba62f3df45d70d35f819b9afafa44471", "NeedsCompilation": "no", "Title": "Global visualization tool of genomic data", "Description": "Package designed to visualize genomic data along the chromosomes, where the vertical chromosomes are sorted by number, with sex chromosomes at the end.", "biocViews": [ "Annotation", "DataRepresentation", "FunctionalGenomics", "Genetics", "Sequencing", "Software", "Visualization" ], "Author": "Ricardo A. Verdugo and Karen Y. Orostica", "Maintainer": "Karen Y. Orostica ", "source.ver": "src/contrib/chromPlot_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/chromPlot_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/chromPlot_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/chromPlot_1.2.0.tgz", "vignettes": [ "vignettes/chromPlot/inst/doc/chromPlot.pdf" ], "vignetteTitles": [ "General Manual" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/chromPlot/inst/doc/chromPlot.R" ] }, "chromstaR": { "Package": "chromstaR", "Version": "1.0.0", "Depends": [ "R (>= 3.3)", "GenomicRanges", "ggplot2", "chromstaRData" ], "Imports": [ "methods", "utils", "grDevices", "graphics", "stats", "foreach", "doParallel", "S4Vectors", "GenomeInfoDb", "IRanges", "reshape2", "Rsamtools", "GenomicAlignments", "bamsignals" ], "Suggests": [ "knitr", "BiocStyle", "testthat", "biomaRt", "ggbio" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "024831787f34f6b379731e4aa74bcd30", "NeedsCompilation": "yes", "Title": "Combinatorial and Differential Chromatin State Analysis for ChIP-Seq Data", "Description": "This package implements functions for combinatorial and differential analysis of ChIP-seq data. It includes uni- and multivariate peak-calling, export to genome browser viewable files, and functions for enrichment analyses.", "biocViews": [ "ChIPSeq", "DifferentialPeakCalling", "HiddenMarkovModel", "MultipleComparison", "Software" ], "Author": "Aaron Taudt, Maria Colome Tatche, Matthias Heinig, Minh Anh Nguyen", "Maintainer": "Aaron Taudt ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/chromstaR_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/chromstaR_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/chromstaR_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/chromstaR_1.0.0.tgz", "vignettes": [ "vignettes/chromstaR/inst/doc/chromstaR.pdf" ], "vignetteTitles": [ "The chromstaR user's guide" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/chromstaR/inst/doc/chromstaR.R" ] }, "CHRONOS": { "Package": "CHRONOS", "Version": "1.2.1", "Depends": [ "R (>= 3.3)" ], "Imports": [ "XML", "RCurl", "RBGL", "parallel", "foreach", "doParallel", "openxlsx", "circlize", "graph", "stats", "utils", "grDevices", "graphics", "methods", "biomaRt" ], "Suggests": [ "RUnit", "BiocGenerics", "knitr" ], "License": "GPL-2", "MD5sum": "7014ac33228255020d607fae1e76f756", "NeedsCompilation": "no", "Title": "CHRONOS: A time-varying method for microRNA-mediated sub-pathway enrichment analysis", "Description": "A package used for efficient unraveling of the inherent dynamic properties of pathways. MicroRNA-mediated subpathway topologies are extracted and evaluated by exploiting the temporal transition and the fold change activity of the linked genes/microRNAs.", "biocViews": [ "GraphAndNetwork", "KEGG", "Pathways", "Software", "SystemsBiology" ], "Author": "Aristidis G. Vrahatis, Konstantina Dimitrakopoulou, Panos Balomenos", "Maintainer": "Panos Balomenos ", "SystemRequirements": "Java version >= 1.7, Pandoc", "VignetteBuilder": "knitr", "source.ver": "src/contrib/CHRONOS_1.2.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CHRONOS_1.2.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CHRONOS_1.2.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CHRONOS_1.2.1.tgz", "vignettes": [ "vignettes/CHRONOS/inst/doc/CHRONOS.pdf" ], "vignetteTitles": [ "CHRONOS" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CHRONOS/inst/doc/CHRONOS.R" ] }, "CINdex": { "Package": "CINdex", "Version": "1.2.0", "Depends": [ "R (>= 3.3)", "GenomicRanges" ], "Imports": [ "bitops", "gplots", "grDevices", "som", "dplyr", "gridExtra", "png", "stringr", "S4Vectors", "IRanges", "GenomeInfoDb", "graphics", "stats", "utils" ], "Suggests": [ "knitr", "testthat", "ReactomePA", "RUnit", "BiocGenerics", "AnnotationHub", "rtracklayer", "pd.genomewidesnp.6", "org.Hs.eg.db", "biovizBase", "TxDb.Hsapiens.UCSC.hg18.knownGene", "methods", "Biostrings", "Homo.sapiens" ], "License": "GPL (>= 2)", "MD5sum": "6dd48db4ba9d01f2efb03719cde3297a", "NeedsCompilation": "no", "Title": "Chromosome Instability Index", "Description": "The CINdex package addresses important area of high-throughput genomic analysis. It allows the automated processing and analysis of the experimental DNA copy number data generated by Affymetrix SNP 6.0 arrays or similar high throughput technologies. It calculates the chromosome instability (CIN) index that allows to quantitatively characterize genome-wide DNA copy number alterations as a measure of chromosomal instability. This package calculates not only overall genomic instability, but also instability in terms of copy number gains and losses separately at the chromosome and cytoband level.", "biocViews": [ "CopyNumberVariation", "Genetics", "GenomicVariation", "Microarray", "Sequencing", "Software", "aCGH" ], "Author": "Lei Song, Krithika Bhuvaneshwar, Yue Wang, Yuanjian Feng, Ie-Ming Shih, Subha Madhavan, Yuriy Gusev", "Maintainer": "Yuriy Gusev ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/CINdex_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CINdex_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CINdex_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CINdex_1.2.0.tgz", "vignettes": [ "vignettes/CINdex/inst/doc/CINdex.pdf", "vignettes/CINdex/inst/doc/PrepareInputData.pdf" ], "vignetteTitles": [ "CINdex Tutorial", "Prepare input data for CINdex" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CINdex/inst/doc/CINdex.R", "vignettes/CINdex/inst/doc/PrepareInputData.R" ] }, "cisPath": { "Package": "cisPath", "Version": "1.14.0", "Depends": [ "R (>= 2.10.0)" ], "Imports": [ "methods", "utils" ], "License": "GPL (>= 3)", "Archs": "i386, x64", "MD5sum": "b8fc816559633b363bb232bb2f11d357", "NeedsCompilation": "yes", "Title": "Visualization and management of the protein-protein interaction networks.", "Description": "cisPath is an R package that uses web browsers to visualize and manage protein-protein interaction networks.", "biocViews": [ "Proteomics", "Software" ], "Author": "Likun Wang ", "Maintainer": "Likun Wang ", "source.ver": "src/contrib/cisPath_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/cisPath_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/cisPath_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/cisPath_1.14.0.tgz", "vignettes": [ "vignettes/cisPath/inst/doc/cisPath.pdf" ], "vignetteTitles": [ "cisPath" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/cisPath/inst/doc/cisPath.R" ] }, "ClassifyR": { "Package": "ClassifyR", "Version": "1.8.2", "Depends": [ "R (>= 3.0.3)", "methods", "Biobase", "BiocParallel" ], "Imports": [ "locfit", "ROCR", "grid" ], "Suggests": [ "limma", "edgeR", "car", "Rmixmod", "ggplot2 (>= 2.0.0)", "gridExtra (>= 2.0.0)", "BiocStyle", "pamr", "sparsediscrim", "PoiClaClu", "curatedOvarianData", "parathyroidSE", "knitr", "klaR", "gtable", "scales", "e1071", "rmarkdown", "IRanges" ], "License": "GPL-3", "MD5sum": "55accbcf13d3b5117804ae33f3c02fd7", "NeedsCompilation": "no", "Title": "A framework for two-class classification problems, with applications to differential variability and differential distribution testing", "Description": "The software formalises a framework for classification in R. There are four stages; Data transformation, feature selection, classifier training, and prediction. The requirements of variable types and names are fixed, but specialised variables for functions can also be provided. The classification framework is wrapped in a driver loop, that reproducibly carries out a number of cross-validation schemes. Functions for differential expression, differential variability, and differential distribution are included. Additional functions may be developed by the user, by creating an interface to the framework.", "biocViews": [ "Classification", "Software", "Survival" ], "Author": "Dario Strbenac, John Ormerod, Graham Mann, Jean Yang", "Maintainer": "Dario Strbenac ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/ClassifyR_1.8.2.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ClassifyR_1.8.2.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ClassifyR_1.8.2.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ClassifyR_1.8.2.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ClassifyR/inst/doc/ClassifyR.R" ], "htmlDocs": [ "vignettes/ClassifyR/inst/doc/ClassifyR.html" ], "htmlTitles": [ "An Introduction to the ClassifyR Package" ] }, "cleanUpdTSeq": { "Package": "cleanUpdTSeq", "Version": "1.12.0", "Depends": [ "R (>= 2.15)", "BiocGenerics (>= 0.1.0)", "methods", "BSgenome", "BSgenome.Drerio.UCSC.danRer7", "GenomicRanges", "seqinr", "e1071" ], "Suggests": [ "BiocStyle", "knitr", "RUnit" ], "License": "GPL-2", "MD5sum": "5e11c1bc1f0404be819934ff03e80d3d", "NeedsCompilation": "no", "Title": "This package classifies putative polyadenylation sites as true or false/internally oligodT primed", "Description": "This package uses the Naive Bayes classifier (from e1071) to assign probability values to putative polyadenylation sites (pA sites) based on training data from zebrafish. This will allow the user to separate true, biologically relevant pA sites from false, oligodT primed pA sites.", "biocViews": [ "GeneRegulation", "Genetics", "SequenceMatching", "Sequencing", "Software" ], "Author": "Sarah Sheppard, Jianhong Ou, Nathan Lawson, Lihua Julie Zhu", "Maintainer": "Sarah Sheppard ; Jianhong Ou ; Lihua Julie Zhu ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/cleanUpdTSeq_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/cleanUpdTSeq_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/cleanUpdTSeq_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/cleanUpdTSeq_1.12.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/cleanUpdTSeq/inst/doc/cleanUpdTSeq.R" ], "htmlDocs": [ "vignettes/cleanUpdTSeq/inst/doc/cleanUpdTSeq.html" ], "htmlTitles": [ "cleanUpdTSeq Vignette" ], "importsMe": [ "InPAS" ] }, "cleaver": { "Package": "cleaver", "Version": "1.12.0", "Depends": [ "R (>= 3.0.0)", "methods", "Biostrings (>= 1.29.8)" ], "Imports": [ "S4Vectors", "IRanges" ], "Suggests": [ "testthat (>= 0.8)", "knitr", "BiocStyle (>= 0.0.14)", "BRAIN", "UniProt.ws (>= 2.1.4)" ], "License": "GPL (>= 3)", "MD5sum": "d8fa801e59ded7a600cbe1cf7b0ddd0f", "NeedsCompilation": "no", "Title": "Cleavage of Polypeptide Sequences", "Description": "In-silico cleavage of polypeptide sequences. The cleavage rules are taken from: http://web.expasy.org/peptide_cutter/peptidecutter_enzymes.html", "biocViews": [ "Proteomics", "Software" ], "Author": "Sebastian Gibb [aut, cre]", "Maintainer": "Sebastian Gibb ", "URL": "https://github.com/sgibb/cleaver/", "VignetteBuilder": "knitr", "BugReports": "https://github.com/sgibb/cleaver/issues/", "source.ver": "src/contrib/cleaver_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/cleaver_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/cleaver_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/cleaver_1.12.0.tgz", "vignettes": [ "vignettes/cleaver/inst/doc/cleaver.pdf" ], "vignetteTitles": [ "in-silico cleavage of polypeptides" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/cleaver/inst/doc/cleaver.R" ], "importsMe": [ "Pbase", "synapter" ] }, "clippda": { "Package": "clippda", "Version": "1.24.0", "Depends": [ "R (>= 2.13.1)", "limma", "statmod", "rgl", "lattice", "scatterplot3d", "graphics", "grDevices", "stats", "utils", "Biobase", "tools", "methods" ], "License": "GPL (>=2)", "MD5sum": "df8b6d42612f3e6d95f4cea4fe5b9a35", "NeedsCompilation": "no", "Title": "A package for the clinical proteomic profiling data analysis", "Description": "Methods for the nalysis of data from clinical proteomic profiling studies. The focus is on the studies of human subjects, which are often observational case-control by design and have technical replicates. A method for sample size determination for planning these studies is proposed. It incorporates routines for adjusting for the expected heterogeneities and imbalances in the data and the within-sample replicate correlations.", "biocViews": [ "DifferentialExpression", "MultipleComparison", "OneChannel", "Preprocessing", "Proteomics", "Software" ], "Author": "Stephen Nyangoma", "Maintainer": "Stephen Nyangoma ", "URL": "http://www.cancerstudies.bham.ac.uk/crctu/CLIPPDA.shtml", "source.ver": "src/contrib/clippda_1.24.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/clippda_1.24.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/clippda_1.24.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/clippda_1.24.0.tgz", "vignettes": [ "vignettes/clippda/inst/doc/clippda.pdf" ], "vignetteTitles": [ "Sample Size Calculation" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/clippda/inst/doc/clippda.R" ] }, "clipper": { "Package": "clipper", "Version": "1.14.0", "Depends": [ "R (>= 2.15.0)", "Matrix", "graph" ], "Imports": [ "methods", "Biobase", "Rcpp", "igraph", "gRbase (>= 1.6.6)", "qpgraph", "KEGGgraph", "corpcor", "RBGL" ], "Suggests": [ "RUnit", "BiocGenerics", "graphite", "ALL", "hgu95av2.db", "MASS", "BiocStyle" ], "Enhances": [ "RCytoscape (>= 1.6.3)" ], "License": "AGPL-3", "MD5sum": "7a35c13c74dc772d7b5565abe0378658", "NeedsCompilation": "no", "Title": "Gene Set Analysis Exploiting Pathway Topology", "Description": "Implements topological gene set analysis using a two-step empirical approach. It exploits graph decomposition theory to create a junction tree and reconstruct the most relevant signal path. In the first step clipper selects significant pathways according to statistical tests on the means and the concentration matrices of the graphs derived from pathway topologies. Then, it \"clips\" the whole pathway identifying the signal paths having the greatest association with a specific phenotype.", "Author": "Paolo Martini , Gabriele Sales , Chiara Romualdi ", "Maintainer": "Paolo Martini ", "source.ver": "src/contrib/clipper_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/clipper_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/clipper_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/clipper_1.14.0.tgz", "vignettes": [ "vignettes/clipper/inst/doc/clipper.pdf" ], "vignetteTitles": [ "clipper" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/clipper/inst/doc/clipper.R" ], "importsMe": [ "ToPASeq" ], "suggestsMe": [ "graphite" ], "biocViews": [ "Software" ] }, "Clomial": { "Package": "Clomial", "Version": "1.10.0", "Depends": [ "R (>= 2.10)", "matrixStats" ], "Imports": [ "methods", "permute" ], "License": "GPL (>= 2)", "MD5sum": "f1e81444b3ade7591a0951de8064be0b", "NeedsCompilation": "no", "Title": "Infers clonal composition of a tumor", "Description": "Clomial fits binomial distributions to counts obtained from Next Gen Sequencing data of multiple samples of the same tumor. The trained parameters can be interpreted to infer the clonal structure of the tumor.", "biocViews": [ "Bayesian", "Clustering", "DNASeq", "ExomeSeq", "GeneticVariability", "Genetics", "MultipleComparison", "Sequencing", "Software", "TargetedResequencing" ], "Author": "Habil Zare and Alex Hu", "Maintainer": "Habil Zare ", "source.ver": "src/contrib/Clomial_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Clomial_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Clomial_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Clomial_1.10.0.tgz", "vignettes": [ "vignettes/Clomial/inst/doc/Clonal_decomposition_by_Clomial.pdf" ], "vignetteTitles": [ "A likelihood maximization approach to infer the clonal structure of a cancer using multiple tumor samples" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Clomial/inst/doc/Clonal_decomposition_by_Clomial.R" ] }, "Clonality": { "Package": "Clonality", "Version": "1.22.0", "Depends": [ "R (>= 2.12.2)", "DNAcopy" ], "Imports": [ "DNAcopy", "grDevices", "graphics", "stats", "utils" ], "Suggests": [ "gdata", "DNAcopy" ], "License": "GPL-3", "MD5sum": "20fde8edcecb0e40993abff3cb00ee60", "NeedsCompilation": "no", "Title": "Clonality testing", "Description": "Statistical tests for clonality versus independence of tumors from the same patient based on their LOH or genomewide copy number profiles", "biocViews": [ "Classification", "CopyNumberVariation", "Microarray", "Software", "aCGH" ], "Author": "Irina Ostrovnaya", "Maintainer": "Irina Ostrovnaya ", "source.ver": "src/contrib/Clonality_1.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Clonality_1.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Clonality_1.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Clonality_1.22.0.tgz", "vignettes": [ "vignettes/Clonality/inst/doc/Clonality.pdf" ], "vignetteTitles": [ "Clonality" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Clonality/inst/doc/Clonality.R" ] }, "clonotypeR": { "Package": "clonotypeR", "Version": "1.12.0", "Imports": [ "methods" ], "Suggests": [ "BiocGenerics", "edgeR", "knitr", "pvclust", "RUnit", "vegan" ], "License": "file LICENSE", "MD5sum": "bb0d8d69d831dcd88619b20f617b8513", "NeedsCompilation": "no", "Title": "High throughput analysis of T cell antigen receptor sequences", "Description": "High throughput analysis of T cell antigen receptor sequences The genes encoding T cell receptors are created by somatic recombination, generating an immense combination of V, (D) and J segments. Additional processes during the recombination create extra sequence diversity between the V an J segments. Collectively, this hyper-variable region is called the CDR3 loop. The purpose of this package is to process and quantitatively analyse millions of V-CDR3-J combination, called clonotypes, from multiple sequence libraries.", "biocViews": [ "Sequencing", "Software" ], "Author": "Charles Plessy ", "Maintainer": "Charles Plessy ", "URL": "http://clonotyper.branchable.com/", "VignetteBuilder": "knitr", "BugReports": "http://clonotyper.branchable.com/Bugs/", "source.ver": "src/contrib/clonotypeR_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/clonotypeR_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/clonotypeR_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/clonotypeR_1.12.0.tgz", "hasREADME": true, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/clonotypeR/inst/doc/clonotypeR.R" ], "htmlDocs": [ "vignettes/clonotypeR/inst/doc/clonotypeR.html" ], "htmlTitles": [ "clonotypeR User's Guide" ] }, "clst": { "Package": "clst", "Version": "1.22.0", "Depends": [ "R (>= 2.10)" ], "Imports": [ "ROC", "lattice" ], "Suggests": [ "RUnit" ], "License": "GPL-3", "MD5sum": "bf42aba98440fe684a60c843beb3ccef", "NeedsCompilation": "no", "Title": "Classification by local similarity threshold", "Description": "Package for modified nearest-neighbor classification based on calculation of a similarity threshold distinguishing within-group from between-group comparisons.", "biocViews": [ "Classification", "Software" ], "Author": "Noah Hoffman", "Maintainer": "Noah Hoffman ", "source.ver": "src/contrib/clst_1.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/clst_1.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/clst_1.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/clst_1.22.0.tgz", "vignettes": [ "vignettes/clst/inst/doc/clstDemo.pdf" ], "vignetteTitles": [ "clst" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/clst/inst/doc/clstDemo.R" ], "dependsOnMe": [ "clstutils" ] }, "clstutils": { "Package": "clstutils", "Version": "1.22.0", "Depends": [ "R (>= 2.10)", "clst", "rjson", "ape" ], "Imports": [ "lattice", "RSQLite" ], "Suggests": [ "RUnit", "RSVGTipsDevice" ], "License": "GPL-3", "MD5sum": "752d7812932bb0e84b1b2da03c09e123", "NeedsCompilation": "no", "Title": "Tools for performing taxonomic assignment.", "Description": "Tools for performing taxonomic assignment based on phylogeny using pplacer and clst.", "biocViews": [ "Classification", "QualityControl", "Sequencing", "Software", "Visualization" ], "Author": "Noah Hoffman", "Maintainer": "Noah Hoffman ", "source.ver": "src/contrib/clstutils_1.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/clstutils_1.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/clstutils_1.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/clstutils_1.22.0.tgz", "vignettes": [ "vignettes/clstutils/inst/doc/pplacerDemo.pdf", "vignettes/clstutils/inst/doc/refSet.pdf" ], "vignetteTitles": [ "clst", "clstutils" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/clstutils/inst/doc/pplacerDemo.R", "vignettes/clstutils/inst/doc/refSet.R" ] }, "clustComp": { "Package": "clustComp", "Version": "1.2.2", "Depends": [ "R (>= 3.3)" ], "Imports": [ "sm", "stats", "graphics", "grDevices" ], "Suggests": [ "Biobase", "colonCA", "RUnit", "BiocGenerics" ], "License": "GPL (>= 2)", "MD5sum": "beb6505c21083f23ac21c3e6ca3bdd36", "NeedsCompilation": "no", "Title": "Clustering Comparison Package", "Description": "clustComp is a package that implements several techniques for the comparison and visualisation of relationships between different clustering results, either flat versus flat or hierarchical versus flat. These relationships among clusters are displayed using a weighted bi-graph, in which the nodes represent the clusters and the edges connect pairs of nodes with non-empty intersection; the weight of each edge is the number of elements in that intersection and is displayed through the edge thickness. The best layout of the bi-graph is provided by the barycentre algorithm, which minimises the weighted number of crossings. In the case of comparing a hierarchical and a non-hierarchical clustering, the dendrogram is pruned at different heights, selected by exploring the tree by depth-first search, starting at the root. Branches are decided to be split according to the value of a scoring function, that can be based either on the aesthetics of the bi-graph or on the mutual information between the hierarchical and the flat clusterings. A mapping between groups of clusters from each side is constructed with a greedy algorithm, and can be additionally visualised.", "biocViews": [ "Clustering", "GeneExpression", "Software", "Visualization" ], "Author": "Aurora Torrente and Alvis Brazma.", "Maintainer": "Aurora Torrente ", "source.ver": "src/contrib/clustComp_1.2.2.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/clustComp_1.2.2.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/clustComp_1.2.2.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/clustComp_1.2.2.tgz", "vignettes": [ "vignettes/clustComp/inst/doc/clustComp.pdf" ], "vignetteTitles": [ "The clustComp Package" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/clustComp/inst/doc/clustComp.R" ] }, "clusterExperiment": { "Package": "clusterExperiment", "Version": "1.0.0", "Depends": [ "R (>= 3.3)", "methods", "SummarizedExperiment" ], "Imports": [ "NMF", "RColorBrewer", "ape", "phylobase", "cluster", "stats", "limma", "dendextend", "howmany", "locfdr", "matrixStats", "graphics", "parallel" ], "Suggests": [ "BiocStyle", "knitr", "diagram", "testthat", "scRNAseq" ], "License": "Artistic-2.0", "MD5sum": "e1ff4062bea57e4d4c92aaa76dc3f107", "NeedsCompilation": "no", "Title": "Compare clusterings for single-cell sequencing", "Description": "This package provides functions for running and comparing many different clusterings of single-cell sequencing data.", "biocViews": [ "Clustering", "RNASeq", "Sequencing", "Software" ], "Author": "Elizabeth Purdom [aut, cre, cph], Davide Risso [aut], Marla Johnson [ctb]", "Maintainer": "Elizabeth Purdom ", "VignetteBuilder": "knitr", "BugReports": "https://github.com/epurdom/clusterExperiment/issues", "source.ver": "src/contrib/clusterExperiment_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/clusterExperiment_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/clusterExperiment_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/clusterExperiment_1.0.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/clusterExperiment/inst/doc/clusterExperimentTutorial.R" ], "htmlDocs": [ "vignettes/clusterExperiment/inst/doc/clusterExperimentTutorial.html" ], "htmlTitles": [ "clusterExperiment Vignette" ] }, "clusterProfiler": { "Package": "clusterProfiler", "Version": "3.2.14", "Depends": [ "R (>= 3.3.1)", "DOSE (>= 3.0.1)" ], "Imports": [ "AnnotationDbi", "ggplot2", "GO.db", "GOSemSim (>= 2.0.0)", "IRanges", "magrittr", "methods", "plyr", "qvalue", "stats", "stats4", "tidyr", "utils" ], "Suggests": [ "AnnotationHub", "BiocStyle", "GSEABase", "KEGG.db", "knitr", "org.Hs.eg.db", "pathview", "ReactomePA", "testthat", "topGO" ], "License": "Artistic-2.0", "MD5sum": "38b8a427cfcdbb328a2aa1284cc11db9", "NeedsCompilation": "no", "Title": "statistical analysis and visualization of functional profiles for genes and gene clusters", "Description": "This package implements methods to analyze and visualize functional profiles (GO and KEGG) of gene and gene clusters.", "biocViews": [ "Annotation", "Clustering", "GO", "GeneSetEnrichment", "KEGG", "MultipleComparison", "Pathways", "Reactome", "Software", "Visualization" ], "Author": "Guangchuang Yu [aut, cre], Li-Gen Wang [ctb], Giovanni Dall'Olio [ctb] (formula interface of compareCluster)", "Maintainer": "Guangchuang Yu ", "URL": "https://guangchuangyu.github.io/clusterProfiler", "VignetteBuilder": "knitr", "BugReports": "https://github.com/GuangchuangYu/clusterProfiler/issues", "source.ver": "src/contrib/clusterProfiler_3.2.14.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/clusterProfiler_3.2.14.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/clusterProfiler_3.2.14.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/clusterProfiler_3.2.14.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/clusterProfiler/inst/doc/clusterProfiler.R" ], "htmlDocs": [ "vignettes/clusterProfiler/inst/doc/clusterProfiler.html" ], "htmlTitles": [ "Statistical analysis and visualization of functional profiles for genes and gene clusters" ], "importsMe": [ "bioCancer", "debrowser", "eegc", "LINC", "MoonlightR", "TCGAbiolinks" ], "suggestsMe": [ "ChIPseeker", "DOSE", "GOSemSim", "isomiRs", "ReactomePA" ] }, "ClusterSignificance": { "Package": "ClusterSignificance", "Version": "1.2.3", "Depends": [ "R (>= 3.3.0)" ], "Imports": [ "methods", "pracma", "princurve", "scatterplot3d", "RColorBrewer", "grDevices", "graphics", "utils" ], "Suggests": [ "knitr", "rmarkdown", "testthat", "BiocStyle", "ggplot2", "plsgenomics" ], "License": "GPL-3", "MD5sum": "57e998961417f061bbd34bfa92b38494", "NeedsCompilation": "no", "Title": "The ClusterSignificance package provides tools to assess if clusters have a separation different from random or permuted data", "Description": "The ClusterSignificance package provides tools to assess if clusters have a separation different from random or permuted data. ClusterSignificance investigates clusters of two or more groups by first, projecting all points onto a one dimensional line. Cluster separations are then scored and the probability of the seen separation being due to chance is evaluated using a permutation method.", "biocViews": [ "Classification", "Clustering", "PrincipalComponent", "Software", "StatisticalMethod" ], "Author": "Jason T. Serviss and Jesper R. Gadin", "Maintainer": "Jason T Serviss ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/ClusterSignificance_1.2.3.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ClusterSignificance_1.2.3.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ClusterSignificance_1.2.3.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ClusterSignificance_1.2.3.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ClusterSignificance/inst/doc/ClusterSignificance-vignette.R" ], "htmlDocs": [ "vignettes/ClusterSignificance/inst/doc/ClusterSignificance-vignette.html" ], "htmlTitles": [ "ClusterSignificance Vignette" ] }, "clusterStab": { "Package": "clusterStab", "Version": "1.46.0", "Depends": [ "Biobase (>= 1.4.22)", "R (>= 1.9.0)", "methods" ], "Suggests": [ "fibroEset", "genefilter" ], "License": "Artistic-2.0", "MD5sum": "0098642e0e1b447ecdae1e02c26f6f59", "NeedsCompilation": "no", "Title": "Compute cluster stability scores for microarray data", "Description": "This package can be used to estimate the number of clusters in a set of microarray data, as well as test the stability of these clusters.", "biocViews": [ "Clustering", "Software" ], "Author": "James W. MacDonald, Debashis Ghosh, Mark Smolkin", "Maintainer": "James W. MacDonald ", "source.ver": "src/contrib/clusterStab_1.46.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/clusterStab_1.46.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/clusterStab_1.46.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/clusterStab_1.46.0.tgz", "vignettes": [ "vignettes/clusterStab/inst/doc/clusterStab.pdf" ], "vignetteTitles": [ "clusterStab Overview" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/clusterStab/inst/doc/clusterStab.R" ] }, "CMA": { "Package": "CMA", "Version": "1.32.0", "Depends": [ "R (>= 2.10)", "methods", "stats", "Biobase" ], "Suggests": [ "MASS", "class", "nnet", "glmnet", "e1071", "randomForest", "plsgenomics", "gbm", "mgcv", "corpcor", "limma", "st", "mvtnorm" ], "License": "GPL (>= 2)", "MD5sum": "4fba28d46a1f9581b2afd0d339cfd4d1", "NeedsCompilation": "no", "Title": "Synthesis of microarray-based classification", "Description": "This package provides a comprehensive collection of various microarray-based classification algorithms both from Machine Learning and Statistics. Variable Selection, Hyperparameter tuning, Evaluation and Comparison can be performed combined or stepwise in a user-friendly environment.", "biocViews": [ "Classification", "DecisionTree", "Software" ], "Author": "Martin Slawski , Anne-Laure Boulesteix , Christoph Bernau .", "Maintainer": "Christoph Bernau ", "source.ver": "src/contrib/CMA_1.32.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CMA_1.32.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CMA_1.32.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CMA_1.32.0.tgz", "vignettes": [ "vignettes/CMA/inst/doc/CMA_vignette.pdf" ], "vignetteTitles": [ "CMA_vignette.pdf" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CMA/inst/doc/CMA_vignette.R" ] }, "cn.farms": { "Package": "cn.farms", "Version": "1.22.0", "Depends": [ "R (>= 3.0)", "Biobase", "methods", "ff", "oligoClasses", "snow" ], "Imports": [ "DBI", "affxparser", "oligo", "DNAcopy", "preprocessCore", "lattice" ], "Suggests": [ "pd.mapping250k.sty", "pd.mapping250k.nsp", "pd.genomewidesnp.5", "pd.genomewidesnp.6" ], "License": "LGPL (>= 2.0)", "Archs": "i386, x64", "MD5sum": "4d6c6f3ef4383b4b36b99b3579478155", "NeedsCompilation": "yes", "Title": "cn.FARMS - factor analysis for copy number estimation", "Description": "This package implements the cn.FARMS algorithm for copy number variation (CNV) analysis. cn.FARMS allows to analyze the most common Affymetrix (250K-SNP6.0) array types, supports high-performance computing using snow and ff.", "biocViews": [ "CopyNumberVariation", "Microarray", "Software" ], "Author": "Andreas Mitterecker, Djork-Arne Clevert", "Maintainer": "Andreas Mitterecker ", "URL": "http://www.bioinf.jku.at/software/cnfarms/cnfarms.html", "source.ver": "src/contrib/cn.farms_1.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/cn.farms_1.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/cn.farms_1.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/cn.farms_1.22.0.tgz", "vignettes": [ "vignettes/cn.farms/inst/doc/cn.farms.pdf" ], "vignetteTitles": [ "cn.farms: Manual for the R package" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/cn.farms/inst/doc/cn.farms.R" ] }, "cn.mops": { "Package": "cn.mops", "Version": "1.20.1", "Depends": [ "R (>= 2.12)", "methods", "utils", "stats", "graphics", "parallel", "GenomicRanges" ], "Imports": [ "BiocGenerics", "Biobase", "IRanges", "Rsamtools", "GenomeInfoDb", "S4Vectors", "exomeCopy" ], "Suggests": [ "DNAcopy" ], "License": "LGPL (>= 2.0)", "Archs": "i386, x64", "MD5sum": "46e402c66248f84a0315dac5fe8c4b46", "NeedsCompilation": "yes", "Title": "cn.mops - Mixture of Poissons for CNV detection in NGS data", "Description": "cn.mops (Copy Number estimation by a Mixture Of PoissonS) is a data processing pipeline for copy number variations and aberrations (CNVs and CNAs) from next generation sequencing (NGS) data. The package supplies functions to convert BAM files into read count matrices or genomic ranges objects, which are the input objects for cn.mops. cn.mops models the depths of coverage across samples at each genomic position. Therefore, it does not suffer from read count biases along chromosomes. Using a Bayesian approach, cn.mops decomposes read variations across samples into integer copy numbers and noise by its mixture components and Poisson distributions, respectively. cn.mops guarantees a low FDR because wrong detections are indicated by high noise and filtered out. cn.mops is very fast and written in C++.", "biocViews": [ "CellBiology", "CopyNumberVariation", "Genetics", "HapMap", "Homo_sapiens", "Sequencing", "Software" ], "Author": "Guenter Klambauer", "Maintainer": "Guenter Klambauer ", "URL": "http://www.bioinf.jku.at/software/cnmops/cnmops.html", "source.ver": "src/contrib/cn.mops_1.20.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/cn.mops_1.20.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/cn.mops_1.20.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/cn.mops_1.20.1.tgz", "vignettes": [ "vignettes/cn.mops/inst/doc/cn.mops.pdf" ], "vignetteTitles": [ "cn.mops: Manual for the R package" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/cn.mops/inst/doc/cn.mops.R" ] }, "CNAnorm": { "Package": "CNAnorm", "Version": "1.20.0", "Depends": [ "R (>= 2.10.1)", "methods" ], "Imports": [ "DNAcopy" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "dfdd8543cd43f24a667624d83b086c81", "NeedsCompilation": "yes", "Title": "A normalization method for Copy Number Aberration in cancer samples", "Description": "Performs ratio, GC content correction and normalization of data obtained using low coverage (one read every 100-10,000 bp) high troughput sequencing. It performs a \"discrete\" normalization looking for the ploidy of the genome. It will also provide tumour content if at least two ploidy states can be found.", "biocViews": [ "CopyNumberVariation", "Coverage", "DNASeq", "GenomicVariation", "Normalization", "Sequencing", "Software", "WholeGenome" ], "Author": "Stefano Berri , Henry M. Wood , Arief Gusnanto ", "Maintainer": "Stefano Berri ", "URL": "http://www.r-project.org,", "source.ver": "src/contrib/CNAnorm_1.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CNAnorm_1.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CNAnorm_1.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CNAnorm_1.20.0.tgz", "vignettes": [ "vignettes/CNAnorm/inst/doc/CNAnorm.pdf" ], "vignetteTitles": [ "CNAnorm.pdf" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CNAnorm/inst/doc/CNAnorm.R" ] }, "CNEr": { "Package": "CNEr", "Version": "1.10.2", "Depends": [ "R (>= 3.2.2)" ], "Imports": [ "Biostrings (>= 2.33.4)", "RSQLite (>= 0.11.4)", "GenomeInfoDb (>= 1.1.3)", "GenomicRanges (>= 1.23.16)", "rtracklayer (>= 1.25.5)", "XVector (>= 0.5.4)", "GenomicAlignments (>= 1.1.9)", "methods", "S4Vectors (>= 0.9.25)", "IRanges (>= 2.5.27)", "readr (>= 0.2.2)", "BiocGenerics", "tools", "parallel", "reshape2 (>= 1.4.1)", "ggplot2 (>= 2.1.0)", "poweRlaw (>= 0.60.3)", "annotate (>= 1.50.0)", "GO.db (>= 3.3.0)", "R.utils (>= 2.3.0)", "KEGGREST (>= 1.14.0)" ], "LinkingTo": [ "S4Vectors", "IRanges", "XVector" ], "Suggests": [ "Gviz (>= 1.7.4)", "BiocStyle", "knitr", "rmarkdown", "testthat", "BSgenome.Drerio.UCSC.danRer10", "BSgenome.Hsapiens.UCSC.hg38", "TxDb.Drerio.UCSC.danRer10.refGene", "BSgenome.Hsapiens.UCSC.hg19", "BSgenome.Ggallus.UCSC.galGal3" ], "License": "GPL-2 | file LICENSE", "License_restricts_use": "yes", "Archs": "i386, x64", "MD5sum": "0e79fade0ec01e8f77a10a82e560f7f2", "NeedsCompilation": "yes", "Title": "CNE Detection and Visualization", "Description": "Large-scale identification and advanced visualization of sets of conserved noncoding elements.", "biocViews": [ "DataImport", "GeneRegulation", "Software", "Visualization" ], "Author": "Ge Tan ", "Maintainer": "Ge Tan ", "URL": "https://github.com/ge11232002/CNEr", "VignetteBuilder": "knitr", "BugReports": "https://github.com/ge11232002/CNEr/issues", "source.ver": "src/contrib/CNEr_1.10.2.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CNEr_1.10.2.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CNEr_1.10.2.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CNEr_1.10.2.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/CNEr/inst/doc/CNEr.R", "vignettes/CNEr/inst/doc/PairwiseWholeGenomeAlignment.R" ], "htmlDocs": [ "vignettes/CNEr/inst/doc/CNEr.html", "vignettes/CNEr/inst/doc/PairwiseWholeGenomeAlignment.html" ], "htmlTitles": [ "CNE identification and visualisation", "Pairwise whole genome alignment" ], "importsMe": [ "TFBSTools" ] }, "CNORdt": { "Package": "CNORdt", "Version": "1.16.0", "Depends": [ "R (>= 1.8.0)", "CellNOptR (>= 0.99)", "abind" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "4fc211110081666e2a778760698400e5", "NeedsCompilation": "yes", "Title": "Add-on to CellNOptR: Discretized time treatments", "Description": "This add-on to the package CellNOptR handles time-course data, as opposed to steady state data in CellNOptR. It scales the simulation step to allow comparison and model fitting for time-course data. Future versions will optimize delays and strengths for each edge.", "biocViews": [ "CellBasedAssays", "CellBiology", "Proteomics", "Software", "TimeCourse" ], "Author": "A. MacNamara", "Maintainer": "A. MacNamara ", "source.ver": "src/contrib/CNORdt_1.16.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CNORdt_1.16.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CNORdt_1.16.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CNORdt_1.16.0.tgz", "vignettes": [ "vignettes/CNORdt/inst/doc/CNORdt-vignette.pdf" ], "vignetteTitles": [ "Using multiple time points to train logic models to data" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CNORdt/inst/doc/CNORdt-vignette-example.R", "vignettes/CNORdt/inst/doc/CNORdt-vignette.R" ] }, "CNORfeeder": { "Package": "CNORfeeder", "Version": "1.14.0", "Depends": [ "R (>= 2.15.0)", "CellNOptR (>= 1.4.0)", "graph" ], "Suggests": [ "minet", "catnet", "Rgraphviz", "RUnit", "BiocGenerics", "igraph" ], "License": "GPL-3", "MD5sum": "a32ddd55226df0b674f433c4c247d6c6", "NeedsCompilation": "no", "Title": "Integration of CellNOptR to add missing links", "Description": "This package integrates literature-constrained and data-driven methods to infer signalling networks from perturbation experiments. It permits to extends a given network with links derived from the data via various inference methods and uses information on physical interactions of proteins to guide and validate the integration of links.", "biocViews": [ "Bioinformatics", "CellBasedAssays", "CellBiology", "NetworkInference", "Proteomics", "Software" ], "Author": "F.Eduati", "Maintainer": "F.Eduati ", "source.ver": "src/contrib/CNORfeeder_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CNORfeeder_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CNORfeeder_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CNORfeeder_1.14.0.tgz", "vignettes": [ "vignettes/CNORfeeder/inst/doc/CNORfeeder-vignette.pdf" ], "vignetteTitles": [ "Main vignette:Playing with networks using CNORfeeder" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CNORfeeder/inst/doc/CNORfeeder-vignette.R" ] }, "CNORfuzzy": { "Package": "CNORfuzzy", "Version": "1.16.0", "Depends": [ "R (>= 2.15.0)", "CellNOptR (>= 1.4.0)", "nloptr (>= 0.8.5)" ], "Suggests": [ "xtable", "Rgraphviz", "RUnit", "BiocGenerics" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "c13664b6f48addf37dfe7952ba601d92", "NeedsCompilation": "yes", "Title": "Addon to CellNOptR: Fuzzy Logic", "Description": "This package is an extension to CellNOptR. It contains additional functionality needed to simulate and train a prior knowledge network to experimental data using constrained fuzzy logic (cFL, rather than Boolean logic as is the case in CellNOptR). Additionally, this package will contain functions to use for the compilation of multiple optimization results (either Boolean or cFL).", "biocViews": [ "Network", "Software" ], "Author": "M. Morris, T. Cokelaer", "Maintainer": "T. Cokelaer ", "source.ver": "src/contrib/CNORfuzzy_1.16.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CNORfuzzy_1.16.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CNORfuzzy_1.16.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CNORfuzzy_1.16.0.tgz", "vignettes": [ "vignettes/CNORfuzzy/inst/doc/CNORfuzzy-vignette.pdf" ], "vignetteTitles": [ "Main vignette:Playing with networks using CNORfuzzyl" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CNORfuzzy/inst/doc/CNORfuzzy-vignette.R" ] }, "CNORode": { "Package": "CNORode", "Version": "1.16.0", "Depends": [ "CellNOptR (>= 1.5.14)", "genalg" ], "Enhances": [ "MEIGOR" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "5de4d1e324f86bd45fba8dcc73b8501a", "NeedsCompilation": "yes", "Title": "ODE add-on to CellNOptR", "Description": "ODE add-on to CellNOptR", "biocViews": [ "Bioinformatics", "CellBasedAssays", "CellBiology", "Proteomics", "Software", "TimeCourse" ], "Author": "David Henriques, Thomas Cokelaer", "Maintainer": "David Henriques ", "source.ver": "src/contrib/CNORode_1.16.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CNORode_1.16.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CNORode_1.16.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CNORode_1.16.0.tgz", "vignettes": [ "vignettes/CNORode/inst/doc/CNORode-vignette.pdf" ], "vignetteTitles": [ "Main vignette:Playing with networks using CNORode" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CNORode/inst/doc/CNORode-vignette.R" ], "dependsOnMe": [ "MEIGOR" ] }, "CNPBayes": { "Package": "CNPBayes", "Version": "1.4.0", "Depends": [ "GenomicRanges" ], "Imports": [ "Rcpp (>= 0.12.1)", "S4Vectors (>= 0.9.25)", "matrixStats", "RColorBrewer", "gtools", "combinat", "IRanges", "GenomeInfoDb", "GenomicRanges", "methods", "BiocGenerics", "graphics", "stats", "coda", "SummarizedExperiment" ], "LinkingTo": [ "Rcpp" ], "Suggests": [ "testthat", "knitr", "BiocStyle", "VanillaICE (>= 1.31.3)", "BiocCheck", "MASS", "oligoClasses", "dplyr", "tidyr", "ggplot2" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "7ebaa8830d51679d10f403949df193b3", "NeedsCompilation": "yes", "Title": "Bayesian mixture models for copy number polymorphisms", "Description": "Bayesian hierarchical mixture models for batch effects and copy number.", "biocViews": [ "Bayesian", "CopyNumberVariation", "Software" ], "Author": "Stephen Cristiano, Robert Scharpf, and Jacob Carey", "Maintainer": "Jacob Carey ", "URL": "https://github.com/scristia/CNPBayes", "VignetteBuilder": "knitr", "BugReports": "https://github.com/scristia/CNPBayes/issues", "source.ver": "src/contrib/CNPBayes_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CNPBayes_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CNPBayes_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CNPBayes_1.4.0.tgz", "vignettes": [ "vignettes/CNPBayes/inst/doc/Convergence.pdf", "vignettes/CNPBayes/inst/doc/FindCNPs.pdf", "vignettes/CNPBayes/inst/doc/Implementation.pdf", "vignettes/CNPBayes/inst/doc/Overview.pdf" ], "vignetteTitles": [ "Overview of CNPBayes package", "Identifying Copy Number Polymorphisms", "Implementation of Bayesian mixture models for copy number estimation", "Overview of CNPBayes package" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CNPBayes/inst/doc/Convergence.R", "vignettes/CNPBayes/inst/doc/FindCNPs.R", "vignettes/CNPBayes/inst/doc/Implementation.R", "vignettes/CNPBayes/inst/doc/Overview.R" ] }, "CNTools": { "Package": "CNTools", "Version": "1.30.0", "Depends": [ "R (>= 2.10)", "methods", "tools", "stats", "genefilter" ], "License": "LGPL", "Archs": "i386, x64", "MD5sum": "a9052ce33c3940b9a33c97051b76ba5e", "NeedsCompilation": "yes", "Title": "Convert segment data into a region by sample matrix to allow for other high level computational analyses.", "Description": "This package provides tools to convert the output of segmentation analysis using DNAcopy to a matrix structure with overlapping segments as rows and samples as columns so that other computational analyses can be applied to segmented data", "biocViews": [ "CopyNumberVariation", "Microarray", "Software" ], "Author": "Jianhua Zhang", "Maintainer": "J. Zhang ", "source.ver": "src/contrib/CNTools_1.30.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CNTools_1.30.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CNTools_1.30.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CNTools_1.30.0.tgz", "vignettes": [ "vignettes/CNTools/inst/doc/HowTo.pdf" ], "vignetteTitles": [ "NCTools HowTo" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CNTools/inst/doc/HowTo.R" ], "dependsOnMe": [ "cghMCR" ] }, "cnvGSA": { "Package": "cnvGSA", "Version": "1.18.0", "Depends": [ "brglm", "doParallel", "foreach", "GenomicRanges", "methods", "splitstackshape" ], "Suggests": [ "cnvGSAdata", "org.Hs.eg.db" ], "License": "LGPL", "MD5sum": "cf00997ded678ea2533ec1307107cf5a", "NeedsCompilation": "no", "Title": "Gene Set Analysis of (Rare) Copy Number Variants", "Description": "This package is intended to facilitate gene-set association with rare CNVs in case-control studies.", "biocViews": [ "MultipleComparison", "Software" ], "Author": "Daniele Merico , Robert Ziman ; packaged by Joseph Lugo ", "Maintainer": "Joseph Lugo ", "source.ver": "src/contrib/cnvGSA_1.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/cnvGSA_1.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/cnvGSA_1.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/cnvGSA_1.18.0.tgz", "vignettes": [ "vignettes/cnvGSA/inst/doc/cnvGSA-vignette.pdf", "vignettes/cnvGSA/inst/doc/cnvGSAUsersGuide.pdf" ], "vignetteTitles": [ "cnvGSA - Gene-Set Analysis of Rare Copy Number Variants", "cnvGSAUsersGuide.pdf" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "dependsOnMe": [ "cnvGSAdata" ] }, "CNVPanelizer": { "Package": "CNVPanelizer", "Version": "1.4.0", "Depends": [ "R (>= 3.2.0)", "GenomicRanges" ], "Imports": [ "S4Vectors", "grDevices", "stats", "utils", "NOISeq", "IRanges", "Rsamtools", "exomeCopy", "foreach", "ggplot2", "plyr", "openxlsx" ], "Suggests": [ "knitr", "RUnit", "BiocGenerics" ], "License": "GPL-3", "MD5sum": "5ad57f9092eca76a08c61bacb0433a04", "NeedsCompilation": "no", "Title": "Reliable CNV detection in targeted sequencing applications", "Description": "A method that allows for the use of a collection of non-matched normal tissue samples. Our approach uses a non-parametric bootstrap subsampling of the available reference samples to estimate the distribution of read counts from targeted sequencing. As inspired by random forest, this is combined with a procedure that subsamples the amplicons associated with each of the targeted genes. The obtained information allows us to reliably classify the copy number aberrations on the gene level.", "biocViews": [ "Classification", "CopyNumberVariation", "Coverage", "Normalization", "Sequencing", "Software" ], "Author": "Cristiano Oliveira [aut], Thomas Wolf [aut, cre], Albrecht Stenzinger [ctb], Volker Endris [ctb], Nicole Pfarr [ctb], Benedikt Brors [ths], Wilko Weichert [ths]", "Maintainer": "Thomas Wolf ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/CNVPanelizer_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CNVPanelizer_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CNVPanelizer_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CNVPanelizer_1.4.0.tgz", "vignettes": [ "vignettes/CNVPanelizer/inst/doc/CNVPanelizer.pdf" ], "vignetteTitles": [ "CNVPanelizer" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CNVPanelizer/inst/doc/CNVPanelizer.R" ] }, "CNVrd2": { "Package": "CNVrd2", "Version": "1.12.0", "Depends": [ "R (>= 3.0.0)", "methods", "VariantAnnotation", "parallel", "rjags", "ggplot2", "gridExtra" ], "Imports": [ "DNAcopy", "IRanges", "Rsamtools" ], "Suggests": [ "knitr" ], "License": "GPL-2", "MD5sum": "59526f3004247ee64b39a4937f0456fc", "NeedsCompilation": "no", "Title": "CNVrd2: a read depth-based method to detect and genotype complex common copy number variants from next generation sequencing data.", "Description": "CNVrd2 uses next-generation sequencing data to measure human gene copy number for multiple samples, indentify SNPs tagging copy number variants and detect copy number polymorphic genomic regions.", "biocViews": [ "Clustering.", "CopyNumberVariation", "Coverage", "LinkageDisequilibrium", "SNP", "Sequencing", "Software" ], "Author": "Hoang Tan Nguyen, Tony R Merriman and Mik Black", "Maintainer": "Hoang Tan Nguyen ", "URL": "https://github.com/hoangtn/CNVrd2", "VignetteBuilder": "knitr", "source.ver": "src/contrib/CNVrd2_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CNVrd2_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CNVrd2_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CNVrd2_1.12.0.tgz", "vignettes": [ "vignettes/CNVrd2/inst/doc/CNVrd2.pdf" ], "vignetteTitles": [ "A Markdown Vignette with knitr" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CNVrd2/inst/doc/CNVrd2.R" ] }, "CNVtools": { "Package": "CNVtools", "Version": "1.68.0", "Depends": [ "R (>= 2.10)", "survival" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "a30523d9d43b96859cd3d015a0c95748", "NeedsCompilation": "yes", "Title": "A package to test genetic association with CNV data", "Description": "This package is meant to facilitate the testing of Copy Number Variant data for genetic association, typically in case-control studies.", "biocViews": [ "GeneticVariability", "Software" ], "Author": "Chris Barnes and Vincent Plagnol ", "Maintainer": "Chris Barnes ", "source.ver": "src/contrib/CNVtools_1.68.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CNVtools_1.68.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CNVtools_1.68.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CNVtools_1.68.0.tgz", "vignettes": [ "vignettes/CNVtools/inst/doc/CNVtools-vignette.pdf" ], "vignetteTitles": [ "Copy Number Variation Tools" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CNVtools/inst/doc/CNVtools-vignette.R" ] }, "cobindR": { "Package": "cobindR", "Version": "1.12.0", "Imports": [ "methods", "seqinr", "yaml", "rtfbs", "gplots", "mclust", "gmp", "BiocGenerics (>= 0.13.8)", "IRanges", "Biostrings", "BSgenome", "biomaRt" ], "Suggests": [ "RUnit" ], "Enhances": [ "rGADEM", "seqLogo", "genoPlotR", "parallel", "VennDiagram", "RColorBrewer", "vcd", "MotifDb", "snowfall" ], "License": "Artistic-2.0", "MD5sum": "d28adcba6dd5daa892ed51c56f1767cb", "NeedsCompilation": "no", "Title": "Finding Co-occuring motifs of transcription factor binding sites", "Description": "Finding and analysing co-occuring motifs of transcription factor binding sites in groups of genes", "biocViews": [ "CellBiology", "ChIPSeq", "MultipleComparison", "SequenceMatching", "Software" ], "Author": "Manuela Benary, Stefan Kroeger, Yuehien Lee, Robert Lehmann", "Maintainer": "Manuela Benary ", "source.ver": "src/contrib/cobindR_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/cobindR_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/cobindR_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/cobindR_1.12.0.tgz", "vignettes": [ "vignettes/cobindR/inst/doc/cobindR.pdf" ], "vignetteTitles": [ "Using cobindR" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/cobindR/inst/doc/cobindR.R" ] }, "CoCiteStats": { "Package": "CoCiteStats", "Version": "1.46.0", "Depends": [ "R (>= 2.0)", "org.Hs.eg.db" ], "Imports": [ "AnnotationDbi" ], "License": "CPL", "MD5sum": "566885698b719fc8812aad55e323f00e", "NeedsCompilation": "no", "Title": "Different test statistics based on co-citation.", "Description": "A collection of software tools for dealing with co-citation data.", "biocViews": [ "Software" ], "Author": "B. Ding and R. Gentleman", "Maintainer": "Bioconductor Package Maintainer ", "source.ver": "src/contrib/CoCiteStats_1.46.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CoCiteStats_1.46.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CoCiteStats_1.46.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CoCiteStats_1.46.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false }, "codelink": { "Package": "codelink", "Version": "1.42.0", "Depends": [ "R (>= 2.10)", "BiocGenerics (>= 0.3.2)", "methods", "Biobase (>= 2.17.8)", "limma" ], "Imports": [ "annotate" ], "Suggests": [ "genefilter", "parallel", "knitr" ], "License": "GPL-2", "MD5sum": "34b8825065f3c4e0a20be3eb9cd41eaa", "NeedsCompilation": "no", "Title": "Manipulation of Codelink microarray data", "Description": "This package facilitates reading, preprocessing and manipulating Codelink microarray data. The raw data must be exported as text file using the Codelink software.", "biocViews": [ "DataImport", "Microarray", "OneChannel", "Preprocessing", "Software" ], "Author": "Diego Diez", "Maintainer": "Diego Diez ", "URL": "https://github.com/ddiez/codelink", "VignetteBuilder": "knitr", "BugReports": "https://github.com/ddiez/codelink/issues", "source.ver": "src/contrib/codelink_1.42.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/codelink_1.42.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/codelink_1.42.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/codelink_1.42.0.tgz", "vignettes": [ "vignettes/codelink/inst/doc/Codelink_Introduction.pdf", "vignettes/codelink/inst/doc/Codelink_Legacy.pdf" ], "vignetteTitles": [ "Codelink Intruction", "Codelink Legacy" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/codelink/inst/doc/Codelink_Introduction.R", "vignettes/codelink/inst/doc/Codelink_Legacy.R" ], "suggestsMe": [ "AgiMicroRna", "MAQCsubset" ] }, "CODEX": { "Package": "CODEX", "Version": "1.6.0", "Depends": [ "R (>= 3.2.3)", "Rsamtools", "GenomeInfoDb", "BSgenome.Hsapiens.UCSC.hg19", "IRanges", "Biostrings", "S4Vectors" ], "Suggests": [ "WES.1KG.WUGSC" ], "License": "GPL-2", "MD5sum": "dbf9171dbab45350c01cd653ff20523e", "NeedsCompilation": "no", "Title": "A Normalization and Copy Number Variation Detection Method for Whole Exome Sequencing", "Description": "A normalization and copy number variation calling procedure for whole exome DNA sequencing data. CODEX relies on the availability of multiple samples processed using the same sequencing pipeline for normalization, and does not require matched controls. The normalization model in CODEX includes terms that specifically remove biases due to GC content, exon length and targeting and amplification efficiency, and latent systemic artifacts. CODEX also includes a Poisson likelihood-based recursive segmentation procedure that explicitly models the count-based exome sequencing data.", "biocViews": [ "CopyNumberVariation", "ExomeSeq", "Normalization", "QualityControl", "Software" ], "Author": "Yuchao Jiang, Nancy R. Zhang", "Maintainer": "Yuchao Jiang ", "source.ver": "src/contrib/CODEX_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CODEX_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CODEX_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CODEX_1.6.0.tgz", "vignettes": [ "vignettes/CODEX/inst/doc/CODEX_vignettes.pdf" ], "vignetteTitles": [ "Using CODEX" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CODEX/inst/doc/CODEX_vignettes.R" ] }, "CoGAPS": { "Package": "CoGAPS", "Version": "2.8.0", "Depends": [ "R (>= 3.0.1)", "Rcpp (>= 0.11.2)" ], "Imports": [ "RColorBrewer (>= 1.0.5)", "gplots (>= 2.8.0)", "graphics", "grDevices", "methods", "stats", "utils" ], "LinkingTo": [ "Rcpp", "BH" ], "Suggests": [ "testthat", "lintr" ], "License": "GPL (==2)", "Archs": "i386, x64", "MD5sum": "2ff4ba8dee10ce106f9bdaf2d93ca6d4", "NeedsCompilation": "yes", "Title": "Coordinated Gene Activity in Pattern Sets", "Description": "Coordinated Gene Activity in Pattern Sets (CoGAPS) implements a Bayesian MCMC matrix factorization algorithm, GAPS, and links it to gene set statistic methods to infer biological process activity. It can be used to perform sparse matrix factorization on any data, and when this data represents biomolecules, to do gene set analysis.", "biocViews": [ "Bayesian", "Clustering", "DifferentialExpression", "DimensionReduction", "GeneExpression", "GeneSetEnrichment", "Microarray", "MultipleComparison", "RNASeq", "Software", "TimeCourse", "Transcription" ], "Author": "Elana J. Fertig, Michael F. Ochs", "Maintainer": "Elana J. Fertig ", "source.ver": "src/contrib/CoGAPS_2.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CoGAPS_2.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CoGAPS_2.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CoGAPS_2.8.0.tgz", "vignettes": [ "vignettes/CoGAPS/inst/doc/CoGAPSUsersManual.pdf" ], "vignetteTitles": [ "GAPS/CoGAPS Users Manual" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CoGAPS/inst/doc/CoGAPSUsersManual.R" ] }, "cogena": { "Package": "cogena", "Version": "1.8.0", "Depends": [ "R (>= 3.2)", "cluster", "ggplot2", "kohonen" ], "Imports": [ "methods", "class", "gplots", "mclust", "amap", "apcluster", "foreach", "parallel", "doParallel", "fastcluster", "corrplot", "biwt", "Biobase", "reshape2", "dplyr", "devtools" ], "Suggests": [ "knitr", "rmarkdown" ], "License": "LGPL-3", "MD5sum": "59baa763c180c819502310a55b93f066", "NeedsCompilation": "no", "Title": "co-expressed gene-set enrichment analysis", "Description": "cogena is a workflow for co-expressed gene-set enrichment analysis. It aims to discovery smaller scale, but highly correlated cellular events that may be of great biological relevance. A novel pipeline for drug discovery and drug repositioning based on the cogena workflow is proposed. Particularly, candidate drugs can be predicted based on the gene expression of disease-related data, or other similar drugs can be identified based on the gene expression of drug-related data. Moreover, the drug mode of action can be disclosed by the associated pathway analysis. In summary, cogena is a flexible workflow for various gene set enrichment analysis for co-expressed genes, with a focus on pathway/GO analysis and drug repositioning.", "biocViews": [ "Clustering", "DataImport", "DataRepresentation", "GO", "GeneExpression", "GeneSetEnrichment", "KEGG", "Microarray", "Pathways", "Sequencing", "Software", "SystemsBiology", "Visualization" ], "Author": "Zhilong Jia [aut, cre], Michael Barnes [aut]", "Maintainer": "Zhilong Jia ", "URL": "https://github.com/zhilongjia/cogena", "VignetteBuilder": "knitr", "BugReports": "https://github.com/zhilongjia/cogena/issues", "source.ver": "src/contrib/cogena_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/cogena_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/cogena_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/cogena_1.8.0.tgz", "vignettes": [ "vignettes/cogena/inst/doc/cogena-vignette_pdf.pdf" ], "vignetteTitles": [ "Vignette Title" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/cogena/inst/doc/cogena-vignette_html.R", "vignettes/cogena/inst/doc/cogena-vignette_pdf.R" ], "htmlDocs": [ "vignettes/cogena/inst/doc/cogena-vignette_html.html" ], "htmlTitles": [ "Vignette Title" ] }, "coGPS": { "Package": "coGPS", "Version": "1.18.0", "Depends": [ "R (>= 2.13.0)" ], "Imports": [ "graphics", "grDevices" ], "Suggests": [ "limma" ], "License": "GPL-2", "MD5sum": "ffd8772a69aec26ca01ab7a359cfbfd1", "NeedsCompilation": "no", "Title": "cancer outlier Gene Profile Sets", "Description": "Gene Set Enrichment Analysis of P-value based statistics for outlier gene detection in dataset merged from multiple studies", "biocViews": [ "DifferentialExpression", "Microarray", "Software" ], "Author": "Yingying Wei, Michael Ochs", "Maintainer": "Yingying Wei ", "source.ver": "src/contrib/coGPS_1.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/coGPS_1.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/coGPS_1.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/coGPS_1.18.0.tgz", "vignettes": [ "vignettes/coGPS/inst/doc/coGPS.pdf" ], "vignetteTitles": [ "coGPS" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/coGPS/inst/doc/coGPS.R" ] }, "COHCAP": { "Package": "COHCAP", "Version": "1.16.0", "Depends": [ "WriteXLS", "COHCAPanno", "RColorBrewer", "gplots" ], "License": "GPL-3", "MD5sum": "6d79339d2efe1c73a932507329ce307c", "NeedsCompilation": "no", "Title": "CpG Island Analysis Pipeline for Illumina Methylation Array and Targeted BS-Seq Data", "Description": "This package provides a pipeline to analyze single-nucleotide resolution methylation data (Illumina 450k/EPIC methylation array, targeted BS-Seq, etc.). It provides differential methylation for CpG Sites, differential methylation for CpG Islands, integration with gene expression data, with visualizaton options.", "biocViews": [ "DNAMethylation", "DifferentialMethylation", "Epigenetics", "MethylSeq", "Microarray", "Software" ], "Author": "Charles Warden", "Maintainer": "Charles Warden ", "SystemRequirements": "Perl", "source.ver": "src/contrib/COHCAP_1.16.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/COHCAP_1.16.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/COHCAP_1.16.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/COHCAP_1.16.0.tgz", "vignettes": [ "vignettes/COHCAP/inst/doc/COHCAP.pdf" ], "vignetteTitles": [ "COHCAP Vignette" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/COHCAP/inst/doc/COHCAP.R" ] }, "coMET": { "Package": "coMET", "Version": "1.6.0", "Depends": [ "R", "grid", "utils", "biomaRt", "Gviz", "psych", "ggbio", "trackViewer" ], "Imports": [ "colortools", "hash", "grDevices", "gridExtra", "rtracklayer", "IRanges", "S4Vectors", "GenomicRanges", "ggplot2", "stats", "corrplot" ], "Suggests": [ "knitr", "RUnit", "BiocGenerics", "BiocStyle" ], "License": "GPL (>= 2)", "MD5sum": "07b73acaa2ed110ab09a34190ec803f4", "NeedsCompilation": "no", "Title": "coMET: visualisation of regional epigenome-wide association scan (EWAS) results and DNA co-methylation patterns", "Description": "Visualisation of EWAS results in a genomic region. In addition to phenotype-association P-values, coMET also generates plots of co-methylation patterns and provides a series of annotation tracks. It can be used to other omic-wide association scans as long as the data can be translated to genomic level and for any species.", "biocViews": [ "ChIPSeq", "DNAMethylation", "DNASeq", "DifferentialMethylation", "ExomeSeq", "FunctionalGenomics", "Genetics", "GenomeWideAssociation", "MethylSeq", "MethylationArray", "Microarray", "RNASeq", "RiboSeq", "Sequencing", "Software", "Visualization" ], "Author": "Tiphaine C. Martin, Thomas Hardiman, Idil Yet, Pei-Chien Tsai, Jordana T. Bell", "Maintainer": "Tiphaine Martin ", "URL": "http://epigen.kcl.ac.uk/comet", "VignetteBuilder": "knitr", "source.ver": "src/contrib/coMET_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/coMET_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/coMET_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/coMET_1.6.0.tgz", "vignettes": [ "vignettes/coMET/inst/doc/coMET.pdf" ], "vignetteTitles": [ "coMET users guide" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/coMET/inst/doc/coMET.R" ] }, "COMPASS": { "Package": "COMPASS", "Version": "1.12.0", "Depends": [ "R (>= 3.0.2)" ], "Imports": [ "Rcpp", "data.table", "RColorBrewer", "scales", "grid", "plyr", "knitr", "abind", "clue", "grDevices", "utils", "pdist" ], "LinkingTo": [ "Rcpp (>= 0.11.0)" ], "Suggests": [ "flowWorkspace (>= 3.9.66)", "flowCore", "ncdfFlow", "shiny", "testthat", "devtools", "Kmisc", "flowWorkspaceData" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "584ec0ee477edcdaf95432968b0bc067", "NeedsCompilation": "yes", "Title": "Combinatorial Polyfunctionality Analysis of Single Cells", "Description": "COMPASS is a statistical framework that enables unbiased analysis of antigen-specific T-cell subsets. COMPASS uses a Bayesian hierarchical framework to model all observed cell-subsets and select the most likely to be antigen-specific while regularizing the small cell counts that often arise in multi-parameter space. The model provides a posterior probability of specificity for each cell subset and each sample, which can be used to profile a subject's immune response to external stimuli such as infection or vaccination.", "biocViews": [ "FlowCytometry", "Software" ], "Author": "Lynn Lin, Kevin Ushey, Greg Finak, Ravio Kolde (pheatmap)", "Maintainer": "Greg Finak ", "VignetteBuilder": "knitr", "BugReports": "https://github.com/RGLab/COMPASS/issues", "source.ver": "src/contrib/COMPASS_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/COMPASS_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/COMPASS_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/COMPASS_1.12.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/COMPASS/inst/doc/COMPASS.R" ], "htmlDocs": [ "vignettes/COMPASS/inst/doc/COMPASS.html" ], "htmlTitles": [ "COMPASS" ] }, "compcodeR": { "Package": "compcodeR", "Version": "1.10.0", "Depends": [ "R (>= 3.0.2)", "sm" ], "Imports": [ "tcltk", "knitr (>= 1.2)", "markdown", "ROCR", "lattice (>= 0.16)", "gplots", "gtools", "gdata", "caTools", "grid", "KernSmooth", "MASS", "ggplot2", "stringr", "modeest", "edgeR", "limma", "vioplot", "methods" ], "Suggests": [ "BiocStyle", "EBSeq", "DESeq", "DESeq2 (>= 1.1.31)", "baySeq (>= 2.2.0)", "genefilter", "NOISeq", "TCC", "samr", "NBPSeq (>= 0.3.0)" ], "Enhances": [ "rpanel", "DSS" ], "License": "GPL (>= 2)", "MD5sum": "d21c0960004e039c8f2c6254994c712e", "NeedsCompilation": "no", "Title": "RNAseq data simulation, differential expression analysis and performance comparison of differential expression methods", "Description": "This package provides extensive functionality for comparing results obtained by different methods for differential expression analysis of RNAseq data. It also contains functions for simulating count data and interfaces to several packages for performing the differential expression analysis.", "biocViews": [ "DifferentialExpression", "RNASeq", "Software" ], "Author": "Charlotte Soneson", "Maintainer": "Charlotte Soneson ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/compcodeR_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/compcodeR_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/compcodeR_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/compcodeR_1.10.0.tgz", "vignettes": [ "vignettes/compcodeR/inst/doc/compcodeR.pdf" ], "vignetteTitles": [ "compcodeR" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/compcodeR/inst/doc/compcodeR.R" ] }, "compEpiTools": { "Package": "compEpiTools", "Version": "1.8.0", "Depends": [ "R (>= 3.1.1)", "methods", "topGO", "GenomicRanges" ], "Imports": [ "AnnotationDbi", "BiocGenerics", "Biostrings", "Rsamtools", "parallel", "grDevices", "gplots", "IRanges", "GenomicFeatures", "XVector", "methylPipe", "GO.db", "S4Vectors", "GenomeInfoDb" ], "Suggests": [ "BSgenome.Mmusculus.UCSC.mm9", "TxDb.Mmusculus.UCSC.mm9.knownGene", "org.Mm.eg.db", "knitr", "rtracklayer" ], "License": "GPL", "MD5sum": "8ad65a79d0326cc6a257d3b6538a0c25", "NeedsCompilation": "no", "Title": "Tools for computational epigenomics", "Description": "Tools for computational epigenomics developed for the analysis, integration and simultaneous visualization of various (epi)genomics data types across multiple genomic regions in multiple samples.", "biocViews": [ "Coverage", "GeneExpression", "GenomeAnnotation", "Sequencing", "Software", "Visualization" ], "Author": "Mattia Pelizzola, Kamal Kishore", "Maintainer": "Kamal Kishore ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/compEpiTools_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/compEpiTools_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/compEpiTools_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/compEpiTools_1.8.0.tgz", "vignettes": [ "vignettes/compEpiTools/inst/doc/compEpiTools.pdf" ], "vignetteTitles": [ "compEpiTools.pdf" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/compEpiTools/inst/doc/compEpiTools.R" ] }, "CompGO": { "Package": "CompGO", "Version": "1.10.0", "Depends": [ "RDAVIDWebService" ], "Imports": [ "rtracklayer", "Rgraphviz", "ggplot2", "GenomicFeatures", "TxDb.Mmusculus.UCSC.mm9.knownGene", "pcaMethods", "reshape2", "pathview" ], "License": "GPL-2", "MD5sum": "deecec9f30a9ee83e710841e59d9948e", "NeedsCompilation": "no", "Title": "An R pipeline for .bed file annotation, comparing GO term enrichment between gene sets and data visualisation", "Description": "This package contains functions to accomplish several tasks. It is able to download full genome databases from UCSC, import .bed files easily, annotate these .bed file regions with genes (plus distance) from aforementioned database dumps, interface with DAVID to create functional annotation and gene ontology enrichment charts based on gene lists (such as those generated from input .bed files) and finally visualise and compare these enrichments using either directed acyclic graphs or scatterplots.", "biocViews": [ "GO", "GeneSetEnrichment", "MultipleComparison", "Software", "Visualization" ], "Author": "Sam D. Bassett [aut], Ashley J. Waardenberg [aut, cre]", "Maintainer": "Ashley J. Waardenberg ", "source.ver": "src/contrib/CompGO_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CompGO_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CompGO_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CompGO_1.10.0.tgz", "vignettes": [ "vignettes/CompGO/inst/doc/CompGO-Intro.pdf", "vignettes/CompGO/inst/doc/CompGO-vignette.pdf" ], "vignetteTitles": [ "Introduction", "CompGO-vignette.pdf" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CompGO/inst/doc/CompGO-Intro.R" ] }, "ComplexHeatmap": { "Package": "ComplexHeatmap", "Version": "1.12.0", "Depends": [ "R (>= 3.1.2)", "grid", "graphics", "stats", "grDevices" ], "Imports": [ "methods", "circlize (>= 0.3.4)", "GetoptLong", "colorspace", "RColorBrewer", "dendextend (>= 1.0.1)", "GlobalOptions (>= 0.0.10)" ], "Suggests": [ "testthat (>= 0.3)", "knitr", "markdown", "cluster", "MASS", "pvclust", "dendsort", "HilbertCurve", "Cairo", "png", "jpeg", "tiff", "fastcluster" ], "License": "GPL (>= 2)", "MD5sum": "37d323080bb0f454c83727f4e81a4c59", "NeedsCompilation": "no", "Title": "Making Complex Heatmaps", "Description": "Complex heatmaps are efficient to visualize associations between different sources of data sets and reveal potential structures. Here the ComplexHeatmap package provides a highly flexible way to arrange multiple heatmaps and supports self-defined annotation graphics.", "biocViews": [ "Sequencing", "Software", "Visualization" ], "Author": "Zuguang Gu", "Maintainer": "Zuguang Gu ", "URL": "https://github.com/jokergoo/ComplexHeatmap", "VignetteBuilder": "knitr", "source.ver": "src/contrib/ComplexHeatmap_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ComplexHeatmap_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ComplexHeatmap_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ComplexHeatmap_1.12.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ComplexHeatmap/inst/doc/s1.introduction.R", "vignettes/ComplexHeatmap/inst/doc/s2.single_heatmap.R", "vignettes/ComplexHeatmap/inst/doc/s3.a_list_of_heatmaps.R", "vignettes/ComplexHeatmap/inst/doc/s4.heatmap_annotation.R", "vignettes/ComplexHeatmap/inst/doc/s5.legend.R", "vignettes/ComplexHeatmap/inst/doc/s6.heatmap_decoration.R", "vignettes/ComplexHeatmap/inst/doc/s7.interactive.R", "vignettes/ComplexHeatmap/inst/doc/s8.oncoprint.R", "vignettes/ComplexHeatmap/inst/doc/s9.examples.R" ], "htmlDocs": [ "vignettes/ComplexHeatmap/inst/doc/s1.introduction.html", "vignettes/ComplexHeatmap/inst/doc/s2.single_heatmap.html", "vignettes/ComplexHeatmap/inst/doc/s3.a_list_of_heatmaps.html", "vignettes/ComplexHeatmap/inst/doc/s4.heatmap_annotation.html", "vignettes/ComplexHeatmap/inst/doc/s5.legend.html", "vignettes/ComplexHeatmap/inst/doc/s6.heatmap_decoration.html", "vignettes/ComplexHeatmap/inst/doc/s7.interactive.html", "vignettes/ComplexHeatmap/inst/doc/s8.oncoprint.html", "vignettes/ComplexHeatmap/inst/doc/s9.examples.html" ], "htmlTitles": [ "1. Introduction to ComplexHeatmap package", "2. Making a single heatmap", "3. Making a list of Heatmaps", "4. Heatmap Annotations", "5. Heatmap and Annotation Legends", "6. Heatmap Decoration", "7. Interactive with Heatmaps", "8. OncoPrint", "9. More Examples" ], "dependsOnMe": [ "EnrichedHeatmap", "recoup" ], "importsMe": [ "EnrichmentBrowser", "fCCAC", "maftools", "TCGAbiolinks", "YAPSA" ], "suggestsMe": [ "gtrellis", "HilbertCurve" ] }, "CONFESS": { "Package": "CONFESS", "Version": "1.2.2", "Depends": [ "R (>= 3.3)", "grDevices", "utils", "stats", "graphics" ], "Imports": [ "methods", "changepoint", "cluster", "contrast", "ecp", "EBImage", "flexmix", "flowCore", "flowClust", "flowMeans", "flowMerge", "flowPeaks", "foreach", "ggplot2", "grid", "limma", "MASS", "moments", "outliers", "parallel", "plotrix", "raster", "readbitmap", "reshape2", "SamSPECTRAL", "waveslim", "wavethresh", "zoo" ], "Suggests": [ "BiocStyle", "knitr", "rmarkdown", "CONFESSdata" ], "License": "GPL-2", "MD5sum": "86f89638e3d74e3f3badc51bf680c426", "NeedsCompilation": "no", "Title": "Cell OrderiNg by FluorEScence Signal", "Description": "Single Cell Fluidigm Spot Detector.", "biocViews": [ "CellBiology", "Classification", "Clustering", "DataImport", "GeneExpression", "QualityControl", "RNASeq", "Regression", "Software", "TimeCourse", "Visualization" ], "Author": "Diana LOW and Efthimios MOTAKIS", "Maintainer": "Diana LOW ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/CONFESS_1.2.2.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CONFESS_1.2.2.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CONFESS_1.2.2.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CONFESS_1.2.2.tgz", "vignettes": [ "vignettes/CONFESS/inst/doc/vignette_tex.pdf" ], "vignetteTitles": [ "CONFESS" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CONFESS/inst/doc/vignette_tex.R", "vignettes/CONFESS/inst/doc/vignette.R" ], "htmlDocs": [ "vignettes/CONFESS/inst/doc/vignette.html" ], "htmlTitles": [ "CONFESS" ] }, "ConsensusClusterPlus": { "Package": "ConsensusClusterPlus", "Version": "1.38.0", "Imports": [ "Biobase", "ALL", "graphics", "stats", "utils", "cluster" ], "License": "GPL version 2", "MD5sum": "03732e02d9aa4ab3676a0fd095456c4a", "NeedsCompilation": "no", "Title": "ConsensusClusterPlus", "Description": "algorithm for determining cluster count and membership by stability evidence in unsupervised analysis", "biocViews": [ "Clustering", "Software" ], "Author": "Matt Wilkerson , Peter Waltman ", "Maintainer": "Matt Wilkerson ", "source.ver": "src/contrib/ConsensusClusterPlus_1.38.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ConsensusClusterPlus_1.38.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ConsensusClusterPlus_1.38.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ConsensusClusterPlus_1.38.0.tgz", "vignettes": [ "vignettes/ConsensusClusterPlus/inst/doc/ConsensusClusterPlus.pdf" ], "vignetteTitles": [ "ConsensusClusterPlus Tutorial" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ConsensusClusterPlus/inst/doc/ConsensusClusterPlus.R" ], "dependsOnMe": [ "CVE" ], "importsMe": [ "CancerSubtypes", "DeSousa2013", "FlowSOM", "TCGAbiolinks" ] }, "consensusSeekeR": { "Package": "consensusSeekeR", "Version": "1.2.0", "Depends": [ "R (>= 2.10)", "BiocGenerics", "IRanges", "GenomicRanges", "BiocParallel" ], "Imports": [ "GenomeInfoDb", "rtracklayer", "stringr", "S4Vectors" ], "Suggests": [ "BiocStyle", "ggplot2", "knitr", "RUnit" ], "License": "Artistic-2.0", "MD5sum": "9a6e5e7b1baa46911d4c3c1bf36a51fb", "NeedsCompilation": "no", "Title": "Detection of consensus regions inside a group of experiences using genomic positions and genomic ranges", "Description": "This package compares genomic positions and genomic ranges from multiple experiments to extract common regions. The size of the analyzed region is adjustable as well as the number of experiences in which a feature must be present in a potential region to tag this region as a consensus region.", "biocViews": [ "BiologicalQuestion", "ChIPSeq", "Coverage", "Genetics", "MultipleComparison", "PeakDetection", "Sequencing", "Software", "Transcription" ], "Author": "Astrid Deschenes [cre, aut], Fabien Claude Lamaze [ctb], Pascal Belleau [aut], Arnaud Droit [aut]", "Maintainer": "Astrid Louise Deschenes ", "URL": "https://github.com/ArnaudDroitLab/consensusSeekeR", "VignetteBuilder": "knitr", "BugReports": "https://github.com/ArnaudDroitLab/consensusSeekeR/issues", "source.ver": "src/contrib/consensusSeekeR_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/consensusSeekeR_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/consensusSeekeR_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/consensusSeekeR_1.2.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/consensusSeekeR/inst/doc/consensusSeekeR.R" ], "htmlDocs": [ "vignettes/consensusSeekeR/inst/doc/consensusSeekeR.html" ], "htmlTitles": [ "Detection of consensus regions inside a group of experiences using genomic positions and genomic ranges" ] }, "contiBAIT": { "Package": "contiBAIT", "Version": "1.2.0", "Depends": [ "BH (>= 1.51.0-3)", "Rsamtools (>= 1.21)" ], "Imports": [ "grDevices", "clue", "cluster", "gplots", "IRanges", "GenomicRanges", "S4Vectors", "Rcpp", "TSP", "GenomicFiles", "gtools", "rtracklayer", "BiocParallel", "DNAcopy", "colorspace", "reshape2", "ggplot2", "methods", "exomeCopy", "GenomicAlignments", "diagram" ], "LinkingTo": [ "Rcpp", "BH" ], "Suggests": [ "BiocStyle" ], "License": "BSD_2_clause + file LICENSE", "Archs": "i386, x64", "MD5sum": "feede14611c4b08a2808ea3b1c30dcbc", "NeedsCompilation": "yes", "Title": "Improves Early Build Genome Assemblies using Strand-Seq Data", "Description": "Using strand inheritance data from multiple single cells from the organism whose genome is to be assembled, contiBAIT can cluster unbridged contigs together into putative chromosomes, and order the contigs within those chromosomes.", "biocViews": [ "CellBasedAssays", "Genetics", "GenomeAssembly", "QualityControl", "Software", "WholeGenome" ], "Author": "Kieran O'Neill, Mark Hills, Mike Gottlieb", "Maintainer": "Kieran O'Neill ", "source.ver": "src/contrib/contiBAIT_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/contiBAIT_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/contiBAIT_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/contiBAIT_1.2.0.tgz", "vignettes": [ "vignettes/contiBAIT/inst/doc/contiBAIT.pdf" ], "vignetteTitles": [ "flowBi" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/contiBAIT/inst/doc/contiBAIT.R" ] }, "conumee": { "Package": "conumee", "Version": "1.8.0", "Depends": [ "R (>= 3.0)", "minfi", "IlluminaHumanMethylation450kmanifest", "IlluminaHumanMethylation450kanno.ilmn12.hg19", "IlluminaHumanMethylationEPICmanifest", "IlluminaHumanMethylationEPICanno.ilm10b2.hg19" ], "Imports": [ "methods", "stats", "DNAcopy", "rtracklayer", "GenomicRanges", "IRanges", "GenomeInfoDb" ], "Suggests": [ "BiocStyle", "knitr", "rmarkdown", "minfiData", "CopyNumber450kData", "RCurl" ], "License": "GPL (>= 2)", "MD5sum": "7349b5d553ed43983b26131dd4773b38", "NeedsCompilation": "no", "Title": "Enhanced copy-number variation analysis using Illumina DNA methylation arrays", "Description": "This package contains a set of processing and plotting methods for performing copy-number variation (CNV) analysis using Illumina 450k or EPIC methylation arrays.", "biocViews": [ "CopyNumberVariation", "DNAMethylation", "MethylationArray", "Microarray", "Normalization", "Preprocessing", "QualityControl", "Software" ], "Author": "Volker Hovestadt, Marc Zapatka", "Maintainer": "Volker Hovestadt ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/conumee_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/conumee_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/conumee_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/conumee_1.8.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/conumee/inst/doc/conumee.R" ], "htmlDocs": [ "vignettes/conumee/inst/doc/conumee.html" ], "htmlTitles": [ "conumee" ] }, "convert": { "Package": "convert", "Version": "1.50.0", "Depends": [ "R (>= 2.6.0)", "Biobase (>= 1.15.33)", "limma (>= 1.7.0)", "marray", "utils", "methods" ], "License": "LGPL", "MD5sum": "43ff2b9dc8c9a3a60b9cf43796db9f36", "NeedsCompilation": "no", "Title": "Convert Microarray Data Objects", "Description": "Define coerce methods for microarray data objects.", "biocViews": [ "Infrastructure", "Microarray", "Software", "TwoChannel" ], "Author": "Gordon Smyth , James Wettenhall , Yee Hwa (Jean Yang) , Martin Morgan Martin Morgan", "Maintainer": "Yee Hwa (Jean) Yang ", "URL": "http://bioinf.wehi.edu.au/limma/convert.html", "source.ver": "src/contrib/convert_1.50.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/convert_1.50.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/convert_1.50.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/convert_1.50.0.tgz", "vignettes": [ "vignettes/convert/inst/doc/convert.pdf" ], "vignetteTitles": [ "Converting Between Microarray Data Classes" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "dependsOnMe": [ "maigesPack", "TurboNorm" ], "suggestsMe": [ "BiocCaseStudies", "dyebias", "dyebiasexamples", "OLIN" ] }, "copa": { "Package": "copa", "Version": "1.42.0", "Depends": [ "Biobase", "methods" ], "Suggests": [ "colonCA" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "1283a2711eb5a6497fbcd435c5279f4e", "NeedsCompilation": "yes", "Title": "Functions to perform cancer outlier profile analysis.", "Description": "COPA is a method to find genes that undergo recurrent fusion in a given cancer type by finding pairs of genes that have mutually exclusive outlier profiles.", "biocViews": [ "DifferentialExpression", "OneChannel", "Software", "TwoChannel", "Visualization" ], "Author": "James W. MacDonald", "Maintainer": "James W. MacDonald ", "source.ver": "src/contrib/copa_1.42.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/copa_1.42.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/copa_1.42.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/copa_1.42.0.tgz", "vignettes": [ "vignettes/copa/inst/doc/copa.pdf" ], "vignetteTitles": [ "copa Overview" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/copa/inst/doc/copa.R" ] }, "copynumber": { "Package": "copynumber", "Version": "1.14.0", "Depends": [ "R (>= 2.10)", "BiocGenerics" ], "Imports": [ "S4Vectors", "IRanges", "GenomicRanges" ], "License": "Artistic-2.0", "MD5sum": "447fcf9ccd7c90954acbafde47d06502", "NeedsCompilation": "no", "Title": "Segmentation of single- and multi-track copy number data by penalized least squares regression.", "Description": "Penalized least squares regression is applied to fit piecewise constant curves to copy number data to locate genomic regions of constant copy number. Procedures are available for individual segmentation of each sample, joint segmentation of several samples and joint segmentation of the two data tracks from SNP-arrays. Several plotting functions are available for visualization of the data and the segmentation results.", "biocViews": [ "CopyNumberVariation", "Genetics", "SNP", "Software", "Visualization", "aCGH" ], "Author": "Gro Nilsen, Knut Liestoel and Ole Christian Lingjaerde.", "Maintainer": "Gro Nilsen ", "source.ver": "src/contrib/copynumber_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/copynumber_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/copynumber_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/copynumber_1.14.0.tgz", "vignettes": [ "vignettes/copynumber/inst/doc/copynumber.pdf" ], "vignetteTitles": [ "copynumber.pdf" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/copynumber/inst/doc/copynumber.R" ] }, "CopywriteR": { "Package": "CopywriteR", "Version": "2.6.0", "Depends": [ "R(>= 3.2)", "BiocParallel" ], "Imports": [ "matrixStats", "gtools", "data.table", "S4Vectors", "chipseq", "IRanges", "Rsamtools", "DNAcopy", "GenomicAlignments", "GenomicRanges", "CopyhelpeR", "GenomeInfoDb", "futile.logger" ], "Suggests": [ "BiocStyle", "SCLCBam", "snow" ], "License": "GPL-2", "MD5sum": "23fbb9325433ba34157af8b996bc5875", "NeedsCompilation": "no", "Title": "Copy number information from targeted sequencing using off-target reads", "Description": "CopywriteR extracts DNA copy number information from targeted sequencing by utiizing off-target reads. It allows for extracting uniformly distributed copy number information, can be used without reference, and can be applied to sequencing data obtained from various techniques including chromatin immunoprecipitation and target enrichment on small gene panels. Thereby, CopywriteR constitutes a widely applicable alternative to available copy number detection tools.", "biocViews": [ "CopyNumberVariation", "Coverage", "ExomeSeq", "Preprocessing", "Software", "TargetedResequencing", "Visualization" ], "Author": "Thomas Kuilman", "Maintainer": "Thomas Kuilman ", "URL": "https://github.com/PeeperLab/CopywriteR", "source.ver": "src/contrib/CopywriteR_2.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CopywriteR_2.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CopywriteR_2.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CopywriteR_2.6.0.tgz", "vignettes": [ "vignettes/CopywriteR/inst/doc/CopywriteR.pdf" ], "vignetteTitles": [ "CopywriteR" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CopywriteR/inst/doc/CopywriteR.R" ] }, "CoRegNet": { "Package": "CoRegNet", "Version": "1.10.0", "Depends": [ "R (>= 2.14)", "igraph", "shiny", "arules", "methods" ], "Suggests": [ "RColorBrewer", "gplots", "BiocStyle", "knitr" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "294ee7778380521ef65396ec44a405b4", "NeedsCompilation": "yes", "Title": "CoRegNet : reconstruction and integrated analysis of co-regulatory networks", "Description": "This package provides methods to identify active transcriptional programs. Methods and classes are provided to import or infer large scale co-regulatory network from transcriptomic data. The specificity of the encoded networks is to model Transcription Factor cooperation. External regulation evidences (TFBS, ChIP,...) can be integrated to assess the inferred network and refine it if necessary. Transcriptional activity of the regulators in the network can be estimated using an measure of their influence in a given sample. Finally, an interactive UI can be used to navigate through the network of cooperative regulators and to visualize their activity in a specific sample or subgroup sample. The proposed visualization tool can be used to integrate gene expression, transcriptional activity, copy number status, sample classification and a transcriptional network including co-regulation information.", "biocViews": [ "GeneExpression", "GeneRegulation", "GraphAndNetwork", "Network", "NetworkEnrichment", "NetworkInference", "Software", "SystemsBiology", "Transcription", "Visualization" ], "Author": "Remy Nicolle, Thibault Venzac and Mohamed Elati", "Maintainer": "Remy Nicolle ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/CoRegNet_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CoRegNet_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CoRegNet_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CoRegNet_1.10.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CoRegNet/inst/doc/CoRegNet.R" ], "htmlDocs": [ "vignettes/CoRegNet/inst/doc/CoRegNet.html" ], "htmlTitles": [ "Custom Print Methods" ] }, "Cormotif": { "Package": "Cormotif", "Version": "1.20.0", "Depends": [ "R (>= 2.12.0)", "affy", "limma" ], "Imports": [ "affy", "graphics", "grDevices" ], "License": "GPL-2", "MD5sum": "d64b0c6d52e66b52f03820e56f243e69", "NeedsCompilation": "no", "Title": "Correlation Motif Fit", "Description": "It fits correlation motif model to multiple studies to detect study specific differential expression patterns.", "biocViews": [ "DifferentialExpression", "Microarray", "Software" ], "Author": "Hongkai Ji, Yingying Wei", "Maintainer": "Yingying Wei ", "source.ver": "src/contrib/Cormotif_1.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Cormotif_1.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Cormotif_1.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Cormotif_1.20.0.tgz", "vignettes": [ "vignettes/Cormotif/inst/doc/CormotifVignette.pdf" ], "vignetteTitles": [ "Cormotif Vignette" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Cormotif/inst/doc/CormotifVignette.R" ] }, "CorMut": { "Package": "CorMut", "Version": "1.16.0", "Depends": [ "seqinr", "igraph" ], "License": "GPL-2", "MD5sum": "b8b04a6db9e8c768a5a34fe72a38809f", "NeedsCompilation": "no", "Title": "Detect the correlated mutations based on selection pressure", "Description": "CorMut provides functions for computing kaks for individual sites or specific amino acids and detecting correlated mutations among them. Three methods are provided for detecting correlated mutations ,including conditional selection pressure, mutual information and Jaccard index. The computation consists of two steps: First, the positive selection sites are detected; Second, the mutation correlations are computed among the positive selection sites. Note that the first step is optional. Meanwhile, CorMut facilitates the comparison of the correlated mutations between two conditions by the means of correlated mutation network.", "biocViews": [ "Sequencing", "Software" ], "Author": "Zhenpeng Li, Yang Huang, Yabo Ouyang, Yiming Shao, Liying Ma", "Maintainer": "Zhenpeng Li", "source.ver": "src/contrib/CorMut_1.16.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CorMut_1.16.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CorMut_1.16.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CorMut_1.16.0.tgz", "vignettes": [ "vignettes/CorMut/inst/doc/CorMut.pdf" ], "vignetteTitles": [ "CorMut" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CorMut/inst/doc/CorMut.R" ] }, "coRNAi": { "Package": "coRNAi", "Version": "1.24.0", "Depends": [ "R (>= 2.10)", "cellHTS2", "limma", "locfit" ], "Imports": [ "MASS", "gplots", "lattice", "grDevices", "graphics", "stats" ], "License": "Artistic-2.0", "MD5sum": "64f6cc27d16eef412da3f3b6e80bf85d", "NeedsCompilation": "no", "Title": "Analysis of co-knock-down RNAi data", "Description": "Analysis of combinatorial cell-based RNAi screens", "biocViews": [ "CellBasedAssays", "Software" ], "Author": "Elin Axelsson", "Maintainer": "Elin Axelsson ", "SystemRequirements": "Graphviz", "source.ver": "src/contrib/coRNAi_1.24.0.tar.gz", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/coRNAi_1.24.0.tgz", "vignettes": [ "vignettes/coRNAi/inst/doc/coRNAi.pdf" ], "vignetteTitles": [ "coRNAi" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/coRNAi/inst/doc/coRNAi.R" ] }, "CORREP": { "Package": "CORREP", "Version": "1.40.0", "Imports": [ "e1071", "stats" ], "Suggests": [ "cluster", "MASS" ], "License": "GPL (>= 2)", "MD5sum": "6e496463b36437a946a912256d824447", "NeedsCompilation": "no", "Title": "Multivariate Correlation Estimator and Statistical Inference Procedures.", "Description": "Multivariate correlation estimation and statistical inference. See package vignette.", "biocViews": [ "Clustering", "GraphAndNetwork", "Microarray", "Software" ], "Author": "Dongxiao Zhu and Youjuan Li", "Maintainer": "Dongxiao Zhu ", "source.ver": "src/contrib/CORREP_1.40.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CORREP_1.40.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CORREP_1.40.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CORREP_1.40.0.tgz", "vignettes": [ "vignettes/CORREP/inst/doc/CORREP.pdf" ], "vignetteTitles": [ "Multivariate Correlation Estimator" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CORREP/inst/doc/CORREP.R" ] }, "cosmiq": { "Package": "cosmiq", "Version": "1.8.0", "Depends": [ "R (>= 3.0.2)", "Rcpp" ], "Imports": [ "pracma", "xcms", "MassSpecWavelet", "faahKO" ], "Suggests": [ "RUnit", "BiocGenerics", "BiocStyle" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "0d22a4b914eb75ec0d43708c2bb78730", "NeedsCompilation": "yes", "Title": "cosmiq - COmbining Single Masses Into Quantities", "Description": "cosmiq is a tool for the preprocessing of liquid- or gas - chromatography mass spectrometry (LCMS/GCMS) data with a focus on metabolomics or lipidomics applications. To improve the detection of low abundant signals, cosmiq generates master maps of the mZ/RT space from all acquired runs before a peak detection algorithm is applied. The result is a more robust identification and quantification of low-intensity MS signals compared to conventional approaches where peak picking is performed in each LCMS/GCMS file separately. The cosmiq package builds on the xcmsSet object structure and can be therefore integrated well with the package xcms as an alternative preprocessing step.", "biocViews": [ "MassSpectrometry", "Metabolomics", "Software" ], "Author": "David Fischer , Christian Panse , Endre Laczko ", "Maintainer": "David Fischer , Christian Panse ", "URL": "http://www.bioconductor.org/packages/devel/bioc/html/cosmiq.html", "source.ver": "src/contrib/cosmiq_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/cosmiq_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/cosmiq_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/cosmiq_1.8.0.tgz", "vignettes": [ "vignettes/cosmiq/inst/doc/cosmiq.pdf" ], "vignetteTitles": [ "cosmiq primer" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/cosmiq/inst/doc/cosmiq.R" ] }, "COSNet": { "Package": "COSNet", "Version": "1.8.0", "Suggests": [ "bionetdata", "PerfMeas", "RUnit", "BiocGenerics" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "e860018afbdfb721006455c562486ef7", "NeedsCompilation": "yes", "Title": "Cost Sensitive Network for node label prediction on graphs with highly unbalanced labelings", "Description": "Package that implements the COSNet classification algorithm. The algorithm predicts node labels in partially labeled graphs where few positives are available for the class being predicted.", "biocViews": [ "Classification", "GraphAndNetwork", "Network", "NeuralNetwork", "Software" ], "Author": "Marco Frasca and Giorgio Valentini -- Universita' degli Studi di Milano", "Maintainer": "Marco Frasca", "URL": "https://github.com/m1frasca/COSNet_GitHub", "source.ver": "src/contrib/COSNet_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/COSNet_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/COSNet_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/COSNet_1.8.0.tgz", "vignettes": [ "vignettes/COSNet/inst/doc/COSNet_v.pdf" ], "vignetteTitles": [ "An R Package for Predicting Binary Labels in Partially-Labeled Graphs" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/COSNet/inst/doc/COSNet_v.R" ] }, "CountClust": { "Package": "CountClust", "Version": "1.2.0", "Depends": [ "R (>= 3.3.0)", "ggplot2 (>= 2.1.0)" ], "Imports": [ "maptpx", "slam", "plyr(>= 1.7.1)", "cowplot", "gtools", "flexmix", "picante", "limma", "parallel", "reshape2", "stats", "utils", "graphics", "grDevices" ], "Suggests": [ "knitr", "BiocStyle", "Biobase", "roxygen2", "RColorBrewer", "devtools", "xtable" ], "License": "GPL (>= 2)", "MD5sum": "7f7ab6cd265c893d805127a86c64ef47", "NeedsCompilation": "no", "Title": "Clustering and Visualizing RNA-Seq Expression Data using Grade of Membership Models", "Description": "Fits grade of membership models (GoM, also known as admixture models) to cluster RNA-seq gene expression count data, identifies characteristic genes driving cluster memberships, and provides a visual summary of the cluster memberships.", "biocViews": [ "Clustering", "GeneExpression", "RNASeq", "Sequencing", "Software", "StatisticalMethod", "Visualization" ], "Author": "Kushal Dey [aut, cre], Joyce Hsiao [aut], Matthew Stephens [aut]", "Maintainer": "Kushal Dey ", "URL": "https://github.com/kkdey/CountClust", "VignetteBuilder": "knitr", "source.ver": "src/contrib/CountClust_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CountClust_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CountClust_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CountClust_1.2.0.tgz", "vignettes": [ "vignettes/CountClust/inst/doc/count-clust.pdf" ], "vignetteTitles": [ "Grade of Membership Clustering and Visualization using CountClust" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CountClust/inst/doc/count-clust.R" ] }, "covEB": { "Package": "covEB", "Version": "1.0.0", "Depends": [ "R (>= 3.3)", "mvtnorm", "igraph", "gsl", "Biobase", "stats" ], "Suggests": [ "curatedBladderData" ], "License": "GPL-3", "MD5sum": "e6d54ff3e3e1306174fa8f7dfa261b71", "NeedsCompilation": "no", "Title": "Empirical Bayes estimate of block diagonal covariance matrices", "Description": "Using bayesian methods to estimate correlation matrices assuming that they can be written and estimated as block diagonal matrices. These block diagonal matrices are determined using shrinkage parameters that values below this parameter to zero.", "biocViews": [ "Bayesian", "GeneExpression", "Microarray", "Preprocessing", "RNASeq", "Software", "StatisticalMethod" ], "Author": "C. Pacini", "Maintainer": "C. Pacini ", "source.ver": "src/contrib/covEB_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/covEB_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/covEB_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/covEB_1.0.0.tgz", "vignettes": [ "vignettes/covEB/inst/doc/covEB.pdf" ], "vignetteTitles": [ "covEB" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/covEB/inst/doc/covEB.R" ] }, "CoverageView": { "Package": "CoverageView", "Version": "1.10.0", "Depends": [ "R (>= 2.10)", "methods", "Rsamtools (>= 1.19.17)", "rtracklayer" ], "Imports": [ "S4Vectors (>= 0.7.21)", "IRanges(>= 2.3.23)", "GenomicRanges", "GenomicAlignments", "parallel", "tools" ], "License": "Artistic-2.0", "MD5sum": "07253a42b68215a8b242b8e530b884e2", "NeedsCompilation": "no", "Title": "Coverage visualization package for R", "Description": "This package provides a framework for the visualization of genome coverage profiles. It can be used for ChIP-seq experiments, but it can be also used for genome-wide nucleosome positioning experiments or other experiment types where it is important to have a framework in order to inspect how the coverage distributed across the genome", "biocViews": [ "ChIPSeq", "RNASeq", "Sequencing", "Software", "Technology", "Visualization" ], "Author": "Ernesto Lowy", "Maintainer": "Ernesto Lowy ", "source.ver": "src/contrib/CoverageView_1.10.0.tar.gz", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CoverageView_1.10.0.tgz", "vignettes": [ "vignettes/CoverageView/inst/doc/CoverageView.pdf" ], "vignetteTitles": [ "Easy visualization of the read coverage" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CoverageView/inst/doc/CoverageView.R" ] }, "covRNA": { "Package": "covRNA", "Version": "1.0.0", "Depends": [ "ade4", "Biobase" ], "Imports": [ "parallel", "genefilter", "grDevices", "stats", "graphics" ], "Suggests": [ "BiocStyle", "knitr", "rmarkdown" ], "License": "GPL (>= 2)", "MD5sum": "147a85912c1db26e654345060b3ad435", "NeedsCompilation": "no", "Title": "Multivariate Analysis of Transcriptomic Data", "Description": "This package provides the analysis methods fourthcorner and RLQ analysis for large-scale transcriptomic data.", "biocViews": [ "GeneExpression", "Software", "Transcription" ], "Author": "Lara Urban ", "Maintainer": "Lara Urban ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/covRNA_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/covRNA_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/covRNA_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/covRNA_1.0.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/covRNA/inst/doc/covRNA.R" ], "htmlDocs": [ "vignettes/covRNA/inst/doc/covRNA.html" ], "htmlTitles": [ "An Introduction to covRNA" ] }, "cpvSNP": { "Package": "cpvSNP", "Version": "1.6.0", "Depends": [ "R (>= 2.10)", "GenomicFeatures", "GSEABase (>= 1.24.0)" ], "Imports": [ "methods", "corpcor", "BiocParallel", "ggplot2", "plyr" ], "Suggests": [ "TxDb.Hsapiens.UCSC.hg19.knownGene", "RUnit", "BiocGenerics", "ReportingTools", "BiocStyle" ], "License": "Artistic-2.0", "MD5sum": "41420532ef02064e33ff3eeb13c89243", "NeedsCompilation": "no", "Title": "Gene set analysis methods for SNP association p-values that lie in genes in given gene sets", "Description": "Gene set analysis methods exist to combine SNP-level association p-values into gene sets, calculating a single association p-value for each gene set. This package implements two such methods that require only the calculated SNP p-values, the gene set(s) of interest, and a correlation matrix (if desired). One method (GLOSSI) requires independent SNPs and the other (VEGAS) can take into account correlation (LD) among the SNPs. Built-in plotting functions are available to help users visualize results.", "biocViews": [ "GeneSetEnrichment", "Genetics", "GenomicVariation", "Pathways", "Software", "StatisticalMethod" ], "Author": "Caitlin McHugh, Jessica Larson, and Jason Hackney", "Maintainer": "Caitlin McHugh ", "source.ver": "src/contrib/cpvSNP_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/cpvSNP_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/cpvSNP_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/cpvSNP_1.6.0.tgz", "vignettes": [ "vignettes/cpvSNP/inst/doc/cpvSNP.pdf" ], "vignetteTitles": [ "Running gene set analyses with the \"cpvSNP\" package" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/cpvSNP/inst/doc/cpvSNP.R" ] }, "cqn": { "Package": "cqn", "Version": "1.20.0", "Depends": [ "R (>= 2.10.0)", "mclust", "nor1mix", "stats", "preprocessCore", "splines", "quantreg" ], "Imports": [ "splines" ], "Suggests": [ "scales", "edgeR" ], "License": "Artistic-2.0", "MD5sum": "49cbfe22490f2e1f7f31d4e8a434a7a0", "NeedsCompilation": "no", "Title": "Conditional quantile normalization", "Description": "A normalization tool for RNA-Seq data, implementing the conditional quantile normalization method.", "biocViews": [ "DifferentialExpression", "Preprocessing", "RNASeq", "Software" ], "Author": "Jean (Zhijin) Wu, Kasper Daniel Hansen", "Maintainer": "Kasper Daniel Hansen ", "source.ver": "src/contrib/cqn_1.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/cqn_1.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/cqn_1.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/cqn_1.20.0.tgz", "vignettes": [ "vignettes/cqn/inst/doc/cqn.pdf" ], "vignetteTitles": [ "CQN (Conditional Quantile Normalization)" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/cqn/inst/doc/cqn.R" ], "importsMe": [ "tweeDEseq" ] }, "CRImage": { "Package": "CRImage", "Version": "1.22.0", "Depends": [ "EBImage", "DNAcopy", "aCGH" ], "Imports": [ "MASS", "e1071", "foreach", "sgeostat" ], "License": "Artistic-2.0", "MD5sum": "12be6ccebab6a9f91b38d8f142ff6eca", "NeedsCompilation": "no", "Title": "CRImage a package to classify cells and calculate tumour cellularity", "Description": "CRImage provides functionality to process and analyze images, in particular to classify cells in biological images. Furthermore, in the context of tumor images, it provides functionality to calculate tumour cellularity.", "biocViews": [ "CellBiology", "Classification", "Software" ], "Author": "Henrik Failmezger , Yinyin Yuan , Oscar Rueda , Florian Markowetz ", "Maintainer": "Henrik Failmezger , Yinyin Yuan ", "source.ver": "src/contrib/CRImage_1.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CRImage_1.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CRImage_1.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CRImage_1.22.0.tgz", "vignettes": [ "vignettes/CRImage/inst/doc/CRImage.pdf" ], "vignetteTitles": [ "CRImage Manual" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CRImage/inst/doc/CRImage.R" ] }, "CRISPRseek": { "Package": "CRISPRseek", "Version": "1.14.1", "Depends": [ "R (>= 3.0.1)", "BiocGenerics", "Biostrings" ], "Imports": [ "parallel", "data.table", "seqinr", "S4Vectors (>= 0.9.25)", "IRanges", "BSgenome", "BiocParallel", "hash" ], "Suggests": [ "RUnit", "BiocStyle", "BSgenome.Hsapiens.UCSC.hg19", "TxDb.Hsapiens.UCSC.hg19.knownGene", "org.Hs.eg.db" ], "License": "GPL (>= 2)", "MD5sum": "38dae68d37b131540fcddc35fe087479", "NeedsCompilation": "no", "Title": "Design of target-specific guide RNAs in CRISPR-Cas9, genome-editing systems", "Description": "The package includes functions to find potential guide RNAs for input target sequences, optionally filter guide RNAs without restriction enzyme cut site, or without paired guide RNAs, genome-wide search for off-targets, score, rank, fetch flank sequence and indicate whether the target and off-targets are located in exon region or not. Potential guide RNAs are annotated with total score of the top5 and topN off-targets, detailed topN mismatch sites, restriction enzyme cut sites, and paired guide RNAs. If GeneRfold and GeneR are installed (http://bioconductor.case.edu/bioconductor/2.8/bioc/html/GeneRfold.html, http://bioc.ism.ac.jp/packages/2.8/bioc/html/GeneR.html), then the minimum free energy and bracket notation of secondary structure of gRNA and gRNA backbone constant region will be included in the summary file. This package leverages Biostrings and BSgenome packages.", "biocViews": [ "CRISPR", "GeneRegulation", "SequenceMatching", "Software" ], "Author": "Lihua Julie Zhu, Benjamin R. Holmes, Herve Pages, Michael Lawrence, Isana Veksler-Lublinsky, Victor Ambros, Neil Aronin and Michael Brodsky", "Maintainer": "Lihua Julie Zhu ", "source.ver": "src/contrib/CRISPRseek_1.14.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CRISPRseek_1.14.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CRISPRseek_1.14.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CRISPRseek_1.14.1.tgz", "vignettes": [ "vignettes/CRISPRseek/inst/doc/CRISPRseek.pdf" ], "vignetteTitles": [ "CRISPRseek Vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CRISPRseek/inst/doc/CRISPRseek.R" ], "dependsOnMe": [ "crisprseekplus" ], "importsMe": [ "GUIDEseq" ] }, "crisprseekplus": { "Package": "crisprseekplus", "Version": "1.0.0", "Depends": [ "R (>= 3.3.0)", "shiny", "shinyjs", "CRISPRseek" ], "Imports": [ "DT", "utils", "GUIDEseq", "GenomicRanges", "GenomicFeatures", "BiocInstaller", "BSgenome", "AnnotationDbi", "hash" ], "Suggests": [ "testthat", "rmarkdown", "knitr", "R.rsp" ], "License": "GPL-3 + file LICENSE", "MD5sum": "aacd4fee06e087c468e877a53469a498", "NeedsCompilation": "no", "Title": "crisprseekplus", "Description": "Bioinformatics platform containing interface to work with offTargetAnalysis and compare2Sequences in the CRISPRseek package, and GUIDEseqAnalysis.", "biocViews": [ "GeneRegulation", "SequenceMatching", "Software" ], "Author": "Sophie Wigmore , Alper Kucukural , Lihua Julie Zhu , Michael Brodsky , Manuel Garber ", "Maintainer": "Alper Kucukural ", "URL": "https://github.com/UMMS-Biocore/crisprseekplus", "VignetteBuilder": "knitr, R.rsp", "BugReports": "https://github.com/UMMS-Biocore/crisprseekplus/issues/new", "source.ver": "src/contrib/crisprseekplus_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/crisprseekplus_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/crisprseekplus_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/crisprseekplus_1.0.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/crisprseekplus/inst/doc/crisprseekplus.R" ], "htmlDocs": [ "vignettes/crisprseekplus/inst/doc/crisprseekplus.html" ], "htmlTitles": [ "DEBrowser Vignette" ] }, "CrispRVariants": { "Package": "CrispRVariants", "Version": "1.2.0", "Depends": [ "R (>= 3.3)", "ggplot2" ], "Imports": [ "AnnotationDbi", "BiocParallel", "Biostrings", "methods", "GenomeInfoDb", "GenomicAlignments", "GenomicRanges", "grDevices", "grid", "gridExtra", "IRanges", "reshape2", "Rsamtools", "S4Vectors (>= 0.9.38)", "utils" ], "Suggests": [ "BiocStyle", "gdata", "GenomicFeatures", "knitr", "rmarkdown", "rtracklayer", "sangerseqR", "testthat", "VariantAnnotation" ], "License": "GPL-2", "MD5sum": "f83bde89e69a3e23e444ec83d0b755aa", "NeedsCompilation": "no", "Title": "Tools for counting and visualising mutations in a target location", "Description": "CrispRVariants provides tools for analysing the results of a CRISPR-Cas9 mutagenesis sequencing experiment, or other sequencing experiments where variants within a given region are of interest. These tools allow users to localize variant allele combinations with respect to any genomic location (e.g. the Cas9 cut site), plot allele combinations and calculate mutation rates with flexible filtering of unrelated variants.", "biocViews": [ "CRISPR", "DataRepresentation", "GeneticVariability", "GenomicVariation", "Software", "VariantDetection", "Visualization" ], "Author": "Helen Lindsay [aut, cre]", "Maintainer": "Helen Lindsay ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/CrispRVariants_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CrispRVariants_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CrispRVariants_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CrispRVariants_1.2.0.tgz", "vignettes": [ "vignettes/CrispRVariants/inst/doc/user_guide.pdf" ], "vignetteTitles": [ "CrispRVariants" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CrispRVariants/inst/doc/user_guide.R" ] }, "crlmm": { "Package": "crlmm", "Version": "1.32.0", "Depends": [ "R (>= 2.14.0)", "oligoClasses (>= 1.21.12)", "preprocessCore (>= 1.17.7)" ], "Imports": [ "methods", "Biobase (>= 2.15.4)", "BiocGenerics", "affyio (>= 1.23.2)", "illuminaio", "ellipse", "mvtnorm", "splines", "stats", "SNPchip", "utils", "lattice", "ff", "foreach", "RcppEigen (>= 0.3.1.2.1)", "matrixStats", "VGAM", "parallel", "graphics", "limma", "beanplot" ], "LinkingTo": [ "preprocessCore (>= 1.17.7)" ], "Suggests": [ "hapmapsnp6", "genomewidesnp6Crlmm (>= 1.0.7)", "GGdata", "snpStats", "RUnit" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "95b2b71866647ed1ee3667941fdc3194", "NeedsCompilation": "yes", "Title": "Genotype Calling (CRLMM) and Copy Number Analysis tool for Affymetrix SNP 5.0 and 6.0 and Illumina arrays", "Description": "Faster implementation of CRLMM specific to SNP 5.0 and 6.0 arrays, as well as a copy number tool specific to 5.0, 6.0, and Illumina platforms.", "biocViews": [ "CopyNumberVariation", "Microarray", "Preprocessing", "SNP", "Software" ], "Author": "Benilton S Carvalho, Robert Scharpf, Matt Ritchie, Ingo Ruczinski, Rafael A Irizarry", "Maintainer": "Benilton S Carvalho , Robert Scharpf , Matt Ritchie ", "source.ver": "src/contrib/crlmm_1.32.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/crlmm_1.32.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/crlmm_1.32.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/crlmm_1.32.0.tgz", "vignettes": [ "vignettes/crlmm/inst/doc/AffyGW.pdf", "vignettes/crlmm/inst/doc/CopyNumberOverview.pdf", "vignettes/crlmm/inst/doc/genotyping.pdf", "vignettes/crlmm/inst/doc/gtypeDownstream.pdf", "vignettes/crlmm/inst/doc/IlluminaPreprocessCN.pdf", "vignettes/crlmm/inst/doc/Infrastructure.pdf" ], "vignetteTitles": [ "Copy number estimation", "Overview of copy number vignettes", "crlmm Vignette - Genotyping", "crlmm Vignette - Downstream Analysis", "Preprocessing and genotyping Illumina arrays for copy number analysis", "Infrastructure for copy number analysis" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/crlmm/inst/doc/genotyping.R" ], "importsMe": [ "VanillaICE" ], "suggestsMe": [ "ArrayTV", "hapmap370k", "oligoClasses", "SNPchip" ] }, "crossmeta": { "Package": "crossmeta", "Version": "1.0.1", "Depends": [ "R (>= 3.3)" ], "Imports": [ "affy (>= 1.50.0)", "affxparser (>= 1.44.0)", "AnnotationDbi (>= 1.34.4)", "Biobase (>= 2.32.0)", "BiocGenerics (>= 0.18.0)", "BiocInstaller (>= 1.22.3)", "DT (>= 0.2)", "data.table (>= 1.9.6)", "fdrtool (>= 1.2.15)", "GEOquery (>= 2.38.4)", "limma (>= 3.28.17)", "matrixStats (>= 0.50.2)", "metaMA (>= 3.1.2)", "miniUI (>= 0.1.1)", "oligo (>= 1.36.1)", "pander (>= 0.6.0)", "RColorBrewer (>= 1.1.2)", "rdrop2 (>= 0.7.0)", "stringr (>= 1.0.0)", "sva (>= 3.20.0)", "shiny (>= 0.13.2)" ], "Suggests": [ "knitr", "rmarkdown", "lydata", "org.Hs.eg.db", "testthat" ], "License": "MIT + file LICENSE", "MD5sum": "7944c749dad11c6a57046dfa4cf7834b", "NeedsCompilation": "no", "Title": "Cross Platform Meta-Analysis of Microarray Data", "Description": "Implements cross-platform and cross-species meta-analyses of Affymentrix, Illumina, and Agilent microarray data. This package automates common tasks such as downloading, normalizing, and annotating raw GEO data. A user interface makes it easy to select control and treatment samples for each contrast and study. This input is used for subsequent surrogate variable analysis (models unaccounted sources of variation) and differential expression analysis. Final meta-analysis of differential expression values can include genes measured in only a subset of studies.", "biocViews": [ "Annotation", "BatchEffect", "DifferentialExpression", "GeneExpression", "Microarray", "OneChannel", "Preprocessing", "Software", "TissueMicroarray", "Transcription" ], "Author": "Alex Pickering", "Maintainer": "Alex Pickering ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/crossmeta_1.0.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/crossmeta_1.0.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/crossmeta_1.0.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/crossmeta_1.0.1.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/crossmeta/inst/doc/crossmeta-vignette.R" ], "htmlDocs": [ "vignettes/crossmeta/inst/doc/crossmeta-vignette.html" ], "htmlTitles": [ "crossmeta vignette" ], "suggestsMe": [ "ccmap" ] }, "CSAR": { "Package": "CSAR", "Version": "1.26.0", "Depends": [ "R (>= 2.15.0)", "S4Vectors", "IRanges", "GenomeInfoDb", "GenomicRanges" ], "Imports": [ "stats", "utils" ], "Suggests": [ "ShortRead", "Biostrings" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "c6f1c86b6de8d34902fa15faaabf020a", "NeedsCompilation": "yes", "Title": "Statistical tools for the analysis of ChIP-seq data", "Description": "Statistical tools for ChIP-seq data analysis. The package includes the statistical method described in Kaufmann et al. (2009) PLoS Biology: 7(4):e1000090. Briefly, Taking the average DNA fragment size subjected to sequencing into account, the software calculates genomic single-nucleotide read-enrichment values. After normalization, sample and control are compared using a test based on the Poisson distribution. Test statistic thresholds to control the false discovery rate are obtained through random permutation.", "biocViews": [ "ChIPSeq", "Genetics", "Software", "Transcription" ], "Author": "Jose M Muino", "Maintainer": "Jose M Muino ", "source.ver": "src/contrib/CSAR_1.26.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CSAR_1.26.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CSAR_1.26.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CSAR_1.26.0.tgz", "vignettes": [ "vignettes/CSAR/inst/doc/CSAR.pdf" ], "vignetteTitles": [ "CSAR Vignette" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CSAR/inst/doc/CSAR.R" ], "importsMe": [ "NarrowPeaks" ], "suggestsMe": [ "NarrowPeaks" ] }, "csaw": { "Package": "csaw", "Version": "1.8.1", "Depends": [ "R (>= 3.3.0)", "GenomicRanges", "SummarizedExperiment (>= 1.1.6)", "BiocParallel" ], "Imports": [ "Rsamtools", "edgeR", "limma", "GenomicFeatures", "AnnotationDbi", "methods", "S4Vectors", "IRanges", "GenomeInfoDb", "BiocGenerics", "Rhtslib", "stats" ], "LinkingTo": [ "Rhtslib", "zlibbioc" ], "Suggests": [ "org.Mm.eg.db", "TxDb.Mmusculus.UCSC.mm10.knownGene" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "e236bd1787215dce64e5cabfda18c4f9", "NeedsCompilation": "yes", "Title": "ChIP-Seq Analysis with Windows", "Description": "Detection of differentially bound regions in ChIP-seq data with sliding windows, with methods for normalization and proper FDR control.", "biocViews": [ "Annotation", "ChIPSeq", "Coverage", "DifferentialPeakCalling", "Genetics", "MultipleComparison", "Normalization", "Sequencing", "Software" ], "Author": "Aaron Lun , Gordon Smyth ", "Maintainer": "Aaron Lun ", "source.ver": "src/contrib/csaw_1.8.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/csaw_1.8.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/csaw_1.8.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/csaw_1.8.1.tgz", "vignettes": [ "vignettes/csaw/inst/doc/csaw.pdf", "vignettes/csaw/inst/doc/csawUserGuide.pdf" ], "vignetteTitles": [ "csaw Vignette", "csawUserGuide.pdf" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "importsMe": [ "diffHic" ] }, "CSSP": { "Package": "CSSP", "Version": "1.12.0", "Imports": [ "methods", "splines", "stats", "utils" ], "Suggests": [ "testthat" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "a0d690c55cfa5a2f93ef8cea10d384f4", "NeedsCompilation": "yes", "Title": "ChIP-Seq Statistical Power", "Description": "Power computation for ChIP-Seq data based on Bayesian estimation for local poisson counting process.", "biocViews": [ "Bayesian", "ChIPSeq", "QualityControl", "Sequencing", "Software" ], "Author": "Chandler Zuo, Sunduz Keles", "Maintainer": "Chandler Zuo", "source.ver": "src/contrib/CSSP_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CSSP_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CSSP_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CSSP_1.12.0.tgz", "vignettes": [ "vignettes/CSSP/inst/doc/cssp.pdf" ], "vignetteTitles": [ "cssp.pdf" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CSSP/inst/doc/cssp.R" ] }, "ctc": { "Package": "ctc", "Version": "1.48.0", "Depends": [ "amap" ], "License": "GPL-2", "MD5sum": "e032e50a1e44babfddb283b28309f514", "NeedsCompilation": "no", "Title": "Cluster and Tree Conversion.", "Description": "Tools for export and import classification trees and clusters to other programs", "biocViews": [ "Classification", "Clustering", "DataImport", "Microarray", "Software", "Visualization" ], "Author": "Antoine Lucas , Laurent Gautier ", "Maintainer": "Antoine Lucas ", "URL": "http://antoinelucas.free.fr/ctc", "source.ver": "src/contrib/ctc_1.48.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ctc_1.48.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ctc_1.48.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ctc_1.48.0.tgz", "vignettes": [ "vignettes/ctc/inst/doc/ctc.pdf" ], "vignetteTitles": [ "Introduction to ctc" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ctc/inst/doc/ctc.R" ], "importsMe": [ "multiClust" ] }, "ctsGE": { "Package": "ctsGE", "Version": "1.0.0", "Depends": [ "R (>= 3.2)" ], "Imports": [ "ccaPP", "ggplot2", "limma", "reshape2", "shiny", "stats", "stringr", "utils" ], "Suggests": [ "BiocStyle", "dplyr", "DT", "GEOquery", "knitr", "pander", "rmarkdown", "testthat" ], "License": "GPL-2", "MD5sum": "da32f305f9242fd842290639bc361469", "NeedsCompilation": "no", "Title": "Clustering of Time Series Gene Expression data", "Description": "Methodology for supervised clustering of potentially many predictor variables, such as genes etc., in time series datasets Provides functions that help the user assigning genes to predefined set of model profiles.", "biocViews": [ "Bayesian", "Clustering", "DifferentialExpression", "GeneExpression", "GeneSetEnrichment", "Genetics", "RNASeq", "Sequencing", "Software", "TimeCourse", "Transcription" ], "Author": "Michal Sharabi-Schwager [aut, cre], Ron Ophir [aut]", "Maintainer": "Michal Sharabi-Schwager ", "URL": "https://github.com/michalsharabi/ctsGE", "VignetteBuilder": "knitr", "BugReports": "https://github.com/michalsharabi/ctsGE/issues", "source.ver": "src/contrib/ctsGE_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ctsGE_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ctsGE_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ctsGE_1.0.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ctsGE/inst/doc/ctsGE.R" ], "htmlDocs": [ "vignettes/ctsGE/inst/doc/ctsGE.html" ], "htmlTitles": [ "ctsGE Package" ] }, "cummeRbund": { "Package": "cummeRbund", "Version": "2.16.0", "Depends": [ "R (>= 2.7.0)", "BiocGenerics (>= 0.3.2)", "RSQLite", "ggplot2", "reshape2", "fastcluster", "rtracklayer", "Gviz" ], "Imports": [ "methods", "plyr", "BiocGenerics", "S4Vectors (>= 0.9.25)", "Biobase" ], "Suggests": [ "cluster", "plyr", "NMFN", "stringr", "GenomicFeatures", "GenomicRanges", "rjson" ], "License": "Artistic-2.0", "MD5sum": "4563d786aa9a596187f1a6e5e31b2210", "NeedsCompilation": "no", "Title": "Analysis, exploration, manipulation, and visualization of Cufflinks high-throughput sequencing data.", "Description": "Allows for persistent storage, access, exploration, and manipulation of Cufflinks high-throughput sequencing data. In addition, provides numerous plotting functions for commonly used visualizations.", "biocViews": [ "Bioinformatics", "Clustering", "DataImport", "DataRepresentation", "DifferentialExpression", "GeneExpression", "HighThroughputSequencing", "HighThroughputSequencingData", "Infrastructure", "MultipleComparisons", "QualityControl", "RNAseq", "RNAseqData", "Software", "Visualization" ], "Author": "L. Goff, C. Trapnell, D. Kelley", "Maintainer": "Loyal A. Goff ", "source.ver": "src/contrib/cummeRbund_2.16.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/cummeRbund_2.16.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/cummeRbund_2.16.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/cummeRbund_2.16.0.tgz", "vignettes": [ "vignettes/cummeRbund/inst/doc/cummeRbund-example-workflow.pdf", "vignettes/cummeRbund/inst/doc/cummeRbund-manual.pdf" ], "vignetteTitles": [ "Sample cummeRbund workflow", "CummeRbund User Guide" ], "hasREADME": true, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/cummeRbund/inst/doc/cummeRbund-example-workflow.R", "vignettes/cummeRbund/inst/doc/cummeRbund-manual.R" ], "dependsOnMe": [ "meshr", "spliceR" ], "suggestsMe": [ "oneChannelGUI" ] }, "customProDB": { "Package": "customProDB", "Version": "1.14.1", "Depends": [ "R (>= 3.0.1)", "IRanges", "AnnotationDbi", "biomaRt" ], "Imports": [ "S4Vectors (>= 0.9.25)", "IRanges", "GenomeInfoDb", "GenomicRanges", "Rsamtools (>= 1.10.2)", "GenomicAlignments", "Biostrings (>= 2.26.3)", "GenomicFeatures (>= 1.17.13)", "biomaRt (>= 2.17.1)", "stringr", "RCurl", "plyr", "VariantAnnotation (>= 1.13.44)", "rtracklayer", "RSQLite", "AnnotationDbi" ], "Suggests": [ "BSgenome.Hsapiens.UCSC.hg19" ], "License": "Artistic-2.0", "MD5sum": "8259b6afee9e1f73f4570818480f42f3", "NeedsCompilation": "no", "Title": "Generate customized protein database from NGS data, with a focus on RNA-Seq data, for proteomics search.", "Description": "Generate customized protein sequence database from RNA-Seq data for proteomics search", "biocViews": [ "AlternativeSplicing", "MassSpectrometry", "Proteomics", "RNASeq", "SNP", "Software", "Transcription" ], "Author": "xiaojing wang", "Maintainer": "xiaojing wang ", "source.ver": "src/contrib/customProDB_1.14.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/customProDB_1.14.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/customProDB_1.14.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/customProDB_1.14.1.tgz", "vignettes": [ "vignettes/customProDB/inst/doc/customProDB.pdf" ], "vignetteTitles": [ "Introduction to customProDB" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/customProDB/inst/doc/customProDB.R" ], "importsMe": [ "PGA" ] }, "CVE": { "Package": "CVE", "Version": "1.0.0", "Depends": [ "R (>= 3.3)", "shiny", "ConsensusClusterPlus", "RColorBrewer", "gplots", "plyr", "ggplot2", "jsonlite", "ape", "WGCNA" ], "Suggests": [ "knitr", "rmarkdown", "testthat", "BiocStyle" ], "License": "GPL-3", "MD5sum": "d30dc89f90fba8515f9c52cf59a56b77", "NeedsCompilation": "no", "Title": "Cancer Variant Explorer", "Description": "Shiny app for interactive variant prioritisation in precision cancer medicine. The input file for CVE is the output file of the recently released Oncotator Variant Annotation tool summarising variant-centric information from 14 different publicly available resources relevant for cancer researches. Interactive priortisation in CVE is based on known germline and cancer variants, DNA repair genes and functional prediction scores. An optional feature of CVE is the exploration of the tumour-specific pathway context that is facilitated using co-expression modules generated from publicly available transcriptome data. Finally druggability of prioritised variants is assessed using the Drug Gene Interaction Database (DGIdb).", "biocViews": [ "BiomedicalInformatics", "Software" ], "Author": "Andreas Mock [aut, cre]", "Maintainer": "Andreas Mock ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/CVE_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CVE_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CVE_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CVE_1.0.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CVE/inst/doc/CVE_tutorial.R", "vignettes/CVE/inst/doc/WGCNA_from_TCGA_RNAseq.R" ], "htmlDocs": [ "vignettes/CVE/inst/doc/CVE_tutorial.html", "vignettes/CVE/inst/doc/WGCNA_from_TCGA_RNAseq.html" ], "htmlTitles": [ "Cancer Variant Explorer (CVE) tutorial", "Weighted gene co-expression network analysis with TCGA RNAseq data" ] }, "cycle": { "Package": "cycle", "Version": "1.28.0", "Depends": [ "R (>= 2.10.0)", "Mfuzz" ], "Imports": [ "Biobase", "stats" ], "License": "GPL-2", "MD5sum": "67c8149667740c198a8306e6f7149880", "NeedsCompilation": "no", "Title": "Significance of periodic expression pattern in time-series data", "Description": "Package for assessing the statistical significance of periodic expression based on Fourier analysis and comparison with data generated by different background models", "biocViews": [ "Microarray", "Software", "TimeCourse" ], "Author": "Matthias Futschik ", "Maintainer": "Matthias Futschik ", "URL": "http://cycle.sysbiolab.eu", "source.ver": "src/contrib/cycle_1.28.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/cycle_1.28.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/cycle_1.28.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/cycle_1.28.0.tgz", "vignettes": [ "vignettes/cycle/inst/doc/cycle.pdf" ], "vignetteTitles": [ "Introduction to cycle" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/cycle/inst/doc/cycle.R" ] }, "cytofkit": { "Package": "cytofkit", "Version": "1.6.5", "Depends": [ "R (>= 2.10.0)", "ggplot2", "plyr" ], "Imports": [ "tcltk", "stats", "Rtsne", "e1071", "flowCore", "gplots", "colourpicker", "VGAM", "reshape2", "ggrepel", "shiny", "vegan", "Biobase", "doParallel", "parallel", "pdist", "methods", "destiny", "FlowSOM(>= 1.4.0)", "igraph(>= 1.0.1)", "RANN(>= 2.5)", "Rcpp (>= 0.12.0)" ], "LinkingTo": [ "Rcpp" ], "Suggests": [ "knitr", "RUnit", "testthat", "BiocGenerics" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "0a55041ee6bf476c537dde4790d54562", "NeedsCompilation": "yes", "Title": "cytofkit: an integrated mass cytometry data analysis pipeline", "Description": "An integrated mass cytometry data analysis pipeline that enables simultaneous illustration of cellular diversity and progression.", "biocViews": [ "BiomedicalInformatics", "CellBiology", "Clustering", "DimensionReduction", "FlowCytometry", "GUI", "Software" ], "Author": "Jinmiao Chen, Hao Chen", "Maintainer": "Jinmiao Chen , Hao Chen ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/cytofkit_1.6.5.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/cytofkit_1.6.5.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/cytofkit_1.6.5.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/cytofkit_1.6.5.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/cytofkit/inst/doc/cytofkit_example.R", "vignettes/cytofkit/inst/doc/cytofkit_shinyAPP.R", "vignettes/cytofkit/inst/doc/cytofkit_workflow.R" ], "htmlDocs": [ "vignettes/cytofkit/inst/doc/cytofkit_example.html", "vignettes/cytofkit/inst/doc/cytofkit_shinyAPP.html", "vignettes/cytofkit/inst/doc/cytofkit_workflow.html" ], "htmlTitles": [ "Quick Start", "ShinyAPP tutorial", "Analysis Pipeline" ] }, "CytoML": { "Package": "CytoML", "Version": "1.0.1", "Imports": [ "flowCore", "flowWorkspace (>= 3.19.24)", "openCyto (>= 1.11.3)", "XML", "data.table", "flowUtils (>= 1.35.7)", "jsonlite", "RBGL", "ncdfFlow", "Rgraphviz", "Biobase", "methods", "graph", "graphics", "utils", "base64enc" ], "Suggests": [ "testthat", "flowWorkspaceData", "knitr", "ggcyto" ], "License": "Artistic-2.0", "MD5sum": "0272bb9787c07223598ac7b46202acec", "NeedsCompilation": "no", "Title": "GatingML interface for openCyto", "Description": "This package is designed to use GatingML2.0 as the standard format to exchange the gated data with other software platform.", "biocViews": [ "DataImport", "DataRepresentation", "FlowCytometry", "Software" ], "Author": "Mike Jiang", "Maintainer": "Mike Jiang ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/CytoML_1.0.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/CytoML_1.0.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/CytoML_1.0.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/CytoML_1.0.1.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/CytoML/inst/doc/HowToExportGatingSet.R", "vignettes/CytoML/inst/doc/HowToParseGatingML.R" ], "htmlDocs": [ "vignettes/CytoML/inst/doc/HowToExportGatingSet.html", "vignettes/CytoML/inst/doc/HowToParseGatingML.html" ], "htmlTitles": [ "How to export a GatingSet to GatingML", "How to parse gatingML into a GatingSet" ] }, "dada2": { "Package": "dada2", "Version": "1.2.2", "Depends": [ "R (>= 3.2.0)", "Rcpp (>= 0.11.2)", "methods (>= 3.2.0)" ], "Imports": [ "Biostrings (>= 2.32.1)", "ggplot2 (>= 1.0)", "data.table (>= 1.9.4)", "reshape2 (>= 1.4.1)", "ShortRead (>= 1.24.0)", "RcppParallel (>= 4.3.0)", "parallel (>= 3.2.0)" ], "LinkingTo": [ "Rcpp", "RcppParallel" ], "Suggests": [ "testthat (>= 0.9.1)", "BiocStyle", "knitr", "rmarkdown" ], "License": "LGPL-3", "Archs": "i386, x64", "MD5sum": "9813f63e75eecd0298d3d5e7d96a460b", "NeedsCompilation": "yes", "Title": "Accurate, high-resolution sample inference from amplicon sequencing data", "Description": "The dada2 package infers exact sequence variants (SVs) from amplicon data, replacing the commonly used and coarser OTU clustering approach. The dada2 pipeline inputs demultiplexed fastq files, and outputs the sequence variants and their sample-wise abundances after removing substitution and chimera errors. Taxonomic classification is available via a native implementation of the RDP naive Bayesian classifier.", "biocViews": [ "Classification", "Metagenomics", "Microbiome", "Sequencing", "Software" ], "Author": "Benjamin Callahan , Paul McMurdie, Susan Holmes", "Maintainer": "Benjamin Callahan ", "URL": "http://benjjneb.github.io/dada2/", "SystemRequirements": "GNU make", "VignetteBuilder": "knitr", "BugReports": "https://github.com/benjjneb/dada2/issues", "source.ver": "src/contrib/dada2_1.2.2.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/dada2_1.2.2.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/dada2_1.2.2.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/dada2_1.2.2.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/dada2/inst/doc/dada2-intro.R" ], "htmlDocs": [ "vignettes/dada2/inst/doc/dada2-intro.html" ], "htmlTitles": [ "Introduction to dada2" ] }, "dagLogo": { "Package": "dagLogo", "Version": "1.12.0", "Depends": [ "R (>= 3.0.1)", "methods", "biomaRt", "grImport", "grid", "motifStack" ], "Imports": [ "pheatmap", "Biostrings" ], "Suggests": [ "XML", "UniProt.ws", "BiocStyle", "knitr", "rmarkdown", "testthat" ], "License": "GPL (>=2)", "MD5sum": "f988a88059f176e36e55ea4d63a59af3", "NeedsCompilation": "no", "Title": "dagLogo", "Description": "Visualize significant conserved amino acid sequence pattern in groups based on probability theory.", "biocViews": [ "SequenceMatching", "Software", "Visualization" ], "Author": "Jianhong Ou, Alexey Stukalov, Niraj Nirala, Usha Acharya, Lihua Julie Zhu", "Maintainer": "Jianhong Ou ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/dagLogo_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/dagLogo_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/dagLogo_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/dagLogo_1.12.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/dagLogo/inst/doc/dagLogo.R" ], "htmlDocs": [ "vignettes/dagLogo/inst/doc/dagLogo.html" ], "htmlTitles": [ "dagLogo Vignette" ] }, "daMA": { "Package": "daMA", "Version": "1.46.0", "Imports": [ "MASS", "stats" ], "License": "GPL (>= 2)", "MD5sum": "971a7d2303b57120efca741b5aa4588e", "NeedsCompilation": "no", "Title": "Efficient design and analysis of factorial two-colour microarray data", "Description": "This package contains functions for the efficient design of factorial two-colour microarray experiments and for the statistical analysis of factorial microarray data. Statistical details are described in Bretz et al. (2003, submitted)", "biocViews": [ "DifferentialExpression", "Microarray", "Software", "TwoChannel" ], "Author": "Jobst Landgrebe and Frank Bretz ", "Maintainer": "Jobst Landgrebe ", "URL": "http://www.microarrays.med.uni-goettingen.de", "source.ver": "src/contrib/daMA_1.46.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/daMA_1.46.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/daMA_1.46.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/daMA_1.46.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false }, "DAPAR": { "Package": "DAPAR", "Version": "1.6.0", "Depends": [ "R (>= 3.3)" ], "Imports": [ "MSnbase", "RColorBrewer", "stats", "preprocessCore", "Cairo", "png", "lattice", "reshape2", "gplots", "pcaMethods", "ggplot2", "limma", "knitr", "tmvtnorm", "norm", "impute", "imputeLCMD", "doParallel", "parallel", "foreach", "grDevices", "graphics", "openxlsx", "utils", "cp4p (>= 0.3.5)", "scales", "Matrix", "vioplot" ], "Suggests": [ "BiocGenerics", "Biobase", "testthat", "BiocStyle", "Prostar" ], "License": "Artistic-2.0", "MD5sum": "acaeea42b631a5a957bd9ff347e4bb2b", "NeedsCompilation": "no", "Title": "Tools for the Differential Analysis of Proteins Abundance with R", "Description": "This package contains a collection of functions for the visualisation and the statistical analysis of proteomic data.", "biocViews": [ "DataImport", "MassSpectrometry", "Normalization", "Preprocessing", "Proteomics", "QualityControl", "Software" ], "Author": "Samuel Wieczorek [cre,aut], Florence Combes [aut], Thomas Burger [aut], Cosmin Lazar [ctb], Alexia Dorffer [ctb]", "Maintainer": "Samuel Wieczorek ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/DAPAR_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/DAPAR_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/DAPAR_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/DAPAR_1.6.0.tgz", "vignettes": [ "vignettes/DAPAR/inst/doc/intro.pdf", "vignettes/DAPAR/inst/doc/Prostar_UserManual.pdf", "vignettes/DAPAR/inst/doc/UPSprotx2.pdf" ], "vignetteTitles": [ "DAPAR One Page Introduction", "Prostar user manual", "UPSprotx2 dataset description" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/DAPAR/inst/doc/Prostar_UserManual.R" ], "importsMe": [ "Prostar" ], "suggestsMe": [ "DAPARdata" ] }, "DART": { "Package": "DART", "Version": "1.22.0", "Depends": [ "R (>= 2.10.0)", "igraph (>= 0.6.0)" ], "Suggests": [ "breastCancerVDX", "breastCancerMAINZ", "Biobase" ], "License": "GPL-2", "MD5sum": "ce81c9622ec6961d003f55adac2b5bc4", "NeedsCompilation": "no", "Title": "Denoising Algorithm based on Relevance network Topology", "Description": "Denoising Algorithm based on Relevance network Topology (DART) is an algorithm designed to evaluate the consistency of prior information molecular signatures (e.g in-vitro perturbation expression signatures) in independent molecular data (e.g gene expression data sets). If consistent, a pruning network strategy is then used to infer the activation status of the molecular signature in individual samples.", "biocViews": [ "DifferentialExpression", "GeneExpression", "GraphAndNetwork", "Pathways", "Software" ], "Author": "Yan Jiao, Katherine Lawler, Andrew E Teschendorff, Charles Shijie Zheng", "Maintainer": "Charles Shijie Zheng ", "source.ver": "src/contrib/DART_1.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/DART_1.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/DART_1.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/DART_1.22.0.tgz", "vignettes": [ "vignettes/DART/inst/doc/DART.pdf" ], "vignetteTitles": [ "DART Tutorial" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/DART/inst/doc/DART.R" ] }, "DBChIP": { "Package": "DBChIP", "Version": "1.18.0", "Depends": [ "R (>= 2.15.0)", "edgeR", "DESeq" ], "Suggests": [ "ShortRead", "BiocGenerics" ], "License": "GPL (>= 2)", "MD5sum": "800cfbbfe37aa9752783710f394470d1", "NeedsCompilation": "no", "Title": "Differential Binding of Transcription Factor with ChIP-seq", "Description": "DBChIP detects differentially bound sharp binding sites across multiple conditions, with or without matching control samples.", "biocViews": [ "ChIPSeq", "Genetics", "Sequencing", "Software", "Transcription" ], "Author": "Kun Liang", "Maintainer": "Kun Liang ", "source.ver": "src/contrib/DBChIP_1.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/DBChIP_1.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/DBChIP_1.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/DBChIP_1.18.0.tgz", "vignettes": [ "vignettes/DBChIP/inst/doc/DBChIP.pdf" ], "vignetteTitles": [ "DBChIP" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/DBChIP/inst/doc/DBChIP.R" ], "importsMe": [ "metagene" ] }, "dcGSA": { "Package": "dcGSA", "Version": "1.2.0", "Depends": [ "R (>= 3.3)", "Matrix" ], "Imports": [ "BiocParallel" ], "Suggests": [ "knitr" ], "License": "GPL-2", "MD5sum": "3cfb02d330d9098cdda7888304f855e3", "NeedsCompilation": "no", "Title": "Distance-correlation based Gene Set Analysis for longitudinal gene expression profiles", "Description": "Distance-correlation based Gene Set Analysis for longitudinal gene expression profiles. In longitudinal studies, the gene expression profiles were collected at each visit from each subject and hence there are multiple measurements of the gene expression profiles for each subject. The dcGSA package could be used to assess the associations between gene sets and clinical outcomes of interest by fully taking advantage of the longitudinal nature of both the gene expression profiles and clinical outcomes.", "biocViews": [ "GeneExpression", "GeneSetEnrichment", "Microarray", "RNASeq", "Sequencing", "Software", "StatisticalMethod" ], "Author": "Jiehuan Sun [aut, cre], Jose Herazo-Maya [aut], Xiu Huang [aut], Naftali Kaminski [aut], and Hongyu Zhao [aut]", "Maintainer": "Jiehuan sun ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/dcGSA_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/dcGSA_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/dcGSA_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/dcGSA_1.2.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false }, "DChIPRep": { "Package": "DChIPRep", "Version": "1.4.0", "Depends": [ "R (>= 3.3)", "DESeq2" ], "Imports": [ "methods", "stats", "utils", "ggplot2", "fdrtool", "reshape2", "GenomicRanges", "SummarizedExperiment", "smoothmest", "plyr", "tidyr", "assertthat", "S4Vectors", "purrr", "soGGi", "ChIPpeakAnno" ], "Suggests": [ "mgcv", "testthat", "BiocStyle", "knitr", "rmarkdown" ], "License": "MIT + file LICENCE", "MD5sum": "83d3bebbcc1677dbef0f55f555acb7ef", "NeedsCompilation": "no", "Title": "DChIPRep - Analysis of chromatin modification ChIP-Seq data with replication", "Description": "The DChIPRep package implements a methodology to assess differences between chromatin modification profiles in replicated ChIP-Seq studies as described in Chabbert et. al - http://www.dx.doi.org/10.15252/msb.20145776. A detailed description of the method is given in the software paper at https://doi.org/10.7717/peerj.1981", "biocViews": [ "ChIPSeq", "Sequencing", "Software" ], "Author": "Bernd Klaus [aut, cre], Christophe Chabbert [aut], Sebastian Gibb [ctb]", "Maintainer": "Bernd Klaus ", "SystemRequirements": "Python 2.7, HTSeq (>= 0.6.1), numpy, argparse, sys", "VignetteBuilder": "knitr", "source.ver": "src/contrib/DChIPRep_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/DChIPRep_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/DChIPRep_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/DChIPRep_1.4.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/DChIPRep/inst/doc/DChIPRepVignette.R" ], "htmlDocs": [ "vignettes/DChIPRep/inst/doc/DChIPRepVignette.html" ], "htmlTitles": [ "DChIPRepVignette" ] }, "ddCt": { "Package": "ddCt", "Version": "1.30.0", "Depends": [ "R (>= 2.3.0)", "methods" ], "Imports": [ "Biobase (>= 1.10.0)", "RColorBrewer (>= 0.1-3)", "xtable", "lattice", "BiocGenerics" ], "Suggests": [ "RUnit" ], "License": "LGPL-3", "MD5sum": "0587d4ed5782b3b10da0f28322a3ee5e", "NeedsCompilation": "no", "Title": "The ddCt Algorithm for the Analysis of Quantitative Real-Time PCR (qRT-PCR)", "Description": "The Delta-Delta-Ct (ddCt) Algorithm is an approximation method to determine relative gene expression with quantitative real-time PCR (qRT-PCR) experiments. Compared to other approaches, it requires no standard curve for each primer-target pair, therefore reducing the working load and yet returning accurate enough results as long as the assumptions of the amplification efficiency hold. The ddCt package implements a pipeline to collect, analyse and visualize qRT-PCR results, for example those from TaqMan SDM software, mainly using the ddCt method. The pipeline can be either invoked by a script in command-line or through the API consisting of S4-Classes, methods and functions.", "biocViews": [ "DifferentialExpression", "GeneExpression", "MicrotitrePlateAssay", "Software", "qPCR" ], "Author": "Jitao David Zhang, Rudolf Biczok, and Markus Ruschhaupt", "Maintainer": "Jitao David Zhang ", "source.ver": "src/contrib/ddCt_1.30.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ddCt_1.30.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ddCt_1.30.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ddCt_1.30.0.tgz", "vignettes": [ "vignettes/ddCt/inst/doc/RT-PCR-Script-ddCt.pdf", "vignettes/ddCt/inst/doc/rtPCR-usage.pdf", "vignettes/ddCt/inst/doc/rtPCR.pdf" ], "vignetteTitles": [ "How to apply the ddCt method", "Analyse RT-PCR data with the end-to-end script in ddCt package", "Introduction to the ddCt method for qRT-PCR data analysis: background, algorithm and example" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ddCt/inst/doc/RT-PCR-Script-ddCt.R", "vignettes/ddCt/inst/doc/rtPCR-usage.R", "vignettes/ddCt/inst/doc/rtPCR.R" ] }, "ddgraph": { "Package": "ddgraph", "Version": "1.18.0", "Depends": [ "graph", "methods", "Rcpp" ], "Imports": [ "bnlearn (>= 2.8)", "gtools", "pcalg", "RColorBrewer", "plotrix", "MASS" ], "LinkingTo": [ "Rcpp" ], "Suggests": [ "Rgraphviz", "e1071", "ROCR", "testthat" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "d8639f4ebf3c956e04a130fed60a3683", "NeedsCompilation": "yes", "Title": "Distinguish direct and indirect interactions with Graphical Modelling", "Description": "Distinguish direct from indirect interactions in gene regulation and infer combinatorial code from highly correlated variables such as transcription factor binding profiles. The package implements the Neighbourhood Consistent PC algorithm (NCPC) and draws Direct Dependence Graphs to represent dependence structure around a target variable. The package also provides a unified interface to other Graphical Modelling (Bayesian Network) packages for distinguishing direct and indirect interactions.", "biocViews": [ "GraphAndNetwork", "Software" ], "Author": "Robert Stojnic", "Maintainer": "Robert Stojnic ", "source.ver": "src/contrib/ddgraph_1.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ddgraph_1.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ddgraph_1.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ddgraph_1.18.0.tgz", "vignettes": [ "vignettes/ddgraph/inst/doc/ddgraph.pdf" ], "vignetteTitles": [ "Overview of the 'ddgraph' package" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ddgraph/inst/doc/ddgraph.R" ] }, "debrowser": { "Package": "debrowser", "Version": "1.3.11", "Depends": [ "R (>= 3.3.0)", "shiny", "ggvis", "jsonlite", "shinyjs" ], "Imports": [ "DT", "ggplot2", "RColorBrewer", "annotate", "gplots", "AnnotationDbi", "DESeq2", "DOSE", "igraph", "grDevices", "graphics", "stats", "utils", "GenomicRanges", "IRanges", "S4Vectors", "SummarizedExperiment", "stringi", "reshape2", "baySeq", "d3heatmap", "org.Hs.eg.db", "org.Mm.eg.db", "limma", "edgeR", "clusterProfiler", "V8", "methods", "sva", "shinydashboard", "devtools", "RCurl" ], "Suggests": [ "testthat", "rmarkdown", "knitr", "R.rsp" ], "License": "GPL-3 + file LICENSE", "MD5sum": "371477cf245d9d9331fe5d79e7d3182a", "NeedsCompilation": "no", "Title": "debrowser: Interactive Differential Expresion Analysis Browser", "Description": "Bioinformatics platform containing interactive plots and tables for differential gene and region expression studies. Allows visualizing expression data much more deeply in an interactive and faster way. By changing the parameters, users can easily discover different parts of the data that like never have been done before. Manually creating and looking these plots takes time. With DEBrowser users can prepare plots without writing any code. Differential expression, PCA and clustering analysis are made on site and the results are shown in various plots such as scatter, bar, box, volcano, ma plots and Heatmaps.", "biocViews": [ "ChIPSeq", "Clustering", "DifferentialExpression", "GeneExpression", "RNASeq", "Sequencing", "Software" ], "Author": "Alper Kucukural , Manuel Garber ", "Maintainer": "Alper Kucukural ", "URL": "https://github.com/UMMS-Biocore/debrowser", "VignetteBuilder": "knitr, R.rsp", "BugReports": "https://github.com/UMMS-Biocore/debrowser/issues/new", "source.ver": "src/contrib/debrowser_1.3.11.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/debrowser_1.3.11.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/debrowser_1.3.11.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/debrowser_1.3.11.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/debrowser/inst/doc/DEBrowser.R" ], "htmlDocs": [ "vignettes/debrowser/inst/doc/DEBrowser.html" ], "htmlTitles": [ "DEBrowser Vignette" ] }, "DECIPHER": { "Package": "DECIPHER", "Version": "2.2.0", "Depends": [ "R (>= 3.3.0)", "Biostrings (>= 2.35.12)", "RSQLite (>= 1.0.0)", "stats", "parallel" ], "Imports": [ "methods", "DBI", "S4Vectors", "IRanges", "XVector" ], "LinkingTo": [ "Biostrings", "S4Vectors", "IRanges", "XVector" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "0f9d68af17d92ba6a8e4cd192764bf43", "NeedsCompilation": "yes", "Title": "Tools for curating, analyzing, and manipulating biological sequences", "Description": "A toolset for deciphering and managing biological sequences.", "biocViews": [ "Alignment", "Clustering", "DataImport", "Genetics", "Microarray", "Microbiome", "QualityControl", "Sequencing", "Software", "Visualization", "WholeGenome", "qPCR" ], "Author": "Erik Wright", "Maintainer": "Erik Wright ", "source.ver": "src/contrib/DECIPHER_2.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/DECIPHER_2.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/DECIPHER_2.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/DECIPHER_2.2.0.tgz", "vignettes": [ "vignettes/DECIPHER/inst/doc/ArtOfAlignmentInR.pdf", "vignettes/DECIPHER/inst/doc/DECIPHERing.pdf", "vignettes/DECIPHER/inst/doc/DesignMicroarray.pdf", "vignettes/DECIPHER/inst/doc/DesignPrimers.pdf", "vignettes/DECIPHER/inst/doc/DesignProbes.pdf", "vignettes/DECIPHER/inst/doc/DesignSignatures.pdf", "vignettes/DECIPHER/inst/doc/FindChimeras.pdf" ], "vignetteTitles": [ "The Art of Multiple Sequence Alignment in R", "Getting Started DECIPHERing", "Design Microarray Probes", "Design Group-Specific Primers", "Design Group-Specific FISH Probes", "Design Primers That Yield Group-Specific Signatures", "Finding Chimeric Sequences" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/DECIPHER/inst/doc/ArtOfAlignmentInR.R", "vignettes/DECIPHER/inst/doc/DECIPHERing.R", "vignettes/DECIPHER/inst/doc/DesignMicroarray.R", "vignettes/DECIPHER/inst/doc/DesignPrimers.R", "vignettes/DECIPHER/inst/doc/DesignProbes.R", "vignettes/DECIPHER/inst/doc/DesignSignatures.R", "vignettes/DECIPHER/inst/doc/FindChimeras.R" ] }, "DeconRNASeq": { "Package": "DeconRNASeq", "Version": "1.16.0", "Depends": [ "R (>= 2.14.0)", "limSolve", "pcaMethods", "ggplot2", "grid" ], "License": "GPL-2", "MD5sum": "41c433788428d5a40231eac1872c210f", "NeedsCompilation": "no", "Title": "Deconvolution of Heterogeneous Tissue Samples for mRNA-Seq data", "Description": "DeconSeq is an R package for deconvolution of heterogeneous tissues based on mRNA-Seq data. It modeled expression levels from heterogeneous cell populations in mRNA-Seq as the weighted average of expression from different constituting cell types and predicted cell type proportions of single expression profiles.", "biocViews": [ "DifferentialExpression", "Software" ], "Author": "Ting Gong Joseph D. Szustakowski ", "Maintainer": "Ting Gong ", "source.ver": "src/contrib/DeconRNASeq_1.16.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/DeconRNASeq_1.16.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/DeconRNASeq_1.16.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/DeconRNASeq_1.16.0.tgz", "vignettes": [ "vignettes/DeconRNASeq/inst/doc/DeconRNASeq.pdf" ], "vignetteTitles": [ "DeconRNASeq Demo" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/DeconRNASeq/inst/doc/DeconRNASeq.R" ] }, "DEDS": { "Package": "DEDS", "Version": "1.48.0", "Depends": [ "R (>= 1.7.0)" ], "License": "LGPL", "Archs": "i386, x64", "MD5sum": "a2c0a125be535aef7fe22dec6bdd95a9", "NeedsCompilation": "yes", "Title": "Differential Expression via Distance Summary for Microarray Data", "Description": "This library contains functions that calculate various statistics of differential expression for microarray data, including t statistics, fold change, F statistics, SAM, moderated t and F statistics and B statistics. It also implements a new methodology called DEDS (Differential Expression via Distance Summary), which selects differentially expressed genes by integrating and summarizing a set of statistics using a weighted distance approach.", "biocViews": [ "DifferentialExpression", "Microarray", "Software" ], "Author": "Yuanyuan Xiao , Jean Yee Hwa Yang .", "Maintainer": "Yuanyuan Xiao ", "source.ver": "src/contrib/DEDS_1.48.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/DEDS_1.48.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/DEDS_1.48.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/DEDS_1.48.0.tgz", "vignettes": [ "vignettes/DEDS/inst/doc/DEDS.pdf" ], "vignetteTitles": [ "DEDS.pdf" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/DEDS/inst/doc/DEDS.R" ] }, "DeepBlueR": { "Package": "DeepBlueR", "Version": "1.0.11", "Depends": [ "R (>= 3.3)", "XML", "RCurl" ], "Imports": [ "GenomicRanges", "data.table", "stringr", "diffr", "dplyr", "methods", "rjson", "utils", "R.utils", "foreach", "withr", "rtracklayer", "GenomeInfoDb", "settings", "filehash" ], "Suggests": [ "knitr", "rmarkdown", "LOLA", "Gviz", "gplots", "ggplot2", "tidyr", "RColorBrewer", "matrixStats" ], "License": "GPL (>=2.0)", "MD5sum": "b978426d83186a3a7c8622cd65ac951b", "NeedsCompilation": "no", "Title": "DeepBlueR", "Description": "Accessing the DeepBlue Epigenetics Data Server through R.", "biocViews": [ "Annotation", "CpGIsland", "DNAMethylation", "DataImport", "DataRepresentation", "Epigenetics", "GeneRegulation", "GenomeAnnotation", "Preprocessing", "Software", "ThirdPartyClient" ], "Author": "Felipe Albrecht, Markus List", "Maintainer": "Felipe Albrecht , Markus List ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/DeepBlueR_1.0.11.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/DeepBlueR_1.0.11.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/DeepBlueR_1.0.11.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/DeepBlueR_1.0.11.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/DeepBlueR/inst/doc/DeepBlueR.R" ], "htmlDocs": [ "vignettes/DeepBlueR/inst/doc/DeepBlueR.html" ], "htmlTitles": [ "The DeepBlue epigenomic data server - R package" ] }, "deepSNV": { "Package": "deepSNV", "Version": "1.20.0", "Depends": [ "R (>= 2.13.0)", "methods", "graphics", "parallel", "Rhtslib", "IRanges", "GenomicRanges", "SummarizedExperiment", "Biostrings", "VGAM", "VariantAnnotation (>= 1.13.44)" ], "Imports": [ "Rhtslib" ], "LinkingTo": [ "Rhtslib" ], "Suggests": [ "RColorBrewer", "knitr", "rmarkdown" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "7aad92032df4ac6702d55a26586dcea0", "NeedsCompilation": "yes", "Title": "Detection of subclonal SNVs in deep sequencing data.", "Description": "This package provides provides quantitative variant callers for detecting subclonal mutations in ultra-deep (>=100x coverage) sequencing experiments. The deepSNV algorithm is used for a comparative setup with a control experiment of the same loci and uses a beta-binomial model and a likelihood ratio test to discriminate sequencing errors and subclonal SNVs. The shearwater algorithm computes a Bayes classifier based on a beta-binomial model for variant calling with multiple samples for precisely estimating model parameters such as local error rates and dispersion and prior knowledge, e.g. from variation data bases such as COSMIC.", "biocViews": [ "DataImport", "GeneticVariability", "Genetics", "SNP", "Sequencing", "Software" ], "Author": "Niko Beerenwinkel [ths], David Jones [ctb], Inigo Martincorena [ctb], Moritz Gerstung [aut, cre]", "Maintainer": "Moritz Gerstung ", "URL": "http://github.com/mg14/deepSNV", "VignetteBuilder": "knitr", "source.ver": "src/contrib/deepSNV_1.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/deepSNV_1.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/deepSNV_1.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/deepSNV_1.20.0.tgz", "vignettes": [ "vignettes/deepSNV/inst/doc/deepSNV.pdf", "vignettes/deepSNV/inst/doc/shearwater.pdf" ], "vignetteTitles": [ "An R package for detecting low frequency variants in deep sequencing experiments", "Subclonal variant calling with multiple samples and prior knowledge using shearwater" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/deepSNV/inst/doc/deepSNV.R", "vignettes/deepSNV/inst/doc/shearwater.R" ], "suggestsMe": [ "GenomicFiles" ] }, "DEFormats": { "Package": "DEFormats", "Version": "1.2.0", "Imports": [ "checkmate", "DESeq2", "edgeR (>= 3.13.4)", "GenomicRanges", "methods", "stats", "SummarizedExperiment" ], "Suggests": [ "BiocStyle (>= 1.8.0)", "knitr", "rmarkdown", "testthat" ], "License": "GPL-3", "MD5sum": "add2e743a8436a75b6df27d7518a3462", "NeedsCompilation": "no", "Title": "Differential gene expression data formats converter", "Description": "Covert between different data formats used by differential gene expression analysis tools.", "biocViews": [ "DifferentialExpression", "GeneExpression", "RNASeq", "Sequencing", "Software", "Transcription" ], "Author": "Andrzej Oleś", "Maintainer": "Andrzej Oleś ", "URL": "https://github.com/aoles/DEFormats", "VignetteBuilder": "knitr", "BugReports": "https://github.com/aoles/DEFormats/issues", "source.ver": "src/contrib/DEFormats_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/DEFormats_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/DEFormats_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/DEFormats_1.2.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/DEFormats/inst/doc/DEFormats.R" ], "htmlDocs": [ "vignettes/DEFormats/inst/doc/DEFormats.html" ], "htmlTitles": [ "Differential gene expression data formats converter" ], "importsMe": [ "regionReport" ] }, "DEGraph": { "Package": "DEGraph", "Version": "1.26.0", "Depends": [ "R (>= 2.10.0)", "R.utils" ], "Imports": [ "graph", "KEGGgraph", "lattice", "mvtnorm", "R.methodsS3", "RBGL", "Rgraphviz", "rrcov", "NCIgraph" ], "Suggests": [ "corpcor", "fields", "graph", "KEGGgraph", "lattice", "marray", "RBGL", "rrcov", "Rgraphviz", "NCIgraph" ], "License": "GPL-3", "MD5sum": "dbcbe55d28126563ba4819b5d2e00f92", "NeedsCompilation": "no", "Title": "Two-sample tests on a graph", "Description": "DEGraph implements recent hypothesis testing methods which directly assess whether a particular gene network is differentially expressed between two conditions. This is to be contrasted with the more classical two-step approaches which first test individual genes, then test gene sets for enrichment in differentially expressed genes. These recent methods take into account the topology of the network to yield more powerful detection procedures. DEGraph provides methods to easily test all KEGG pathways for differential expression on any gene expression data set and tools to visualize the results.", "biocViews": [ "DecisionTree", "DifferentialExpression", "GraphAndNetwork", "Microarray", "Network", "NetworkEnrichment", "Software" ], "Author": "Laurent Jacob, Pierre Neuvial and Sandrine Dudoit", "Maintainer": "Laurent Jacob ", "source.ver": "src/contrib/DEGraph_1.26.0.tar.gz", "vignettes": [ "vignettes/DEGraph/inst/doc/DEGraph.pdf" ], "vignetteTitles": [ "DEGraph: differential expression testing for gene networks" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/DEGraph/inst/doc/DEGraph.R" ], "suggestsMe": [ "ToPASeq" ] }, "DEGreport": { "Package": "DEGreport", "Version": "1.10.1", "Depends": [ "R (>= 3.2.0)", "quantreg" ], "Imports": [ "utils", "methods", "ggplot2", "Nozzle.R1", "coda", "edgeR", "cluster", "logging", "dplyr", "tidyr", "reshape", "pheatmap", "grid", "gridExtra", "knitr", "grDevices", "stats" ], "Suggests": [ "biomaRt", "RUnit", "BiocStyle", "BiocGenerics", "org.Hs.eg.db", "DESeq2", "AnnotationDbi", "BiocParallel" ], "License": "MIT + file LICENSE", "MD5sum": "10cf54a93f65e01f42a9a45583e08fe4", "NeedsCompilation": "no", "Title": "Report of DEG analysis", "Description": "Creation of a HTML report of differential expression analyses of count data. It integrates some of the code mentioned in DESeq2 and edgeR vignettes, and report a ranked list of genes according to the fold changes mean and variability for each selected gene.", "biocViews": [ "DifferentialExpression", "GeneExpression", "RNASeq", "ReportWriting", "Software", "Visualization" ], "Author": "Lorena Pantano", "Maintainer": "Lorena Pantano ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/DEGreport_1.10.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/DEGreport_1.10.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/DEGreport_1.10.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/DEGreport_1.10.1.tgz", "vignettes": [ "vignettes/DEGreport/inst/doc/DEGreport.pdf" ], "vignetteTitles": [ "DEGreport" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/DEGreport/inst/doc/DEGreport.R" ] }, "DEGseq": { "Package": "DEGseq", "Version": "1.28.0", "Depends": [ "R (>= 2.8.0)", "qvalue", "samr", "methods" ], "Imports": [ "graphics", "grDevices", "methods", "stats", "utils" ], "License": "LGPL (>=2)", "Archs": "i386, x64", "MD5sum": "485ada471202bc479e4d8bc7f972ecdd", "NeedsCompilation": "yes", "Title": "Identify Differentially Expressed Genes from RNA-seq data", "Description": "DEGseq is an R package to identify differentially expressed genes from RNA-Seq data.", "biocViews": [ "DifferentialExpression", "GeneExpression", "Preprocessing", "RNASeq", "Software" ], "Author": "Likun Wang and Xi Wang .", "Maintainer": "Likun Wang ", "source.ver": "src/contrib/DEGseq_1.28.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/DEGseq_1.28.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/DEGseq_1.28.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/DEGseq_1.28.0.tgz", "vignettes": [ "vignettes/DEGseq/inst/doc/DEGseq.pdf" ], "vignetteTitles": [ "DEGseq" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/DEGseq/inst/doc/DEGseq.R" ] }, "deltaGseg": { "Package": "deltaGseg", "Version": "1.14.0", "Depends": [ "R (>= 2.15.1)", "methods", "ggplot2", "changepoint", "wavethresh", "tseries", "pvclust", "fBasics", "grid", "reshape", "scales" ], "Suggests": [ "knitr" ], "License": "GPL-2", "MD5sum": "4670d658d5ef32692faa61ffc9c303f4", "NeedsCompilation": "no", "Title": "deltaGseg", "Description": "Identifying distinct subpopulations through multiscale time series analysis", "biocViews": [ "Clustering", "Proteomics", "Software", "TimeCourse", "Visualization" ], "Author": "Diana Low, Efthymios Motakis", "Maintainer": "Diana Low ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/deltaGseg_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/deltaGseg_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/deltaGseg_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/deltaGseg_1.14.0.tgz", "vignettes": [ "vignettes/deltaGseg/inst/doc/deltaGseg.pdf" ], "vignetteTitles": [ "deltaGseg" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/deltaGseg/inst/doc/deltaGseg.R" ] }, "DeMAND": { "Package": "DeMAND", "Version": "1.4.0", "Depends": [ "R (>= 2.14.0)", "KernSmooth", "methods" ], "License": "file LICENSE", "MD5sum": "e9f26a5c12beb98bebb90c7b25bd0699", "NeedsCompilation": "no", "Title": "DeMAND", "Description": "DEMAND predicts Drug MoA by interrogating a cell context specific regulatory network with a small number (N >= 6) of compound-induced gene expression signatures, to elucidate specific proteins whose interactions in the network is dysregulated by the compound.", "biocViews": [ "GeneExpression", "Network", "NetworkEnrichment", "Software", "StatisticalMethod", "SystemsBiology" ], "Author": "Jung Hoon Woo , Yishai Shimoni ", "Maintainer": "Jung Hoon Woo , Mariano Alvarez ", "source.ver": "src/contrib/DeMAND_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/DeMAND_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/DeMAND_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/DeMAND_1.4.0.tgz", "vignettes": [ "vignettes/DeMAND/inst/doc/DeMAND.pdf" ], "vignetteTitles": [ "Using DeMAND" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/DeMAND/inst/doc/DeMAND.R" ] }, "derfinder": { "Package": "derfinder", "Version": "1.8.5", "Depends": [ "R(>= 3.2)" ], "Imports": [ "AnnotationDbi (>= 1.27.9)", "BiocParallel", "bumphunter (>= 1.9.2)", "derfinderHelper (>= 1.1.0)", "GenomeInfoDb (>= 1.3.3)", "GenomicAlignments", "GenomicFeatures", "GenomicFiles", "GenomicRanges (>= 1.17.40)", "Hmisc", "IRanges (>= 2.3.23)", "methods", "qvalue (>= 1.99.0)", "Rsamtools (>= 1.25.0)", "rtracklayer", "S4Vectors (>= 0.9.38)" ], "Suggests": [ "BiocStyle", "biovizBase", "devtools (>= 1.6)", "derfinderData (>= 0.99.0)", "derfinderPlot", "DESeq2", "ggplot2", "knitcitations (>= 1.0.1)", "knitr (>= 1.6)", "limma", "rmarkdown (>= 0.3.3)", "testthat", "TxDb.Hsapiens.UCSC.hg19.knownGene" ], "License": "Artistic-2.0", "MD5sum": "51135da5b204d8417d4a018779c390e3", "NeedsCompilation": "no", "Title": "Annotation-agnostic differential expression analysis of RNA-seq data at base-pair resolution via the DER Finder approach", "Description": "This package provides functions for annotation-agnostic differential expression analysis of RNA-seq data. Two implementations of the DER Finder approach are included in this package: (1) single base-level F-statistics and (2) DER identification at the expressed regions-level. The DER Finder approach can also be used to identify differentially bounded ChIP-seq peaks.", "biocViews": [ "ChIPSeq", "DifferentialExpression", "DifferentialPeakCalling", "RNASeq", "Sequencing", "Software" ], "Author": "Leonardo Collado-Torres [aut, cre], Alyssa C. Frazee [ctb], Andrew E. Jaffe [aut], Jeffrey T. Leek [aut, ths]", "Maintainer": "Leonardo Collado-Torres ", "URL": "https://github.com/lcolladotor/derfinder", "VignetteBuilder": "knitr", "BugReports": "https://support.bioconductor.org/t/derfinder/", "source.ver": "src/contrib/derfinder_1.8.5.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/derfinder_1.8.5.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/derfinder_1.8.5.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/derfinder_1.8.5.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/derfinder/inst/doc/derfinder-quickstart.R", "vignettes/derfinder/inst/doc/derfinder-users-guide.R" ], "htmlDocs": [ "vignettes/derfinder/inst/doc/derfinder-quickstart.html", "vignettes/derfinder/inst/doc/derfinder-users-guide.html" ], "htmlTitles": [ "derfinder quick start guide", "derfinder users guide" ], "importsMe": [ "derfinderPlot", "recount", "regionReport" ] }, "derfinderHelper": { "Package": "derfinderHelper", "Version": "1.8.1", "Depends": [ "R(>= 3.2.2)" ], "Imports": [ "IRanges (>= 1.99.27)", "Matrix", "methods", "S4Vectors (>= 0.2.2)" ], "Suggests": [ "devtools (>= 1.6)", "knitcitations (>= 1.0.1)", "knitr (>= 1.6)", "BiocStyle", "rmarkdown (>= 0.3.3)", "testthat" ], "License": "Artistic-2.0", "MD5sum": "f98a084de0873140da58aa1461596abd", "NeedsCompilation": "no", "Title": "derfinder helper package", "Description": "Helper package for speeding up the derfinder package when using multiple cores.", "biocViews": [ "DifferentialExpression", "RNASeq", "Sequencing", "Software" ], "Author": "Leonardo Collado-Torres [aut, cre], Andrew E. Jaffe [aut], Jeffrey T. Leek [aut, ths]", "Maintainer": "Leonardo Collado-Torres ", "URL": "https://github.com/leekgroup/derfinderHelper", "VignetteBuilder": "knitr", "BugReports": "https://support.bioconductor.org/t/derfinderHelper", "source.ver": "src/contrib/derfinderHelper_1.8.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/derfinderHelper_1.8.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/derfinderHelper_1.8.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/derfinderHelper_1.8.1.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/derfinderHelper/inst/doc/derfinderHelper.R" ], "htmlDocs": [ "vignettes/derfinderHelper/inst/doc/derfinderHelper.html" ], "htmlTitles": [ "Introduction to derfinderHelper" ], "importsMe": [ "derfinder" ] }, "derfinderPlot": { "Package": "derfinderPlot", "Version": "1.8.1", "Depends": [ "R(>= 3.2)" ], "Imports": [ "derfinder (>= 1.1.0)", "GenomeInfoDb (>= 1.3.3)", "GenomicFeatures", "GenomicRanges (>= 1.17.40)", "ggbio (>= 1.13.13)", "ggplot2", "graphics", "grDevices", "IRanges (>= 1.99.28)", "limma", "methods", "plyr", "RColorBrewer", "reshape2", "S4Vectors (>= 0.9.38)", "scales", "utils" ], "Suggests": [ "biovizBase", "bumphunter (>= 1.7.6)", "derfinderData (>= 0.99.0)", "devtools (>= 1.6)", "knitcitations (>= 1.0.1)", "knitr (>= 1.6)", "BiocStyle", "org.Hs.eg.db", "rmarkdown (>= 0.3.3)", "testthat", "TxDb.Hsapiens.UCSC.hg19.knownGene" ], "License": "Artistic-2.0", "MD5sum": "f689ad03127b3e1d391feceba0ce0631", "NeedsCompilation": "no", "Title": "Plotting functions for derfinder", "Description": "This package provides plotting functions for results from the derfinder package.", "biocViews": [ "DifferentialExpression", "RNASeq", "Sequencing", "Software", "Visualization" ], "Author": "Leonardo Collado-Torres [aut, cre], Andrew E. Jaffe [aut], Jeffrey T. Leek [aut, ths]", "Maintainer": "Leonardo Collado-Torres ", "URL": "https://github.com/leekgroup/derfinderPlot", "VignetteBuilder": "knitr", "BugReports": "https://support.bioconductor.org/t/derfinderPlot", "source.ver": "src/contrib/derfinderPlot_1.8.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/derfinderPlot_1.8.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/derfinderPlot_1.8.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/derfinderPlot_1.8.1.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/derfinderPlot/inst/doc/derfinderPlot.R" ], "htmlDocs": [ "vignettes/derfinderPlot/inst/doc/derfinderPlot.html" ], "htmlTitles": [ "Introduction to derfinderPlot" ], "suggestsMe": [ "derfinder", "regionReport" ] }, "DESeq": { "Package": "DESeq", "Version": "1.26.0", "Depends": [ "BiocGenerics (>= 0.7.5)", "Biobase (>= 2.21.7)", "locfit", "lattice" ], "Imports": [ "genefilter", "geneplotter", "methods", "MASS", "RColorBrewer" ], "Suggests": [ "pasilla (>= 0.2.10)", "vsn", "gplots" ], "License": "GPL (>= 3)", "Archs": "i386, x64", "MD5sum": "192656a424ff0d1e1f60dff8fc5bb28c", "NeedsCompilation": "yes", "Title": "Differential gene expression analysis based on the negative binomial distribution", "Description": "Estimate variance-mean dependence in count data from high-throughput sequencing assays and test for differential expression based on a model using the negative binomial distribution", "biocViews": [ "ChIPSeq", "DifferentialExpression", "RNASeq", "SAGE", "Sequencing", "Software" ], "Author": "Simon Anders, EMBL Heidelberg ", "Maintainer": "Simon Anders ", "URL": "http://www-huber.embl.de/users/anders/DESeq", "source.ver": "src/contrib/DESeq_1.26.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/DESeq_1.26.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/DESeq_1.26.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/DESeq_1.26.0.tgz", "vignettes": [ "vignettes/DESeq/inst/doc/DESeq.pdf" ], "vignetteTitles": [ "Analysing RNA-Seq data with the \"DESeq\" package" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/DESeq/inst/doc/DESeq.R" ], "dependsOnMe": [ "DBChIP", "EDDA", "metaseqR", "Polyfit", "SeqGSEA", "TCC", "tRanslatome" ], "importsMe": [ "ampliQueso", "ArrayExpressHTS", "DEsubs", "easyRNASeq", "EDASeq", "EDDA", "gCMAP", "HTSFilter", "rnaSeqMap", "ToPASeq" ], "suggestsMe": [ "BitSeq", "compcodeR", "dexus", "DiffBind", "ELBOW", "gage", "genefilter", "IHWpaper", "oneChannelGUI", "PROPER", "regionReport", "SSPA", "XBSeq" ] }, "DESeq2": { "Package": "DESeq2", "Version": "1.14.1", "Depends": [ "S4Vectors (>= 0.9.25)", "IRanges", "GenomicRanges", "SummarizedExperiment (>= 1.1.6)" ], "Imports": [ "BiocGenerics (>= 0.7.5)", "Biobase", "BiocParallel", "genefilter", "methods", "locfit", "geneplotter", "ggplot2", "Hmisc", "Rcpp (>= 0.11.0)" ], "LinkingTo": [ "Rcpp", "RcppArmadillo" ], "Suggests": [ "testthat", "knitr", "BiocStyle", "vsn", "pheatmap", "RColorBrewer", "airway", "IHW", "tximport", "tximportData", "readr", "pasilla (>= 0.2.10)" ], "License": "LGPL (>= 3)", "Archs": "i386, x64", "MD5sum": "d1c433056295927a6700046e282bcccd", "NeedsCompilation": "yes", "Title": "Differential gene expression analysis based on the negative binomial distribution", "Description": "Estimate variance-mean dependence in count data from high-throughput sequencing assays and test for differential expression based on a model using the negative binomial distribution.", "biocViews": [ "ChIPSeq", "DifferentialExpression", "GeneExpression", "RNASeq", "SAGE", "Sequencing", "Software", "Transcription" ], "Author": "Michael Love, Simon Anders, Wolfgang Huber", "Maintainer": "Michael Love ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/DESeq2_1.14.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/DESeq2_1.14.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/DESeq2_1.14.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/DESeq2_1.14.1.tgz", "vignettes": [ "vignettes/DESeq2/inst/doc/DESeq2.pdf" ], "vignetteTitles": [ "Analyzing RNA-seq data with the \"DESeq2\" package" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/DESeq2/inst/doc/DESeq2.R" ], "dependsOnMe": [ "ASpli", "DChIPRep", "DEXSeq", "FourCSeq", "MLSeq", "rgsepd", "TCC", "XBSeq" ], "importsMe": [ "anamiR", "debrowser", "DEFormats", "DEsubs", "DiffBind", "eegc", "EnrichmentBrowser", "FourCSeq", "GenoGAM", "Glimma", "HTSFilter", "IHWpaper", "isomiRs", "JunctionSeq", "pcaExplorer", "regionReport", "ReportingTools", "SNPhood", "systemPipeR", "ToPASeq" ], "suggestsMe": [ "biobroom", "BiocGenerics", "compcodeR", "DEGreport", "derfinder", "diffloop", "gage", "GenomicAlignments", "GenomicRanges", "IHW", "JctSeqData", "oneChannelGUI", "phyloseq", "recount", "RUVSeq", "scran", "Single.mTEC.Transcriptomes", "subSeq", "tximport", "variancePartition" ] }, "destiny": { "Package": "destiny", "Version": "2.0.8", "Depends": [ "R (>= 3.2.0)" ], "Imports": [ "methods", "graphics", "grDevices", "utils", "stats", "Matrix", "Rcpp (>= 0.10.3)", "RcppEigen", "Biobase", "BiocGenerics", "Hmisc", "FNN", "VIM", "proxy", "igraph", "smoother", "scales", "scatterplot3d" ], "LinkingTo": [ "Rcpp", "RcppEigen" ], "Suggests": [ "ggplot2", "nbconvertR" ], "Enhances": [ "rgl" ], "License": "GPL", "Archs": "i386, x64", "MD5sum": "dc6410f9206cc0a2cc637f1089e56d1b", "NeedsCompilation": "yes", "Title": "Creates diffusion maps", "Description": "Create and plot diffusion maps.", "biocViews": [ "CellBasedAssays", "CellBiology", "Clustering", "Software", "Visualization" ], "Author": "Philipp Angerer [cre, aut], Laleh Haghverdi [ctb], Maren Büttner [ctb], Fabian Theis [ctb], Carsten Marr [ctb], Florian Büttner [ctb]", "Maintainer": "Philipp Angerer ", "SystemRequirements": "C++11", "VignetteBuilder": "nbconvertR", "source.ver": "src/contrib/destiny_2.0.8.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/destiny_2.0.8.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/destiny_2.0.8.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/destiny_2.0.8.tgz", "vignettes": [ "vignettes/destiny/inst/doc/Diffusion-Map-recap.pdf", "vignettes/destiny/inst/doc/Diffusion-Maps.pdf", "vignettes/destiny/inst/doc/DPT.pdf", "vignettes/destiny/inst/doc/Global-Sigma.pdf" ], "vignetteTitles": [ "Diffusion-Map-recap.pdf", "Diffusion-Maps.pdf", "DPT.pdf", "Global-Sigma.pdf" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "importsMe": [ "cytofkit" ], "suggestsMe": [ "scater" ] }, "DEsubs": { "Package": "DEsubs", "Version": "1.0.2", "Depends": [ "R (>= 3.3)", "locfit" ], "Imports": [ "graph", "igraph", "RBGL", "circlize", "limma", "edgeR", "samr", "EBSeq", "NBPSeq", "DESeq", "stats", "grDevices", "graphics", "pheatmap", "utils", "ggplot2", "Matrix", "jsonlite", "tools", "DESeq2", "methods" ], "Suggests": [ "RUnit", "BiocGenerics", "knitr" ], "License": "GPL-3", "MD5sum": "de640952a51c0358e8a4125a15613dd0", "NeedsCompilation": "no", "Title": "DEsubs: an R package for flexible identification of differentially expressed subpathways using RNA-seq expression experiments", "Description": "DEsubs is a network-based systems biology package that extracts disease-perturbed subpathways within a pathway network as recorded by RNA-seq experiments. It contains an extensive and customizable framework covering a broad range of operation modes at all stages of the subpathway analysis, enabling a case-specific approach. The operation modes refer to the pathway network construction and processing, the subpathway extraction, visualization and enrichment analysis with regard to various biological and pharmacological features. Its capabilities render it a tool-guide for both the modeler and experimentalist for the identification of more robust systems-level biomarkers for complex diseases.", "biocViews": [ "DifferentialExpression", "GeneExpression", "GraphAndNetwork", "KEGG", "Network", "NetworkEnrichment", "Normalization", "Pathways", "RNASeq", "Software", "SystemsBiology" ], "Author": "Aristidis G. Vrahatis and Panos Balomenos", "Maintainer": "Aristidis G. Vrahatis and Panos Balomenos ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/DEsubs_1.0.2.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/DEsubs_1.0.2.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/DEsubs_1.0.2.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/DEsubs_1.0.2.tgz", "vignettes": [ "vignettes/DEsubs/inst/doc/DEsubs.pdf" ], "vignetteTitles": [ "DEsubs" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/DEsubs/inst/doc/DEsubs.R" ] }, "DEXSeq": { "Package": "DEXSeq", "Version": "1.20.2", "Depends": [ "BiocParallel", "Biobase", "SummarizedExperiment", "IRanges (>= 2.5.17)", "GenomicRanges (>= 1.23.7)", "DESeq2 (>= 1.9.11)", "AnnotationDbi", "RColorBrewer", "S4Vectors" ], "Imports": [ "BiocGenerics", "biomaRt", "hwriter", "methods", "stringr", "Rsamtools", "statmod", "geneplotter", "genefilter" ], "Suggests": [ "GenomicFeatures (>= 1.13.29)", "pasilla (>= 0.2.22)", "parathyroidSE", "BiocStyle", "knitr" ], "License": "GPL (>= 3)", "MD5sum": "fafc5f3f3ef32033f11e1347bd318a7f", "NeedsCompilation": "no", "Title": "Inference of differential exon usage in RNA-Seq", "Description": "The package is focused on finding differential exon usage using RNA-seq exon counts between samples with different experimental designs. It provides functions that allows the user to make the necessary statistical tests based on a model that uses the negative binomial distribution to estimate the variance between biological replicates and generalized linear models for testing. The package also provides functions for the visualization and exploration of the results.", "biocViews": [ "AlternativeSplicing", "DifferentialExpression", "DifferentialSplicing", "GeneExpression", "RNASeq", "Sequencing", "Software", "Visualization" ], "Author": "Simon Anders and Alejandro Reyes ", "Maintainer": "Alejandro Reyes ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/DEXSeq_1.20.2.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/DEXSeq_1.20.2.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/DEXSeq_1.20.2.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/DEXSeq_1.20.2.tgz", "vignettes": [ "vignettes/DEXSeq/inst/doc/DEXSeq.pdf" ], "vignetteTitles": [ "Analyzing RNA-seq data for differential exon usage with the \"DEXSeq\" package" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/DEXSeq/inst/doc/DEXSeq.R" ], "dependsOnMe": [ "ASpli" ], "suggestsMe": [ "GenomicRanges", "JctSeqData", "oneChannelGUI", "pasilla", "subSeq" ] }, "dexus": { "Package": "dexus", "Version": "1.14.0", "Depends": [ "R (>= 2.15)", "methods", "BiocGenerics" ], "Suggests": [ "parallel", "statmod", "stats", "DESeq", "RColorBrewer" ], "License": "LGPL (>= 2.0)", "Archs": "i386, x64", "MD5sum": "43c91f240daaeddbaaaa1e73bd1d1ffe", "NeedsCompilation": "yes", "Title": "DEXUS - Identifying Differential Expression in RNA-Seq Studies with Unknown Conditions or without Replicates", "Description": "DEXUS identifies differentially expressed genes in RNA-Seq data under all possible study designs such as studies without replicates, without sample groups, and with unknown conditions. DEXUS works also for known conditions, for example for RNA-Seq data with two or multiple conditions. RNA-Seq read count data can be provided both by the S4 class Count Data Set and by read count matrices. Differentially expressed transcripts can be visualized by heatmaps, in which unknown conditions, replicates, and samples groups are also indicated. This software is fast since the core algorithm is written in C. For very large data sets, a parallel version of DEXUS is provided in this package. DEXUS is a statistical model that is selected in a Bayesian framework by an EM algorithm. DEXUS does not need replicates to detect differentially expressed transcripts, since the replicates (or conditions) are estimated by the EM method for each transcript. The method provides an informative/non-informative value to extract differentially expressed transcripts at a desired significance level or power.", "biocViews": [ "CellBiology", "Classification", "DifferentialExpression", "GeneExpression", "QualityControl", "RNASeq", "Sequencing", "Software" ], "Author": "Guenter Klambauer", "Maintainer": "Guenter Klambauer ", "source.ver": "src/contrib/dexus_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/dexus_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/dexus_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/dexus_1.14.0.tgz", "vignettes": [ "vignettes/dexus/inst/doc/dexus.pdf" ], "vignetteTitles": [ "dexus: Manual for the R package" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/dexus/inst/doc/dexus.R" ] }, "DFP": { "Package": "DFP", "Version": "1.32.0", "Depends": [ "methods", "Biobase (>= 2.5.5)" ], "License": "GPL-2", "MD5sum": "fce0da46dd5867be35b6974c21ff981f", "NeedsCompilation": "no", "Title": "Gene Selection", "Description": "This package provides a supervised technique able to identify differentially expressed genes, based on the construction of \\emph{Fuzzy Patterns} (FPs). The Fuzzy Patterns are built by means of applying 3 Membership Functions to discretized gene expression values.", "biocViews": [ "DifferentialExpression", "Microarray", "Software" ], "Author": "R. Alvarez-Gonzalez, D. Glez-Pena, F. Diaz, F. Fdez-Riverola", "Maintainer": "Rodrigo Alvarez-Glez ", "source.ver": "src/contrib/DFP_1.32.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/DFP_1.32.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/DFP_1.32.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/DFP_1.32.0.tgz", "vignettes": [ "vignettes/DFP/inst/doc/DFP.pdf" ], "vignetteTitles": [ "Howto: Discriminat Fuzzy Pattern" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/DFP/inst/doc/DFP.R" ] }, "DiffBind": { "Package": "DiffBind", "Version": "2.2.12", "Depends": [ "R (>= 3.3.0)", "GenomicRanges", "SummarizedExperiment" ], "Imports": [ "RColorBrewer", "amap", "edgeR", "gplots", "grDevices", "limma", "GenomicAlignments", "locfit", "stats", "utils", "IRanges", "zlibbioc", "lattice", "systemPipeR", "tools", "Rcpp", "dplyr", "BiocParallel", "parallel", "S4Vectors", "Rsamtools", "DESeq2", "methods" ], "LinkingTo": [ "Rsamtools (>= 1.19.38)", "Rcpp" ], "Suggests": [ "DESeq", "BiocStyle", "testthat" ], "Enhances": [ "rgl", "XLConnect" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "d1f4cf8b8642416849460ce9339ccc62", "NeedsCompilation": "yes", "Title": "Differential Binding Analysis of ChIP-Seq peak data", "Description": "Compute differentially bound sites from multiple ChIP-seq experiments using affinity (quantitative) data. Also enables occupancy (overlap) analysis and plotting functions.", "biocViews": [ "ChIPSeq", "DifferentialPeakCalling", "Sequencing", "Software" ], "Author": "Rory Stark, Gord Brown ", "Maintainer": "Rory Stark", "source.ver": "src/contrib/DiffBind_2.2.12.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/DiffBind_2.2.12.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/DiffBind_2.2.12.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/DiffBind_2.2.12.tgz", "vignettes": [ "vignettes/DiffBind/inst/doc/DiffBind.pdf" ], "vignetteTitles": [ "DiffBind: Differential binding analysis of ChIP-Seq peak data" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/DiffBind/inst/doc/DiffBind.R" ], "dependsOnMe": [ "ChIPQC" ] }, "diffGeneAnalysis": { "Package": "diffGeneAnalysis", "Version": "1.56.0", "Imports": [ "graphics", "grDevices", "minpack.lm (>= 1.0-4)", "stats", "utils" ], "License": "GPL", "MD5sum": "ede0fbda08caa91db7fdff7a11a6ec09", "NeedsCompilation": "no", "Title": "Performs differential gene expression Analysis", "Description": "Analyze microarray data", "biocViews": [ "DifferentialExpression", "Microarray", "Software" ], "Author": "Choudary Jagarlamudi", "Maintainer": "Choudary Jagarlamudi ", "source.ver": "src/contrib/diffGeneAnalysis_1.56.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/diffGeneAnalysis_1.56.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/diffGeneAnalysis_1.56.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/diffGeneAnalysis_1.56.0.tgz", "vignettes": [ "vignettes/diffGeneAnalysis/inst/doc/diffGeneAnalysis.pdf" ], "vignetteTitles": [ "Documentation on diffGeneAnalysis" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/diffGeneAnalysis/inst/doc/diffGeneAnalysis.R" ] }, "diffHic": { "Package": "diffHic", "Version": "1.6.0", "Depends": [ "R (>= 3.3.0)", "GenomicRanges", "InteractionSet", "SummarizedExperiment" ], "Imports": [ "Rsamtools", "Rhtslib", "Biostrings", "BSgenome", "rhdf5", "edgeR", "limma", "csaw", "locfit", "methods", "IRanges", "S4Vectors", "GenomeInfoDb", "BiocGenerics", "grDevices", "graphics", "stats", "utils" ], "LinkingTo": [ "Rhtslib", "zlibbioc" ], "Suggests": [ "BSgenome.Ecoli.NCBI.20080805", "Matrix" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "55b278cd6dc9a970f92a2af67ca98254", "NeedsCompilation": "yes", "Title": "Differential Analyis of Hi-C Data", "Description": "Detects differential interactions across biological conditions in a Hi-C experiment. Methods are provided for read alignment and data pre-processing into interaction counts. Statistical analysis is based on edgeR and supports normalization and filtering. Several visualization options are also available.", "biocViews": [ "Alignment", "Clustering", "Coverage", "HiC", "MultipleComparison", "Normalization", "Preprocessing", "Sequencing", "Software" ], "Author": "Aaron Lun ", "Maintainer": "Aaron Lun ", "source.ver": "src/contrib/diffHic_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/diffHic_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/diffHic_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/diffHic_1.6.0.tgz", "vignettes": [ "vignettes/diffHic/inst/doc/diffHic.pdf", "vignettes/diffHic/inst/doc/diffHicUsersGuide.pdf" ], "vignetteTitles": [ "diffHic Vignette", "diffHicUsersGuide.pdf" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/diffHic/inst/doc/bam2hdf.R" ] }, "DiffLogo": { "Package": "DiffLogo", "Version": "1.4.0", "Depends": [ "R (>= 1.8.0)", "stats", "cba" ], "Suggests": [ "knitr", "testthat", "seqLogo", "MotifDb" ], "License": "GPL (>= 2)", "MD5sum": "4ffaaef49d0bab4b0a9556d1a1c60eaf", "NeedsCompilation": "no", "Title": "DiffLogo: A comparative visualisation of sequence motifs", "Description": "DiffLogo is an easy-to-use tool to visualize motif differences.", "biocViews": [ "MotifAnnotation", "MultipleComparison", "SequenceMatching", "Software", "Visualization" ], "Author": "Martin Nettling [aut], Hendrik Treutler [aut, cre], Jan Grau [aut, ctb], Jens Keilwagen [aut, ctb], Stefan Posch [aut], Ivo Grosse [aut]", "Maintainer": "Hendrik Treutler ", "URL": "https://github.com/mgledi/DiffLogo/", "VignetteBuilder": "knitr", "BugReports": "https://github.com/mgledi/DiffLogo/issues", "source.ver": "src/contrib/DiffLogo_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/DiffLogo_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/DiffLogo_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/DiffLogo_1.4.0.tgz", "vignettes": [ "vignettes/DiffLogo/inst/doc/DiffLogoBasics.pdf" ], "vignetteTitles": [ "Basics of the DiffLogo package" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/DiffLogo/inst/doc/DiffLogoBasics.R" ] }, "diffloop": { "Package": "diffloop", "Version": "1.2.2", "Imports": [ "methods", "GenomicRanges", "foreach", "plyr", "dplyr", "reshape2", "ggplot2", "matrixStats", "Sushi", "edgeR", "locfit", "statmod", "biomaRt", "GenomeInfoDb", "S4Vectors", "IRanges", "grDevices", "graphics", "stats", "utils", "Biobase", "readr", "data.table", "rtracklayer", "pbapply", "limma" ], "Suggests": [ "DESeq2", "diffloopdata", "ggrepel", "knitr", "rmarkdown", "testthat" ], "License": "MIT + file LICENSE", "MD5sum": "5e238ccbbd85fb0ad9c1072177e0b7bf", "NeedsCompilation": "no", "Title": "Identifying differential DNA loops from chromatin topology data", "Description": "A suite of tools for subsetting, visualizing, annotating, and statistically analyzing the results of one or more ChIA-PET experiments or other assays that infer chromatin loops.", "biocViews": [ "DataImport", "DataRepresentation", "GO", "Preprocessing", "QualityControl", "Software", "Visualization" ], "Author": "Caleb Lareau [aut, cre], Martin Aryee [aut]", "Maintainer": "Caleb Lareau ", "URL": "https://github.com/aryeelab/diffloop", "VignetteBuilder": "knitr", "BugReports": "https://github.com/aryeelab/diffloop/issues", "source.ver": "src/contrib/diffloop_1.2.2.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/diffloop_1.2.2.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/diffloop_1.2.2.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/diffloop_1.2.2.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/diffloop/inst/doc/diffloop.R" ], "htmlDocs": [ "vignettes/diffloop/inst/doc/diffloop.html" ], "htmlTitles": [ "diffloop: Identifying differential DNA loops from chromatin topology data." ] }, "diggit": { "Package": "diggit", "Version": "1.6.0", "Depends": [ "R (>= 3.0.2)", "Biobase", "methods" ], "Imports": [ "ks", "viper(>= 1.3.1)", "parallel" ], "Suggests": [ "diggitdata" ], "License": "file LICENSE", "MD5sum": "e4edb4a998ecd8bfa453feb3cb29f189", "NeedsCompilation": "no", "Title": "Inference of Genetic Variants Driving Cellular Phenotypes", "Description": "Inference of Genetic Variants Driving Cellullar Phenotypes by the DIGGIT algorithm", "biocViews": [ "FunctionalPrediction", "GeneExpression", "GeneRegulation", "NetworkEnrichment", "Software", "SystemsBiology" ], "Author": "Mariano J Alvarez ", "Maintainer": "Mariano J Alvarez ", "source.ver": "src/contrib/diggit_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/diggit_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/diggit_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/diggit_1.6.0.tgz", "vignettes": [ "vignettes/diggit/inst/doc/diggit.pdf" ], "vignetteTitles": [ "Using DIGGIT" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/diggit/inst/doc/diggit.R" ] }, "Director": { "Package": "Director", "Version": "1.0.0", "Depends": [ "R (>= 3.3)" ], "Imports": [ "htmltools", "utils", "grDevices" ], "License": "GPL-3 + file LICENSE", "MD5sum": "28d0d1717743197875f921fade670f47", "NeedsCompilation": "no", "Title": "A dynamic visualization tool of multi-level data", "Description": "Director is an R package designed to streamline the visualization of molecular effects in regulatory cascades. It utilizes the R package htmltools and a modified Sankey plugin of the JavaScript library D3 to provide a fast and easy, browser-enabled solution to discovering potentially interesting downstream effects of regulatory and/or co-expressed molecules. The diagrams are robust, interactive, and packaged as highly-portable HTML files that eliminate the need for third-party software to view. This enables a straightforward approach for scientists to interpret the data produced, and bioinformatics developers an alternative means to present relevant data.", "biocViews": [ "Software", "Visualization" ], "Author": "Katherine Icay [aut, cre]", "Maintainer": "Katherine Icay ", "URL": "https://github.com/kzouchka/Director", "BugReports": "https://github.com/kzouchka/Director/issues", "source.ver": "src/contrib/Director_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Director_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Director_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Director_1.0.0.tgz", "vignettes": [ "vignettes/Director/inst/doc/vignette.pdf" ], "vignetteTitles": [ "Using Director" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/Director/inst/doc/vignette.R" ] }, "DirichletMultinomial": { "Package": "DirichletMultinomial", "Version": "1.16.0", "Depends": [ "S4Vectors", "IRanges" ], "Imports": [ "stats4", "methods", "BiocGenerics" ], "Suggests": [ "lattice", "parallel", "MASS", "RColorBrewer", "xtable" ], "License": "LGPL-3", "Archs": "i386, x64", "MD5sum": "9d8db7c2a649f8ff9eee98e549717415", "NeedsCompilation": "yes", "Title": "Dirichlet-Multinomial Mixture Model Machine Learning for Microbiome Data", "Description": "Dirichlet-multinomial mixture models can be used to describe variability in microbial metagenomic data. This package is an interface to code originally made available by Holmes, Harris, and Quince, 2012, PLoS ONE 7(2): 1-15, as discussed further in the man page for this package, ?DirichletMultinomial.", "biocViews": [ "Classification", "Clustering", "Metagenomics", "Microbiome", "Sequencing", "Software" ], "Author": "Martin Morgan ", "Maintainer": "Martin Morgan ", "SystemRequirements": "gsl", "source.ver": "src/contrib/DirichletMultinomial_1.16.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/DirichletMultinomial_1.16.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/DirichletMultinomial_1.16.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/DirichletMultinomial_1.16.0.tgz", "vignettes": [ "vignettes/DirichletMultinomial/inst/doc/DirichletMultinomial.pdf" ], "vignetteTitles": [ "An introduction to DirichletMultinomial" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/DirichletMultinomial/inst/doc/DirichletMultinomial.R" ], "importsMe": [ "TFBSTools" ] }, "dks": { "Package": "dks", "Version": "1.20.0", "Depends": [ "R (>= 2.8)" ], "Imports": [ "cubature" ], "License": "GPL", "MD5sum": "45713f07b9a33d076c1b620b72dedc50", "NeedsCompilation": "no", "Title": "The double Kolmogorov-Smirnov package for evaluating multiple testing procedures.", "Description": "The dks package consists of a set of diagnostic functions for multiple testing methods. The functions can be used to determine if the p-values produced by a multiple testing procedure are correct. These functions are designed to be applied to simulated data. The functions require the entire set of p-values from multiple simulated studies, so that the joint distribution can be evaluated.", "biocViews": [ "MultipleComparison", "QualityControl", "Software" ], "Author": "Jeffrey T. Leek ", "Maintainer": "Jeffrey T. Leek ", "source.ver": "src/contrib/dks_1.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/dks_1.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/dks_1.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/dks_1.20.0.tgz", "vignettes": [ "vignettes/dks/inst/doc/dks.pdf" ], "vignetteTitles": [ "dksTutorial" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/dks/inst/doc/dks.R" ] }, "DMRcaller": { "Package": "DMRcaller", "Version": "1.6.0", "Depends": [ "R (>= 3.2)", "GenomicRanges", "IRanges", "S4Vectors" ], "Imports": [ "parallel", "Rcpp", "RcppRoll" ], "Suggests": [ "knitr", "RUnit", "BiocGenerics" ], "License": "GPL-3", "MD5sum": "a405323789e8943c2b70d6f13953ced9", "NeedsCompilation": "no", "Title": "Differentially Methylated Regions caller", "Description": "Uses Bisulfite sequencing data in two conditions and identifies differentially methylated regions between the conditions in CG and non-CG context. The input is the CX report files produced by Bismark and the output is a list of DMRs stored as GRanges objects.", "biocViews": [ "Coverage", "DNAMethylation", "DifferentialMethylation", "Sequencing", "Software" ], "Author": "Nicolae Radu Zabet and Jonathan Michael Foonlan Tsang ", "Maintainer": "Nicolae Radu Zabet ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/DMRcaller_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/DMRcaller_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/DMRcaller_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/DMRcaller_1.6.0.tgz", "vignettes": [ "vignettes/DMRcaller/inst/doc/DMRcaller.pdf" ], "vignetteTitles": [ "DMRcaller" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/DMRcaller/inst/doc/DMRcaller.R" ] }, "DMRcate": { "Package": "DMRcate", "Version": "1.10.10", "Depends": [ "R (>= 3.3.0)", "minfi", "DSS", "DMRcatedata" ], "Imports": [ "limma", "missMethyl", "GenomicRanges", "parallel", "methods", "graphics", "plyr", "Gviz", "IRanges", "stats", "utils", "S4Vectors" ], "Suggests": [ "knitr", "RUnit", "BiocGenerics", "IlluminaHumanMethylation450kanno.ilmn12.hg19", "IlluminaHumanMethylationEPICanno.ilm10b2.hg19" ], "License": "file LICENSE", "MD5sum": "00d6c4e4305d8775b388192e1e6adbe3", "NeedsCompilation": "no", "Title": "Methylation array and sequencing spatial analysis methods", "Description": "De novo identification and extraction of differentially methylated regions (DMRs) from the human genome using Whole Genome Bisulphite Sequencing (WGBS) and Illumina Infinium Array (450K and EPIC) data. Provides functionality for filtering probes possibly confounded by SNPs and cross-hybridisation. Includes GRanges generation and plotting functions.", "biocViews": [ "DNAMethylation", "DifferentialExpression", "DifferentialMethylation", "GeneExpression", "Genetics", "GenomeAnnotation", "MethylationArray", "Microarray", "MultipleComparison", "OneChannel", "QualityControl", "Software", "TimeCourse", "TwoChannel" ], "Author": "Tim Peters", "Maintainer": "Tim Peters ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/DMRcate_1.10.10.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/DMRcate_1.10.10.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/DMRcate_1.10.10.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/DMRcate_1.10.10.tgz", "vignettes": [ "vignettes/DMRcate/inst/doc/DMRcate.pdf" ], "vignetteTitles": [ "The DMRcate package user's guide" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/DMRcate/inst/doc/DMRcate.R" ], "importsMe": [ "MEAL" ], "dependsOnMe": [ "ChAMP" ] }, "DMRforPairs": { "Package": "DMRforPairs", "Version": "1.10.0", "Depends": [ "R (>= 2.15.2)", "Gviz (>= 1.2.1)", "R2HTML (>= 2.2.1)", "GenomicRanges (>= 1.10.7)", "parallel" ], "License": "GPL (>= 2)", "MD5sum": "cd725ba722d7c59dc714da33543ffb0d", "NeedsCompilation": "no", "Title": "DMRforPairs: identifying Differentially Methylated Regions between unique samples using array based methylation profiles", "Description": "DMRforPairs (formerly DMR2+) allows researchers to compare n>=2 unique samples with regard to their methylation profile. The (pairwise) comparison of n unique single samples distinguishes DMRforPairs from other existing pipelines as these often compare groups of samples in either single CpG locus or region based analysis. DMRforPairs defines regions of interest as genomic ranges with sufficient probes located in close proximity to each other. Probes in one region are optionally annotated to the same functional class(es). Differential methylation is evaluated by comparing the methylation values within each region between individual samples and (if the difference is sufficiently large), testing this difference formally for statistical significance.", "biocViews": [ "Annotation", "DNAMethylation", "DifferentialMethylation", "Microarray", "ReportWriting", "Software", "Visualization" ], "Author": "Martin Rijlaarsdam [aut, cre], Yvonne vd Zwan [aut], Lambert Dorssers [aut], Leendert Looijenga [aut]", "Maintainer": "Martin Rijlaarsdam ", "URL": "http://www.martinrijlaarsdam.nl, http://www.erasmusmc.nl/pathologie/research/lepo/3898639/", "source.ver": "src/contrib/DMRforPairs_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/DMRforPairs_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/DMRforPairs_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/DMRforPairs_1.10.0.tgz", "vignettes": [ "vignettes/DMRforPairs/inst/doc/DMRforPairs_vignette.pdf" ], "vignetteTitles": [ "DMRforPairs_vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/DMRforPairs/inst/doc/DMRforPairs_vignette.R" ] }, "DNABarcodes": { "Package": "DNABarcodes", "Version": "1.4.0", "Depends": [ "Matrix", "parallel" ], "Imports": [ "Rcpp (>= 0.11.2)", "BH" ], "LinkingTo": [ "Rcpp", "BH" ], "Suggests": [ "knitr", "BiocStyle", "rmarkdown" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "5675217b30b7ef4f36b8a88059050ce3", "NeedsCompilation": "yes", "Title": "A tool for creating and analysing DNA barcodes used in Next Generation Sequencing multiplexing experiments", "Description": "The package offers a function to create DNA barcode sets capable of correcting insertion, deletion, and substitution errors. Existing barcodes can be analysed regarding their minimal, maximal and average distances between barcodes. Finally, reads that start with a (possibly mutated) barcode can be demultiplexed, i.e., assigned to their original reference barcode.", "biocViews": [ "Preprocessing", "Sequencing", "Software" ], "Author": "Tilo Buschmann ", "Maintainer": "Tilo Buschmann ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/DNABarcodes_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/DNABarcodes_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/DNABarcodes_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/DNABarcodes_1.4.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/DNABarcodes/inst/doc/DNABarcodes.R" ], "htmlDocs": [ "vignettes/DNABarcodes/inst/doc/DNABarcodes.html" ], "htmlTitles": [ "DNABarcodes" ] }, "DNAcopy": { "Package": "DNAcopy", "Version": "1.48.0", "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "f684816f5cf76f89fd1189842cf63102", "NeedsCompilation": "yes", "Title": "DNA copy number data analysis", "Description": "Implements the circular binary segmentation (CBS) algorithm to segment DNA copy number data and identify genomic regions with abnormal copy number.", "biocViews": [ "CopyNumberVariation", "Microarray", "Software" ], "Author": "Venkatraman E. Seshan, Adam Olshen", "Maintainer": "Venkatraman E. Seshan ", "source.ver": "src/contrib/DNAcopy_1.48.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/DNAcopy_1.48.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/DNAcopy_1.48.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/DNAcopy_1.48.0.tgz", "vignettes": [ "vignettes/DNAcopy/inst/doc/DNAcopy.pdf" ], "vignetteTitles": [ "DNAcopy" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/DNAcopy/inst/doc/DNAcopy.R" ], "dependsOnMe": [ "CGHcall", "cghMCR", "Clonality", "CRImage", "PureCN", "snapCGH" ], "importsMe": [ "ADaCGH2", "AneuFinder", "ArrayTV", "ChAMP", "Clonality", "cn.farms", "CNAnorm", "CNVrd2", "contiBAIT", "conumee", "CopywriteR", "GWASTools", "MEDIPS", "MinimumDistance", "QDNAseq", "rCGH", "Repitools", "snapCGH" ], "suggestsMe": [ "beadarraySNP", "Clonality", "cn.mops", "fastseg", "genoset" ] }, "DNAshapeR": { "Package": "DNAshapeR", "Version": "1.2.0", "Depends": [ "R (>= 3.3)", "GenomicRanges" ], "Imports": [ "Rcpp (>= 0.12.1)", "Biostrings", "fields" ], "LinkingTo": [ "Rcpp" ], "Suggests": [ "AnnotationHub", "knitr", "rmarkdown", "testthat", "BSgenome.Scerevisiae.UCSC.sacCer3", "BSgenome.Hsapiens.UCSC.hg19", "caret" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "e8e11921254ffe5a800d1a971a46ca2a", "NeedsCompilation": "yes", "Title": "High-throughput prediction of DNA shape features", "Description": "DNAhapeR is an R/BioConductor package for ultra-fast, high-throughput predictions of DNA shape features. The package allows to predict, visualize and encode DNA shape features for statistical learning.", "biocViews": [ "DNA3DStructure", "Software", "StructuralPrediction" ], "Author": "Tsu-Pei Chiu and Federico Comoglio", "Maintainer": "Tsu-Pei Chiu ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/DNAshapeR_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/DNAshapeR_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/DNAshapeR_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/DNAshapeR_1.2.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/DNAshapeR/inst/doc/DNAshapeR.R" ], "htmlDocs": [ "vignettes/DNAshapeR/inst/doc/DNAshapeR.html" ], "htmlTitles": [ "DNAshapeR" ] }, "domainsignatures": { "Package": "domainsignatures", "Version": "1.34.0", "Depends": [ "R (>= 2.4.0)", "KEGG.db", "prada", "biomaRt", "methods" ], "Imports": [ "AnnotationDbi" ], "License": "Artistic-2.0", "MD5sum": "a64dbdcb1e23c0651893f1c97bcda567", "NeedsCompilation": "no", "Title": "Geneset enrichment based on InterPro domain signatures", "Description": "Find significantly enriched gene classifications in a list of functionally undescribed genes based on their InterPro domain structure.", "biocViews": [ "Annotation", "GeneSetEnrichment", "Pathways", "Software" ], "Author": "Florian Hahne, Tim Beissbarth", "Maintainer": "Florian Hahne ", "source.ver": "src/contrib/domainsignatures_1.34.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/domainsignatures_1.34.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/domainsignatures_1.34.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/domainsignatures_1.34.0.tgz", "vignettes": [ "vignettes/domainsignatures/inst/doc/domainenrichment.pdf" ], "vignetteTitles": [ "Gene set enrichment using InterPro domain signatures" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/domainsignatures/inst/doc/domainenrichment.R" ] }, "doppelgangR": { "Package": "doppelgangR", "Version": "1.2.0", "Depends": [ "R (>= 3.3)", "Biobase", "BiocParallel" ], "Imports": [ "sva", "impute", "digest", "mnormt", "methods", "grDevices", "graphics", "stats", "utils" ], "Suggests": [ "BiocStyle", "knitr", "rmarkdown", "curatedOvarianData", "ROCR", "pROC", "RUnit", "simulatorZ", "proxy" ], "License": "GPL (>=2.0)", "MD5sum": "20a7081c36500da4e8d80c56b0faa4d8", "NeedsCompilation": "no", "Title": "Identify likely duplicate samples from genomic or meta-data", "Description": "The main function is doppelgangR(), which takes as minimal input a list of ExpressionSet object, and searches all list pairs for duplicated samples. The search is based on the genomic data (exprs(eset)), phenotype/clinical data (pData(eset)), and \"smoking guns\" - supposedly unique identifiers found in pData(eset).", "biocViews": [ "GeneExpression", "Microarray", "QualityControl", "RNASeq", "Software" ], "Author": "Levi Waldron, Markus Riester, Marcel Ramos", "Maintainer": "Levi Waldron ", "URL": "https://github.com/lwaldron/doppelgangR", "VignetteBuilder": "knitr", "BugReports": "https://github.com/lwaldron/doppelgangR/issues", "source.ver": "src/contrib/doppelgangR_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/doppelgangR_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/doppelgangR_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/doppelgangR_1.2.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/doppelgangR/inst/doc/doppelgangR.R" ], "htmlDocs": [ "vignettes/doppelgangR/inst/doc/doppelgangR.html" ], "htmlTitles": [ "doppelgangR vignette" ] }, "DOQTL": { "Package": "DOQTL", "Version": "1.10.0", "Depends": [ "R (>= 3.0.0)", "BSgenome.Mmusculus.UCSC.mm10", "GenomicRanges", "VariantAnnotation" ], "Imports": [ "annotate", "annotationTools", "biomaRt", "Biobase", "BiocGenerics", "corpcor", "doParallel", "foreach", "fpc", "hwriter", "IRanges", "iterators", "mclust", "QTLRel", "regress", "rhdf5", "Rsamtools", "RUnit", "XML" ], "Suggests": [ "MUGAExampleData", "doMPI" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "53260bc0199adac1f4e168250924293b", "NeedsCompilation": "yes", "Title": "Genotyping and QTL Mapping in DO Mice", "Description": "DOQTL is a quantitative trait locus (QTL) mapping pipeline designed for Diversity Outbred mice and other multi-parent outbred populations. The package reads in data from genotyping arrays and perform haplotype reconstruction using a hidden Markov model (HMM). The haplotype probabilities from the HMM are then used to perform linkage mapping. When founder sequences are available, DOQTL can use the haplotype reconstructions to impute the founder sequences onto DO genomes and perform association mapping.", "biocViews": [ "GeneticVariability", "Genetics", "HiddenMarkovModel", "SNP", "Software" ], "Author": "Daniel Gatti, Karl Broman, Andrey Shabalin, Petr Simecek", "Maintainer": "Daniel Gatti ", "URL": "http://do.jax.org", "source.ver": "src/contrib/DOQTL_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/DOQTL_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/DOQTL_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/DOQTL_1.10.0.tgz", "vignettes": [ "vignettes/DOQTL/inst/doc/QTL_Mapping_DO_Mice.pdf" ], "vignetteTitles": [ "QTL Mapping using Diversity Outbred Mice" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/DOQTL/inst/doc/QTL_Mapping_DO_Mice.R" ] }, "DOSE": { "Package": "DOSE", "Version": "3.0.10", "Depends": [ "R (>= 3.3.1)" ], "Imports": [ "AnnotationDbi", "BiocParallel", "DO.db", "fgsea", "ggplot2", "GOSemSim (>= 2.0.0)", "graphics", "grDevices", "grid", "igraph", "methods", "qvalue", "reshape2", "S4Vectors", "scales", "stats", "stats4", "utils" ], "Suggests": [ "BiocStyle", "clusterProfiler", "knitr", "org.Hs.eg.db", "testthat", "UpSetR" ], "License": "Artistic-2.0", "MD5sum": "e914514c03ca7fc63aab000c231d2d8f", "NeedsCompilation": "no", "Title": "Disease Ontology Semantic and Enrichment analysis", "Description": "This package implements five methods proposed by Resnik, Schlicker, Jiang, Lin and Wang respectively for measuring semantic similarities among DO terms and gene products. Enrichment analyses including hypergeometric model and gene set enrichment analysis are also implemented for discovering disease associations of high-throughput biological data.", "biocViews": [ "Annotation", "GeneSetEnrichment", "MultipleComparison", "Pathways", "Software", "Visualization" ], "Author": "Guangchuang Yu with contributions from Li-Gen Wang, Vladislav Petyuk and Giovanni Dall'Olio.", "Maintainer": "Guangchuang Yu ", "URL": "https://guangchuangyu.github.io/DOSE", "VignetteBuilder": "knitr", "BugReports": "https://github.com/GuangchuangYu/DOSE/issues", "source.ver": "src/contrib/DOSE_3.0.10.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/DOSE_3.0.10.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/DOSE_3.0.10.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/DOSE_3.0.10.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/DOSE/inst/doc/DOSE.R", "vignettes/DOSE/inst/doc/enrichmentAnalysis.R", "vignettes/DOSE/inst/doc/GSEA.R", "vignettes/DOSE/inst/doc/semanticAnalysis.R" ], "htmlDocs": [ "vignettes/DOSE/inst/doc/DOSE.html", "vignettes/DOSE/inst/doc/enrichmentAnalysis.html", "vignettes/DOSE/inst/doc/GSEA.html", "vignettes/DOSE/inst/doc/semanticAnalysis.html" ], "htmlTitles": [ "00 DOSE introduction", "02 Disease enrichment analysis", "03 Disease GSEA", "01 DOSE semantic similarity analysis" ], "dependsOnMe": [ "clusterProfiler", "meshes", "ReactomePA" ], "importsMe": [ "bioCancer", "ChIPseeker", "debrowser", "eegc", "facopy", "LINC", "MoonlightR" ], "suggestsMe": [ "GOSemSim" ] }, "DRIMSeq": { "Package": "DRIMSeq", "Version": "1.2.0", "Depends": [ "R (>= 3.3.0)" ], "Imports": [ "GenomicRanges", "IRanges", "S4Vectors", "BiocGenerics", "methods", "BiocParallel", "edgeR", "utils", "stats", "grDevices", "ggplot2", "reshape2" ], "Suggests": [ "PasillaTranscriptExpr", "GeuvadisTranscriptExpr", "grid", "BiocStyle", "knitr", "testthat" ], "License": "GPL (>= 3)", "MD5sum": "4413845b7ab7e186ae1e9c4f93e35347", "NeedsCompilation": "no", "Title": "Differential splicing and sQTL analyses with Dirichlet-multinomial model in RNA-Seq", "Description": "The package provides two frameworks. One for the differential splicing analysis between different conditions and one for the sQTL analysis. Both are based on modeling the counts of genomic features (i.e., transcripts, exons or exonic bins) with Dirichlet-multinomial distribution. The package also makes available functions for visualization and exploration of the data and results.", "biocViews": [ "AlternativeSplicing", "DifferentialExpression", "DifferentialSplicing", "GeneExpression", "Genetics", "MultipleComparison", "RNASeq", "SNP", "Sequencing", "Software", "WorkflowStep" ], "Author": "Malgorzata Nowicka [aut, cre]", "Maintainer": "Malgorzata Nowicka ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/DRIMSeq_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/DRIMSeq_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/DRIMSeq_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/DRIMSeq_1.2.0.tgz", "vignettes": [ "vignettes/DRIMSeq/inst/doc/DRIMSeq.pdf" ], "vignetteTitles": [ "Differential splicing and sQTL analyses in RNA-seq with 'DRIMSeq' package" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/DRIMSeq/inst/doc/DRIMSeq.R" ] }, "DriverNet": { "Package": "DriverNet", "Version": "1.14.0", "Depends": [ "R (>= 2.10)", "methods" ], "License": "GPL-3", "MD5sum": "1783e50d1693efd554878992938987a0", "NeedsCompilation": "no", "Title": "Drivernet: uncovering somatic driver mutations modulating transcriptional networks in cancer", "Description": "DriverNet is a package to predict functional important driver genes in cancer by integrating genome data (mutation and copy number variation data) and transcriptome data (gene expression data). The different kinds of data are combined by an influence graph, which is a gene-gene interaction network deduced from pathway data. A greedy algorithm is used to find the possible driver genes, which may mutated in a larger number of patients and these mutations will push the gene expression values of the connected genes to some extreme values.", "biocViews": [ "Network", "Software" ], "Author": "Ali Bashashati, Reza Haffari, Jiarui Ding, Gavin Ha, Kenneth Liu, Jamie Rosner and Sohrab Shah", "Maintainer": "Jiarui Ding ", "source.ver": "src/contrib/DriverNet_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/DriverNet_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/DriverNet_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/DriverNet_1.14.0.tgz", "vignettes": [ "vignettes/DriverNet/inst/doc/DriverNet-Overview.pdf" ], "vignetteTitles": [ "An introduction to DriverNet" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/DriverNet/inst/doc/DriverNet-Overview.R" ] }, "DrugVsDisease": { "Package": "DrugVsDisease", "Version": "2.14.0", "Depends": [ "R (>= 2.10)", "affy", "limma", "biomaRt", "ArrayExpress", "GEOquery", "DrugVsDiseasedata", "cMap2data", "qvalue" ], "Imports": [ "annotate", "hgu133a.db", "hgu133a2.db", "hgu133plus2.db", "RUnit", "BiocGenerics", "xtable" ], "License": "GPL-3", "MD5sum": "af0592b06a8fe326f46d31376fef442a", "NeedsCompilation": "no", "Title": "Comparison of disease and drug profiles using Gene set Enrichment Analysis", "Description": "This package generates ranked lists of differential gene expression for either disease or drug profiles. Input data can be downloaded from Array Express or GEO, or from local CEL files. Ranked lists of differential expression and associated p-values are calculated using Limma. Enrichment scores (Subramanian et al. PNAS 2005) are calculated to a reference set of default drug or disease profiles, or a set of custom data supplied by the user. Network visualisation of significant scores are output in Cytoscape format.", "biocViews": [ "Clustering", "GeneExpression", "Microarray", "Software" ], "Author": "C. Pacini", "Maintainer": "j. Saez-Rodriguez ", "source.ver": "src/contrib/DrugVsDisease_2.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/DrugVsDisease_2.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/DrugVsDisease_2.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/DrugVsDisease_2.14.0.tgz", "vignettes": [ "vignettes/DrugVsDisease/inst/doc/DrugVsDisease.pdf" ], "vignetteTitles": [ "DrugVsDisease" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/DrugVsDisease/inst/doc/DrugVsDisease.R" ] }, "dSimer": { "Package": "dSimer", "Version": "1.0.0", "Depends": [ "R (>= 3.3.0)", "igraph (>= 1.0.1)" ], "Imports": [ "stats", "Rcpp (>= 0.11.3)", "ggplot2", "reshape2", "GO.db", "org.Hs.eg.db", "AnnotationDbi", "graphics" ], "LinkingTo": [ "Rcpp" ], "Suggests": [ "knitr", "rmarkdown", "BiocStyle" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "bdb1c946272689a45ffa117c5577111b", "NeedsCompilation": "yes", "Title": "Integration of Disease Similarity Methods", "Description": "dSimer is an R package which provides computation of nine methods for measuring disease-disease similarity, including a standard cosine similarity measure and eight function-based methods. The disease similarity matrix obtained from these nine methods can be visualized through heatmap and network. Biological data widely used in disease-disease associations study are also provided by dSimer.", "biocViews": [ "Network", "Software", "Visualization" ], "Author": "Min Li , Peng Ni with contributions from Zhihui Fei and Ping Huang.", "Maintainer": "Peng Ni ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/dSimer_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/dSimer_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/dSimer_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/dSimer_1.0.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/dSimer/inst/doc/dSimer.R" ], "htmlDocs": [ "vignettes/dSimer/inst/doc/dSimer.html" ], "htmlTitles": [ "Integration of Disease Similarity Methods" ] }, "DSS": { "Package": "DSS", "Version": "2.14.0", "Depends": [ "Biobase", "bsseq", "splines", "methods" ], "Suggests": [ "BiocStyle" ], "License": "GPL", "Archs": "i386, x64", "MD5sum": "20ce023ae7de59c82dfe6a2a0ff34ea6", "NeedsCompilation": "yes", "Title": "Dispersion shrinakge for sequencing data.", "Description": "DSS is an R library performing differntial analysis for count-based sequencing data. It detectes differentially expressed genes (DEGs) from RNA-seq, and differentially methylated loci or regions (DML/DMRs) from bisulfite sequencing (BS-seq). The core of DSS is a new dispersion shrinkage method for estimating the dispersion parameter from Gamma-Poisson or Beta-Binomial distributions.", "biocViews": [ "ChIPSeq", "DNAMethylation", "DifferentialExpression", "DifferentialMethylation", "GeneExpression", "RNASeq", "Sequencing", "Software" ], "Author": "Hao Wu ", "Maintainer": "Hao Wu ", "source.ver": "src/contrib/DSS_2.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/DSS_2.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/DSS_2.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/DSS_2.14.0.tgz", "vignettes": [ "vignettes/DSS/inst/doc/DSS.pdf" ], "vignetteTitles": [ "Differential expression for RNA-seq data with dispersion shrinkage" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/DSS/inst/doc/DSS.R" ], "dependsOnMe": [ "DMRcate" ], "suggestsMe": [ "PROPER" ] }, "DTA": { "Package": "DTA", "Version": "2.20.0", "Depends": [ "R (>= 2.10)", "LSD" ], "Imports": [ "scatterplot3d" ], "License": "Artistic-2.0", "MD5sum": "907645b2c13a568952e490c92f360a8f", "NeedsCompilation": "no", "Title": "Dynamic Transcriptome Analysis", "Description": "Dynamic Transcriptome Analysis (DTA) can monitor the cellular response to perturbations with higher sensitivity and temporal resolution than standard transcriptomics. The package implements the underlying kinetic modeling approach capable of the precise determination of synthesis- and decay rates from individual microarray or RNAseq measurements.", "biocViews": [ "DifferentialExpression", "GeneExpression", "Microarray", "Software", "Transcription" ], "Author": "Bjoern Schwalb, Benedikt Zacher, Sebastian Duemcke, Achim Tresch", "Maintainer": "Bjoern Schwalb ", "source.ver": "src/contrib/DTA_2.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/DTA_2.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/DTA_2.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/DTA_2.20.0.tgz", "vignettes": [ "vignettes/DTA/inst/doc/DTA.pdf" ], "vignetteTitles": [ "A guide to Dynamic Transcriptome Analysis (DTA)" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/DTA/inst/doc/DTA.R" ] }, "dualKS": { "Package": "dualKS", "Version": "1.34.0", "Depends": [ "R (>= 2.6.0)", "Biobase (>= 1.15.0)", "affy", "methods" ], "Imports": [ "graphics" ], "License": "LGPL (>= 2.0)", "MD5sum": "a73afaebab46c4a1c72a7bf2917c09ad", "NeedsCompilation": "no", "Title": "Dual KS Discriminant Analysis and Classification", "Description": "This package implements a Kolmogorov Smirnov rank-sum based algorithm for training (i.e. discriminant analysis--identification of genes that discriminate between classes) and classification of gene expression data sets. One of the chief strengths of this approach is that it is amenable to the \"multiclass\" problem. That is, it can discriminate between more than 2 classes.", "biocViews": [ "Classification", "Microarray", "Software" ], "Author": "Eric J. Kort, Yarong Yang", "Maintainer": "Eric J. Kort , Yarong Yang ", "source.ver": "src/contrib/dualKS_1.34.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/dualKS_1.34.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/dualKS_1.34.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/dualKS_1.34.0.tgz", "vignettes": [ "vignettes/dualKS/inst/doc/dualKS.pdf" ], "vignetteTitles": [ "dualKS.pdf" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/dualKS/inst/doc/dualKS.R" ] }, "DupChecker": { "Package": "DupChecker", "Version": "1.12.0", "Imports": [ "tools", "R.utils", "RCurl" ], "Suggests": [ "knitr" ], "License": "GPL (>= 2)", "MD5sum": "4e4c5d5944217c1be86aaabcc2a9ac85", "NeedsCompilation": "no", "Title": "a package for checking high-throughput genomic data redundancy in meta-analysis", "Description": "Meta-analysis has become a popular approach for high-throughput genomic data analysis because it often can significantly increase power to detect biological signals or patterns in datasets. However, when using public-available databases for meta-analysis, duplication of samples is an often encountered problem, especially for gene expression data. Not removing duplicates would make study results questionable. We developed a Bioconductor package DupChecker that efficiently identifies duplicated samples by generating MD5 fingerprints for raw data.", "biocViews": [ "Preprocessing", "Software" ], "Author": "Quanhu Sheng, Yu Shyr, Xi Chen", "Maintainer": "\"Quanhu SHENG\" ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/DupChecker_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/DupChecker_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/DupChecker_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/DupChecker_1.12.0.tgz", "vignettes": [ "vignettes/DupChecker/inst/doc/DupChecker.pdf" ], "vignetteTitles": [ "Validate genomic data with \"DupChecker\" package" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/DupChecker/inst/doc/DupChecker.R" ] }, "dupRadar": { "Package": "dupRadar", "Version": "1.4.0", "Depends": [ "R (>= 3.2.0)" ], "Imports": [ "Rsubread (>= 1.14.1)" ], "Suggests": [ "BiocStyle", "knitr", "rmarkdown", "AnnotationHub" ], "License": "GPL-3", "MD5sum": "bf81a5534f2a465e7c7a792b18c7633f", "NeedsCompilation": "no", "Title": "Assessment of duplication rates in RNA-Seq datasets", "Description": "Duplication rate quality control for RNA-Seq datasets.", "biocViews": [ "QualityControl", "RNASeq", "Sequencing", "Software", "Technology" ], "Author": "Sergi Sayols , Holger Klein ", "Maintainer": "Sergi Sayols , Holger Klein ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/dupRadar_1.4.0.tar.gz", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/dupRadar_1.4.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/dupRadar/inst/doc/dupRadar.R" ], "htmlDocs": [ "vignettes/dupRadar/inst/doc/dupRadar.html" ], "htmlTitles": [ "Using dupRadar" ] }, "dyebias": { "Package": "dyebias", "Version": "1.34.0", "Depends": [ "R (>= 1.4.1)", "marray", "Biobase" ], "Suggests": [ "limma", "convert", "GEOquery", "dyebiasexamples", "methods" ], "License": "GPL-3", "MD5sum": "e7b37d0c7785502b9c6e6747e5dc51b3", "NeedsCompilation": "no", "Title": "The GASSCO method for correcting for slide-dependent gene-specific dye bias", "Description": "Many two-colour hybridizations suffer from a dye bias that is both gene-specific and slide-specific. The former depends on the content of the nucleotide used for labeling; the latter depends on the labeling percentage. The slide-dependency was hitherto not recognized, and made addressing the artefact impossible. Given a reasonable number of dye-swapped pairs of hybridizations, or of same vs. same hybridizations, both the gene- and slide-biases can be estimated and corrected using the GASSCO method (Margaritis et al., Mol. Sys. Biol. 5:266 (2009), doi:10.1038/msb.2009.21)", "biocViews": [ "Microarray", "Preprocessing", "QualityControl", "Software", "TwoChannel" ], "Author": "Philip Lijnzaad and Thanasis Margaritis", "Maintainer": "Philip Lijnzaad ", "URL": "http://www.holstegelab.nl/publications/margaritis_lijnzaad", "source.ver": "src/contrib/dyebias_1.34.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/dyebias_1.34.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/dyebias_1.34.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/dyebias_1.34.0.tgz", "vignettes": [ "vignettes/dyebias/inst/doc/dyebias-vignette.pdf" ], "vignetteTitles": [ "dye bias correction" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/dyebias/inst/doc/dyebias-vignette.R" ], "suggestsMe": [ "dyebiasexamples" ] }, "DynDoc": { "Package": "DynDoc", "Version": "1.52.0", "Depends": [ "methods", "utils" ], "Imports": [ "methods" ], "License": "Artistic-2.0", "MD5sum": "db212af5bb3f57c14dc9af6663f02221", "NeedsCompilation": "no", "Title": "Dynamic document tools", "Description": "A set of functions to create and interact with dynamic documents and vignettes.", "biocViews": [ "Infrastructure", "ReportWriting", "Software" ], "Author": "R. Gentleman, Jeff Gentry", "Maintainer": "Bioconductor Package Maintainer ", "source.ver": "src/contrib/DynDoc_1.52.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/DynDoc_1.52.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/DynDoc_1.52.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/DynDoc_1.52.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "dependsOnMe": [ "tkWidgets" ] }, "EasyqpcR": { "Package": "EasyqpcR", "Version": "1.16.0", "Imports": [ "plyr", "matrixStats", "plotrix", "gWidgetsRGtk2" ], "Suggests": [ "SLqPCR", "qpcrNorm", "qpcR", "knitr" ], "License": "GPL (>=2)", "MD5sum": "8de8a87b9756fd05eeb02588a97413ff", "NeedsCompilation": "no", "Title": "EasyqpcR for low-throughput real-time quantitative PCR data analysis", "Description": "This package is based on the qBase algorithms published by Hellemans et al. in 2007. The EasyqpcR package allows you to import easily qPCR data files as described in the vignette. Thereafter, you can calculate amplification efficiencies, relative quantities and their standard errors, normalization factors based on the best reference genes choosen (using the SLqPCR package), and then the normalized relative quantities, the NRQs scaled to your control and their standard errors. This package has been created for low-throughput qPCR data analysis.", "biocViews": [ "GeneExpression", "Software", "qPCR" ], "Author": "Le Pape Sylvain", "Maintainer": "Le Pape Sylvain ", "source.ver": "src/contrib/EasyqpcR_1.16.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/EasyqpcR_1.16.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/EasyqpcR_1.16.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/EasyqpcR_1.16.0.tgz", "vignettes": [ "vignettes/EasyqpcR/inst/doc/vignette_EasyqpcR.pdf" ], "vignetteTitles": [ "EasyqpcR" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/EasyqpcR/inst/doc/vignette_EasyqpcR.R" ] }, "easyRNASeq": { "Package": "easyRNASeq", "Version": "2.10.0", "Imports": [ "Biobase (>= 2.31.3)", "BiocGenerics (>= 0.17.2)", "BiocParallel (>= 1.5.1)", "biomaRt (>= 2.27.2)", "Biostrings (>= 2.39.3)", "DESeq (>= 1.23.0)", "edgeR (>= 3.13.4)", "GenomeInfoDb (>= 1.7.3)", "genomeIntervals (>= 1.27.0)", "GenomicAlignments (>= 1.7.3)", "GenomicRanges (>= 1.23.16)", "SummarizedExperiment (>= 1.1.11)", "graphics", "IRanges (>= 2.5.27)", "LSD (>= 3.0)", "locfit", "methods", "parallel", "Rsamtools (>= 1.23.1)", "S4Vectors (>= 0.9.38)", "ShortRead (>= 1.29.1)", "utils" ], "Suggests": [ "BiocStyle (>= 1.9.2)", "BSgenome (>= 1.39.0)", "BSgenome.Dmelanogaster.UCSC.dm3 (>= 1.4.0)", "curl", "GenomicFeatures (>= 1.23.15)", "knitr", "rmarkdown", "RnaSeqTutorial (>= 0.9.0)", "RUnit (>= 0.4.31)" ], "License": "Artistic-2.0", "MD5sum": "e4970184d486f5a07a984d1f7716eb05", "NeedsCompilation": "no", "Title": "Count summarization and normalization for RNA-Seq data", "Description": "Calculates the coverage of high-throughput short-reads against a genome of reference and summarizes it per feature of interest (e.g. exon, gene, transcript). The data can be normalized as 'RPKM' or by the 'DESeq' or 'edgeR' package.", "biocViews": [ "GeneExpression", "Genetics", "Preprocessing", "RNASeq", "Software" ], "Author": "Nicolas Delhomme, Ismael Padioleau, Bastian Schiffthaler, Niklas Maehler", "Maintainer": "Nicolas Delhomme ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/easyRNASeq_2.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/easyRNASeq_2.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/easyRNASeq_2.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/easyRNASeq_2.10.0.tgz", "vignettes": [ "vignettes/easyRNASeq/inst/doc/easyRNASeq.pdf" ], "vignetteTitles": [ "easyRNASeq" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/easyRNASeq/inst/doc/easyRNASeq.R", "vignettes/easyRNASeq/inst/doc/simpleRNASeq.R" ], "htmlDocs": [ "vignettes/easyRNASeq/inst/doc/simpleRNASeq.html" ], "htmlTitles": [ "geneNetworkR" ], "suggestsMe": [ "SeqGSEA" ], "dependsOnMe": [ "RnaSeqTutorial" ] }, "EBarrays": { "Package": "EBarrays", "Version": "2.38.0", "Depends": [ "R (>= 1.8.0)", "Biobase", "lattice", "methods" ], "Imports": [ "Biobase", "cluster", "graphics", "grDevices", "lattice", "methods", "stats" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "dc143c0344fff2436c6ea5698735297d", "NeedsCompilation": "yes", "Title": "Unified Approach for Simultaneous Gene Clustering and Differential Expression Identification", "Description": "EBarrays provides tools for the analysis of replicated/unreplicated microarray data.", "biocViews": [ "Clustering", "DifferentialExpression", "Software" ], "Author": "Ming Yuan, Michael Newton, Deepayan Sarkar and Christina Kendziorski", "Maintainer": "Ming Yuan ", "source.ver": "src/contrib/EBarrays_2.38.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/EBarrays_2.38.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/EBarrays_2.38.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/EBarrays_2.38.0.tgz", "vignettes": [ "vignettes/EBarrays/inst/doc/vignette.pdf" ], "vignetteTitles": [ "Introduction to EBarrays" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/EBarrays/inst/doc/vignette.R" ], "dependsOnMe": [ "EBcoexpress", "gaga", "geNetClassifier" ], "importsMe": [ "casper" ], "suggestsMe": [ "Category" ] }, "EBcoexpress": { "Package": "EBcoexpress", "Version": "1.18.0", "Depends": [ "EBarrays", "mclust", "minqa" ], "Suggests": [ "graph", "igraph", "colorspace" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "bcbc591f9986b6a061fcaec84d3ccf91", "NeedsCompilation": "yes", "Title": "EBcoexpress for Differential Co-Expression Analysis", "Description": "An Empirical Bayesian Approach to Differential Co-Expression Analysis at the Gene-Pair Level", "biocViews": [ "Bayesian", "Software" ], "Author": "John A. Dawson", "Maintainer": "John A. Dawson ", "source.ver": "src/contrib/EBcoexpress_1.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/EBcoexpress_1.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/EBcoexpress_1.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/EBcoexpress_1.18.0.tgz", "vignettes": [ "vignettes/EBcoexpress/inst/doc/EBcoexpressVignette.pdf" ], "vignetteTitles": [ "EBcoexpress Demo" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/EBcoexpress/inst/doc/EBcoexpressVignette.R" ], "dependsOnMe": [ "SRGnet" ] }, "EBImage": { "Package": "EBImage", "Version": "4.16.0", "Imports": [ "BiocGenerics (>= 0.7.1)", "methods", "graphics", "grDevices", "stats", "abind", "tiff", "jpeg", "png", "locfit", "fftwtools (>= 0.9-7)", "utils" ], "Suggests": [ "BiocStyle", "digest", "knitr", "rmarkdown" ], "License": "LGPL", "Archs": "i386, x64", "MD5sum": "8346f2f8de5f8d9890dcc2cfa0f544c0", "NeedsCompilation": "yes", "Title": "Image processing and analysis toolbox for R", "Description": "EBImage provides general purpose functionality for image processing and analysis. In the context of (high-throughput) microscopy-based cellular assays, EBImage offers tools to segment cells and extract quantitative cellular descriptors. This allows the automation of such tasks using the R programming language and facilitates the use of other tools in the R environment for signal processing, statistical modeling, machine learning and visualization with image data.", "biocViews": [ "Software", "Visualization" ], "Author": "Andrzej Oleś, Gregoire Pau, Mike Smith, Oleg Sklyar, Wolfgang Huber, with contributions from Joseph Barry and Philip A. Marais", "Maintainer": "Andrzej Oleś ", "URL": "https://github.com/aoles/EBImage", "VignetteBuilder": "knitr", "BugReports": "https://github.com/aoles/EBImage/issues", "source.ver": "src/contrib/EBImage_4.16.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/EBImage_4.16.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/EBImage_4.16.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/EBImage_4.16.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/EBImage/inst/doc/EBImage-introduction.R" ], "htmlDocs": [ "vignettes/EBImage/inst/doc/EBImage-introduction.html" ], "htmlTitles": [ "Introduction to EBImage" ], "dependsOnMe": [ "CRImage", "DonaPLLP2013", "FISHalyseR", "flowcatchR", "furrowSeg", "HD2013SGI", "imageHTS", "PGPC" ], "importsMe": [ "CONFESS", "flowCHIC", "yamss" ], "suggestsMe": [ "DmelSGI", "ggtree", "HilbertVis", "tofsims" ] }, "EBSEA": { "Package": "EBSEA", "Version": "1.2.0", "Imports": [ "edgeR", "limma", "gtools", "graphics", "stats" ], "License": "GPL-2", "MD5sum": "ff9fd33ec92646d5286c476bacdcee3b", "NeedsCompilation": "no", "Title": "Exon Based Strategy for Expression Analysis of genes", "Description": "Calculates differential expression of genes based on exon counts of genes obtained from RNA-seq sequencing data.", "biocViews": [ "DifferentialExpression", "GeneExpression", "Sequencing", "Software" ], "Author": "Arfa Mehmood, Asta Laiho, Laura L. Elo", "Maintainer": "Arfa Mehmood ", "source.ver": "src/contrib/EBSEA_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/EBSEA_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/EBSEA_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/EBSEA_1.2.0.tgz", "vignettes": [ "vignettes/EBSEA/inst/doc/EBSEA.pdf" ], "vignetteTitles": [ "EBSEA: Exon Based Strategy for Expression Analysis of genes" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/EBSEA/inst/doc/EBSEA.R" ] }, "EBSeq": { "Package": "EBSeq", "Version": "1.14.0", "Depends": [ "blockmodeling", "gplots", "testthat", "R (>= 3.0.0)" ], "License": "Artistic-2.0", "MD5sum": "fcb77b346a9d0b02139bd2f2b095807e", "NeedsCompilation": "no", "Title": "An R package for gene and isoform differential expression analysis of RNA-seq data", "Description": "Differential Expression analysis at both gene and isoform level using RNA-seq data", "biocViews": [ "DifferentialExpression", "MultipleComparison", "RNASeq", "Sequencing", "Software", "StatisticalMethod" ], "Author": "Ning Leng, Christina Kendziorski", "Maintainer": "Ning Leng ", "source.ver": "src/contrib/EBSeq_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/EBSeq_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/EBSeq_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/EBSeq_1.14.0.tgz", "vignettes": [ "vignettes/EBSeq/inst/doc/EBSeq_Vignette.pdf" ], "vignetteTitles": [ "EBSeq Vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/EBSeq/inst/doc/EBSeq_Vignette.R" ], "dependsOnMe": [ "EBSeqHMM", "Oscope" ], "importsMe": [ "DEsubs" ], "suggestsMe": [ "compcodeR" ] }, "EBSeqHMM": { "Package": "EBSeqHMM", "Version": "1.8.0", "Depends": [ "EBSeq" ], "License": "Artistic-2.0", "MD5sum": "f0cff910dac70e72449d79e017c55085", "NeedsCompilation": "no", "Title": "Bayesian analysis for identifying gene or isoform expression changes in ordered RNA-seq experiments", "Description": "The EBSeqHMM package implements an auto-regressive hidden Markov model for statistical analysis in ordered RNA-seq experiments (e.g. time course or spatial course data). The EBSeqHMM package provides functions to identify genes and isoforms that have non-constant expression profile over the time points/positions, and cluster them into expression paths.", "biocViews": [ "Bayesian", "DifferentialExpression", "GeneExpression", "HiddenMarkovModel", "MultipleComparison", "RNASeq", "Sequencing", "Software", "StatisticalMethod", "TimeCourse" ], "Author": "Ning Leng, Christina Kendziorski", "Maintainer": "Ning Leng ", "source.ver": "src/contrib/EBSeqHMM_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/EBSeqHMM_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/EBSeqHMM_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/EBSeqHMM_1.8.0.tgz", "vignettes": [ "vignettes/EBSeqHMM/inst/doc/EBSeqHMM_vignette.pdf" ], "vignetteTitles": [ "HMM" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/EBSeqHMM/inst/doc/EBSeqHMM_vignette.R" ] }, "ecolitk": { "Package": "ecolitk", "Version": "1.46.0", "Depends": [ "R (>= 2.10)" ], "Imports": [ "Biobase", "graphics", "methods" ], "Suggests": [ "ecoliLeucine", "ecolicdf", "graph", "multtest", "affy" ], "License": "GPL (>= 2)", "MD5sum": "92c0850fe72ba6503abed258d0825b65", "NeedsCompilation": "no", "Title": "Meta-data and tools for E. coli", "Description": "Meta-data and tools to work with E. coli. The tools are mostly plotting functions to work with circular genomes. They can used with other genomes/plasmids.", "biocViews": [ "Annotation", "Software", "Visualization" ], "Author": "Laurent Gautier", "Maintainer": "Laurent Gautier ", "source.ver": "src/contrib/ecolitk_1.46.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ecolitk_1.46.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ecolitk_1.46.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ecolitk_1.46.0.tgz", "vignettes": [ "vignettes/ecolitk/inst/doc/ecolitk.pdf" ], "vignetteTitles": [ "ecolitk" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ecolitk/inst/doc/ecolitk.R" ] }, "EDASeq": { "Package": "EDASeq", "Version": "2.8.0", "Depends": [ "Biobase (>= 2.15.1)", "ShortRead (>= 1.11.42)" ], "Imports": [ "methods", "graphics", "BiocGenerics", "IRanges (>= 1.13.9)", "DESeq", "aroma.light", "Rsamtools (>= 1.5.75)", "biomaRt", "Biostrings", "AnnotationDbi", "GenomicFeatures", "GenomicRanges" ], "Suggests": [ "BiocStyle", "knitr", "yeastRNASeq", "leeBamViews", "edgeR", "KernSmooth" ], "License": "Artistic-2.0", "MD5sum": "66cf53c66753ebcd237607aeed9b7b22", "NeedsCompilation": "no", "Title": "Exploratory Data Analysis and Normalization for RNA-Seq", "Description": "Numerical and graphical summaries of RNA-Seq read data. Within-lane normalization procedures to adjust for GC-content effect (or other gene-level effects) on read counts: loess robust local regression, global-scaling, and full-quantile normalization (Risso et al., 2011). Between-lane normalization procedures to adjust for distributional differences between lanes (e.g., sequencing depth): global-scaling and full-quantile normalization (Bullard et al., 2010).", "biocViews": [ "DifferentialExpression", "Preprocessing", "QualityControl", "RNASeq", "Sequencing", "Software" ], "Author": "Davide Risso [aut, cre, cph], Sandrine Dudoit [aut], Ludwig Geistlinger [ctb]", "Maintainer": "Davide Risso ", "URL": "https://github.com/drisso/EDASeq", "VignetteBuilder": "knitr", "BugReports": "https://github.com/drisso/EDASeq/issues", "source.ver": "src/contrib/EDASeq_2.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/EDASeq_2.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/EDASeq_2.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/EDASeq_2.8.0.tgz", "vignettes": [ "vignettes/EDASeq/inst/doc/EDASeq.pdf" ], "vignetteTitles": [ "EDASeq: Exploratory Data Analysis and Normalization for RNA-Seq data" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/EDASeq/inst/doc/EDASeq.R" ], "dependsOnMe": [ "metaseqR", "RUVSeq" ], "importsMe": [ "EnrichmentBrowser", "TCGAbiolinks" ], "suggestsMe": [ "HTSFilter", "oneChannelGUI" ] }, "EDDA": { "Package": "EDDA", "Version": "1.12.0", "Depends": [ "Rcpp (>= 0.10.4)", "parallel", "methods", "ROCR", "DESeq", "baySeq", "snow", "edgeR" ], "Imports": [ "graphics", "stats", "utils", "parallel", "methods", "ROCR", "DESeq", "baySeq", "snow", "edgeR" ], "LinkingTo": [ "Rcpp" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "5221bcd28dabf657ab24d3ab39105248", "NeedsCompilation": "yes", "Title": "Experimental Design in Differential Abundance analysis", "Description": "EDDA can aid in the design of a range of common experiments such as RNA-seq, Nanostring assays, RIP-seq and Metagenomic sequencing, and enables researchers to comprehensively investigate the impact of experimental decisions on the ability to detect differential abundance. This work was published on 3 December 2014 at Genome Biology under the title \"The importance of study design for detecting differentially abundant features in high-throughput experiments\" (http://genomebiology.com/2014/15/12/527).", "biocViews": [ "ChIPSeq", "ExperimentalDesign", "Normalization", "RNASeq", "Sequencing", "Software" ], "Author": "Li Juntao, Luo Huaien, Chia Kuan Hui Burton, Niranjan Nagarajan", "Maintainer": "Chia Kuan Hui Burton , Niranjan Nagarajan ", "URL": "http://edda.gis.a-star.edu.sg/, http://genomebiology.com/2014/15/12/527", "source.ver": "src/contrib/EDDA_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/EDDA_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/EDDA_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/EDDA_1.12.0.tgz", "vignettes": [ "vignettes/EDDA/inst/doc/EDDA.pdf" ], "vignetteTitles": [ "EDDA Vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false }, "edge": { "Package": "edge", "Version": "2.6.0", "Depends": [ "R(>= 3.1.0)", "Biobase" ], "Imports": [ "methods", "splines", "sva", "snm", "jackstraw", "qvalue(>= 1.99.0)", "MASS" ], "Suggests": [ "testthat", "knitr", "ggplot2", "reshape2" ], "License": "MIT + file LICENSE", "Archs": "i386, x64", "MD5sum": "2a58fdb50b8f4690454eb84701725701", "NeedsCompilation": "yes", "Title": "Extraction of Differential Gene Expression", "Description": "The edge package implements methods for carrying out differential expression analyses of genome-wide gene expression studies. Significance testing using the optimal discovery procedure and generalized likelihood ratio tests (equivalent to F-tests and t-tests) are implemented for general study designs. Special functions are available to facilitate the analysis of common study designs, including time course experiments. Other packages such as snm, sva, and qvalue are integrated in edge to provide a wide range of tools for gene expression analysis.", "biocViews": [ "DataImport", "DifferentialExpression", "GeneExpression", "MultipleComparison", "Regression", "Software", "TimeCourse" ], "Author": "John D. Storey, Jeffrey T. Leek and Andrew J. Bass", "Maintainer": "John D. Storey , Andrew J. Bass ", "URL": "https://github.com/jdstorey/edge", "VignetteBuilder": "knitr", "BugReports": "https://github.com/jdstorey/edge/issues", "source.ver": "src/contrib/edge_2.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/edge_2.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/edge_2.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/edge_2.6.0.tgz", "vignettes": [ "vignettes/edge/inst/doc/edge.pdf" ], "vignetteTitles": [ "edge Package" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/edge/inst/doc/edge.R" ] }, "edgeR": { "Package": "edgeR", "Version": "3.16.5", "Depends": [ "R (>= 2.15.0)", "limma" ], "Imports": [ "graphics", "stats", "utils", "methods", "locfit" ], "Suggests": [ "MASS", "statmod", "splines", "KernSmooth" ], "License": "GPL (>=2)", "Archs": "i386, x64", "MD5sum": "7fa050082478fb13173ee758342a6861", "NeedsCompilation": "yes", "Title": "Empirical Analysis of Digital Gene Expression Data in R", "Description": "Differential expression analysis of RNA-seq expression profiles with biological replication. Implements a range of statistical methodology based on the negative binomial distributions, including empirical Bayes estimation, exact tests, generalized linear models and quasi-likelihood tests. As well as RNA-seq, it be applied to differential signal analysis of other types of genomic data that produce counts, including ChIP-seq, SAGE and CAGE.", "biocViews": [ "AlternativeSplicing", "BatchEffect", "Bayesian", "ChIPSeq", "Clustering", "Coverage", "DifferentialExpression", "DifferentialSplicing", "GeneExpression", "GeneSetEnrichment", "Genetics", "MultipleComparison", "Normalization", "QualityControl", "RNASeq", "Regression", "SAGE", "Sequencing", "Software", "TimeCourse", "Transcription" ], "Author": "Yunshun Chen , Aaron Lun , Davis McCarthy , Xiaobei Zhou , Mark Robinson , Gordon Smyth ", "Maintainer": "Yunshun Chen , Aaron Lun , Mark Robinson , Davis McCarthy , Gordon Smyth ", "URL": "http://bioinf.wehi.edu.au/edgeR", "source.ver": "src/contrib/edgeR_3.16.5.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/edgeR_3.16.5.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/edgeR_3.16.5.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/edgeR_3.16.5.tgz", "vignettes": [ "vignettes/edgeR/inst/doc/edgeR.pdf", "vignettes/edgeR/inst/doc/edgeRUsersGuide.pdf" ], "vignetteTitles": [ "edgeR Vignette", "edgeRUsersGuide.pdf" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "dependsOnMe": [ "ASpli", "DBChIP", "EDDA", "manta", "methylMnM", "MLSeq", "RnaSeqSampleSizeData", "RUVSeq", "TCC", "tRanslatome" ], "importsMe": [ "affycoretools", "ampliQueso", "ArrayExpressHTS", "baySeq", "compcodeR", "csaw", "debrowser", "DEFormats", "DEGreport", "DEsubs", "DiffBind", "diffHic", "diffloop", "DRIMSeq", "easyRNASeq", "EBSEA", "EDDA", "eegc", "EGSEA", "EnrichmentBrowser", "erccdashboard", "Glimma", "HTSFilter", "MEDIPS", "metaseqR", "msmsTests", "PROPER", "regsplice", "Repitools", "ReportingTools", "rnaSeqMap", "RnaSeqSampleSize", "scater", "scde", "scran", "STATegRa", "SVAPLSseq", "systemPipeR", "TCGAbiolinks", "ToPASeq", "tweeDEseq", "yarn" ], "suggestsMe": [ "biobroom", "BitSeq", "ClassifyR", "clonotypeR", "cqn", "EDASeq", "gage", "gCrisprTools", "GenomicAlignments", "GenomicRanges", "goseq", "groHMM", "GSAR", "GSVA", "JctSeqData", "leeBamViews", "missMethyl", "oneChannelGUI", "regionReport", "SSPA", "subSeq", "tximport", "variancePartition" ] }, "eegc": { "Package": "eegc", "Version": "1.0.0", "Depends": [ "R (>= 3.3.0)" ], "Imports": [ "R.utils", "gplots", "sna", "wordcloud", "igraph", "pheatmap", "edgeR", "DESeq2", "clusterProfiler", "S4Vectors", "ggplot2", "org.Hs.eg.db", "org.Mm.eg.db", "limma", "DOSE", "AnnotationDbi" ], "Suggests": [ "knitr" ], "License": "GPL-2", "MD5sum": "5bb152aa0332698179a2bebb9bada0bb", "NeedsCompilation": "no", "Title": "Engineering Evaluation by Gene Categorization (eegc)", "Description": "This package has been developed to evaluate cellular engineering processes for direct differentiation of stem cells or conversion (transdifferentiation) of somatic cells to primary cells based on high throughput gene expression data screened either by DNA microarray or RNA sequencing. The package takes gene expression profiles as inputs from three types of samples: (i) somatic or stem cells to be (trans)differentiated (input of the engineering process), (ii) induced cells to be evaluated (output of the engineering process) and (iii) target primary cells (reference for the output). The package performs differential gene expression analysis for each pair-wise sample comparison to identify and evaluate the transcriptional differences among the 3 types of samples (input, output, reference). The ideal goal is to have induced and primary reference cell showing overlapping profiles, both very different from the original cells.", "biocViews": [ "DifferentialExpression", "GeneExpression", "GeneRegulation", "GeneSetEnrichment", "GeneTarget", "Microarray", "RNASeq", "Sequencing", "Software" ], "Author": "Xiaoyuan Zhou, Guofeng Meng, Christine Nardini, Hongkang Mei", "Maintainer": "Xiaoyuan Zhou ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/eegc_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/eegc_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/eegc_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/eegc_1.0.0.tgz", "vignettes": [ "vignettes/eegc/inst/doc/eegc.pdf" ], "vignetteTitles": [ "Engineering Evaluation by Gene Categorization (eegc)" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/eegc/inst/doc/eegc.R" ] }, "EGAD": { "Package": "EGAD", "Version": "1.2.0", "Depends": [ "R(>= 3.3)" ], "Imports": [ "gplots", "Biobase", "GEOquery", "limma", "arrayQualityMetrics", "impute", "RColorBrewer", "zoo", "igraph", "plyr", "Matrix", "MASS", "RCurl", "affy" ], "Suggests": [ "knitr", "rmarkdown", "testthat" ], "License": "GPL-2", "MD5sum": "7ae2bb13243ba5b828a22938095e8708", "NeedsCompilation": "no", "Title": "Extending guilt by association by degree", "Description": "The package implements a series of highly efficient tools to calculate functional properties of networks based on guilt by association methods.", "biocViews": [ "FunctionalGenomics", "FunctionalPrediction", "GenePrediction", "GraphAndNetwork", "Network", "NetworkEnrichment", "Software", "SystemsBiology" ], "Author": "Sara Ballouz [aut, cre], Melanie Weber [aut, ctb], Paul Pavlidis [aut], Jesse Gillis [aut, ctb]", "Maintainer": "Sara Ballouz ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/EGAD_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/EGAD_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/EGAD_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/EGAD_1.2.0.tgz", "vignettes": [ "vignettes/EGAD/inst/doc/EGAD.pdf" ], "vignetteTitles": [ "\"EGAD user guide\"" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/EGAD/inst/doc/EGAD.R" ] }, "EGSEA": { "Package": "EGSEA", "Version": "1.2.0", "Depends": [ "R (>= 3.3)", "Biobase", "gage (>= 2.14.4)", "AnnotationDbi", "topGO (>= 2.16.0)", "pathview (>= 1.4.2)" ], "Imports": [ "PADOG (>= 1.6.0)", "GSVA (>= 1.12.0)", "globaltest (>= 5.18.0)", "limma (>= 3.20.9)", "edgeR (>= 3.6.8)", "HTMLUtils (>= 0.1.5)", "hwriter (>= 1.2.2)", "gplots (>= 2.14.2)", "ggplot2 (>= 1.0.0)", "safe (>= 3.4.0)", "stringi (>= 0.5.0)", "parallel", "stats", "metap", "grDevices", "graphics", "utils", "org.Hs.eg.db", "org.Mm.eg.db", "org.Rn.eg.db", "RColorBrewer", "methods", "EGSEAdata" ], "Suggests": [ "BiocStyle", "knitr", "testthat" ], "License": "GPL-2", "MD5sum": "8142ada223aa3d0cb80a60b12a3b3ca5", "NeedsCompilation": "no", "Title": "Ensemble of Gene Set Enrichment Analyses", "Description": "This package implements the Ensemble of Gene Set Enrichment Analyses (EGSEA) method for gene set testing.", "biocViews": [ "DifferentialExpression", "GO", "GeneExpression", "GeneSetEnrichment", "Genetics", "GraphAndNetwork", "KEGG", "Metabolomics", "Microarray", "MultipleComparison", "OneChannel", "Pathways", "Proteomics", "RNASeq", "Sequencing", "Software", "SystemsBiology", "TwoChannel" ], "Author": "Monther Alhamdoosh, Milica Ng and Matthew Ritchie", "Maintainer": "Monther Alhamdoosh ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/EGSEA_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/EGSEA_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/EGSEA_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/EGSEA_1.2.0.tgz", "vignettes": [ "vignettes/EGSEA/inst/doc/EGSEA.pdf" ], "vignetteTitles": [ "EGSEA vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/EGSEA/inst/doc/EGSEA.R" ], "suggestsMe": [ "EGSEAdata" ] }, "eiR": { "Package": "eiR", "Version": "1.14.1", "Depends": [ "R (>= 2.10.0)", "ChemmineR (>= 2.15.15)", "methods", "DBI" ], "Imports": [ "snow", "tools", "snowfall", "RUnit", "methods", "ChemmineR", "RCurl", "digest", "BiocGenerics" ], "LinkingTo": [ "BH" ], "Suggests": [ "RCurl", "snow", "BiocStyle", "knitcitations", "knitr", "knitrBootstrap" ], "License": "Artistic-2.0", "MD5sum": "a443353df0c6469aac5b516de63d6b75", "NeedsCompilation": "yes", "Title": "Accelerated similarity searching of small molecules", "Description": "The eiR package provides utilities for accelerated structure similarity searching of very large small molecule data sets using an embedding and indexing approach.", "biocViews": [ "BiomedicalInformatics", "CellBasedAssays", "Cheminformatics", "Clustering", "DataImport", "Infrastructure", "MicrotitrePlateAssay", "Pharmacogenetics", "Pharmacogenomics", "Proteomics", "Software", "Visualization" ], "Author": "Kevin Horan, Yiqun Cao and Tyler Backman", "Maintainer": "Thomas Girke ", "URL": "https://github.com/girke-lab/eiR", "SystemRequirements": "GSL (>=1.14) http://www.gnu.org/software/gsl/", "VignetteBuilder": "knitr", "source.ver": "src/contrib/eiR_1.14.1.tar.gz", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/eiR_1.14.1.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": true, "hasLICENSE": true, "Rfiles": [ "vignettes/eiR/inst/doc/eiR.R" ], "htmlDocs": [ "vignettes/eiR/inst/doc/eiR.html" ], "htmlTitles": [ "eiR" ] }, "eisa": { "Package": "eisa", "Version": "1.26.0", "Depends": [ "isa2", "Biobase (>= 2.17.8)", "AnnotationDbi", "methods" ], "Imports": [ "BiocGenerics", "Category", "genefilter", "DBI" ], "Suggests": [ "igraph (>= 0.6)", "Matrix", "GOstats", "GO.db", "KEGG.db", "biclust", "MASS", "xtable", "ALL", "hgu95av2.db", "targetscan.Hs.eg.db", "org.Hs.eg.db" ], "License": "GPL (>= 2)", "MD5sum": "a4b012c00d3bf9c469ae31db7cf7218f", "NeedsCompilation": "no", "Title": "Expression data analysis via the Iterative Signature Algorithm", "Description": "The Iterative Signature Algorithm (ISA) is a biclustering method; it finds correlated blocks (transcription modules) in gene expression (or other tabular) data. The ISA is capable of finding overlapping modules and it is resilient to noise. This package provides a convenient interface to the ISA, using standard BioConductor data structures; and also contains various visualization tools that can be used with other biclustering algorithms.", "biocViews": [ "Classification", "GeneExpression", "Microarray", "Software", "Visualization" ], "Author": "Gabor Csardi ", "Maintainer": "Gabor Csardi ", "source.ver": "src/contrib/eisa_1.26.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/eisa_1.26.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/eisa_1.26.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/eisa_1.26.0.tgz", "vignettes": [ "vignettes/eisa/inst/doc/EISA_tutorial.pdf" ], "vignetteTitles": [ "The Iterative Signature Algorithm for Gene Expression Data" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/eisa/inst/doc/EISA_tutorial.R" ], "dependsOnMe": [ "ExpressionView" ], "importsMe": [ "ExpressionView" ] }, "ELBOW": { "Package": "ELBOW", "Version": "1.10.0", "Depends": [ "R (>= 2.15.0)" ], "Suggests": [ "DESeq", "GEOquery", "limma", "simpleaffy", "affyPLM", "RColorBrewer" ], "License": "file LICENSE", "License_is_FOSS": "yes", "License_restricts_use": "no", "MD5sum": "f644fa05be5f0c1889cea6adc23df955", "NeedsCompilation": "no", "Title": "ELBOW - Evaluating foLd change By the lOgit Way", "Description": "Elbow an improved fold change test that uses cluster analysis and pattern recognition to set cut off limits that are derived directly from intrareplicate variance without assuming a normal distribution for as few as 2 biological replicates. Elbow also provides the same consistency as fold testing in cross platform analysis. Elbow has lower false positive and false negative rates than standard fold testing when both are evaluated using T testing and Statistical Analysis of Microarray using 12 replicates (six replicates each for initial and final conditions). Elbow provides a null value based on initial condition replicates and gives error bounds for results to allow better evaluation of significance.", "biocViews": [ "GeneExpression", "Microarray", "MultiChannel", "OneChannel", "RNASeq", "Sequencing", "Software", "Technology", "TwoChannel" ], "Author": "Xiangli Zhang, Natalie Bjorklund, Graham Alvare, Tom Ryzdak, Richard Sparling, Brian Fristensky", "Maintainer": "Graham Alvare , Xiangli Zhang ", "source.ver": "src/contrib/ELBOW_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ELBOW_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ELBOW_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ELBOW_1.10.0.tgz", "vignettes": [ "vignettes/ELBOW/inst/doc/Elbow_tutorial_vignette.pdf" ], "vignetteTitles": [ "Using ELBOW --- the definitive ELBOW tutorial" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/ELBOW/inst/doc/Elbow_tutorial_vignette.R" ] }, "ELMER": { "Package": "ELMER", "Version": "1.4.1", "Depends": [ "R (>= 3.2.0)", "IlluminaHumanMethylation450kanno.ilmn12.hg19", "Homo.sapiens", "ELMER.data" ], "Imports": [ "methods", "BiocGenerics", "S4Vectors", "IRanges", "GenomeInfoDb", "GenomicRanges", "ggplot2", "reshape", "grid", "gridExtra", "minfi", "GenomicFeatures" ], "Suggests": [ "parallel", "snow", "BiocStyle", "knitr", "R.utils", "downloader" ], "License": "GPL-3", "MD5sum": "b63a5fe0d5ecb731ee8456100298d3ff", "NeedsCompilation": "no", "Title": "Inferring Regulatory Element Landscapes and Transcription Factor Networks Using Cancer Methylomes", "Description": "ELMER is designed to use DNA methylation and gene expression from a large number of samples to infere regulatory element landscape and transcription factor network in primary tissue.", "biocViews": [ "DNAMethylation", "GeneExpression", "GeneRegulation", "MotifAnnotation", "Software" ], "Author": "Lijing Yao [aut], Ben Berman [aut], Peggy Farnham [aut], Hui Shen [ctb], Peter Laird [ctb], Simon Coetzee [cre, ctb]", "Maintainer": "Simon Coetzee ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/ELMER_1.4.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ELMER_1.4.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ELMER_1.4.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ELMER_1.4.1.tgz", "vignettes": [ "vignettes/ELMER/inst/doc/vignettes.pdf" ], "vignetteTitles": [ "ELMER: Inferring Regulatory Element Landscapes and Transcription Factor Networks Using Methylomes" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ELMER/inst/doc/vignettes.R" ] }, "EMDomics": { "Package": "EMDomics", "Version": "2.4.0", "Depends": [ "R (>= 3.2.1)" ], "Imports": [ "emdist", "BiocParallel", "matrixStats", "ggplot2", "CDFt", "preprocessCore" ], "Suggests": [ "knitr" ], "License": "MIT + file LICENSE", "MD5sum": "f23af14934fd7e1961bec0dcc38ce02a", "NeedsCompilation": "no", "Title": "Earth Mover's Distance for Differential Analysis of Genomics Data", "Description": "The EMDomics algorithm is used to perform a supervised multi-class analysis to measure the magnitude and statistical significance of observed continuous genomics data between groups. Usually the data will be gene expression values from array-based or sequence-based experiments, but data from other types of experiments can also be analyzed (e.g. copy number variation). Traditional methods like Significance Analysis of Microarrays (SAM) and Linear Models for Microarray Data (LIMMA) use significance tests based on summary statistics (mean and standard deviation) of the distributions. This approach lacks power to identify expression differences between groups that show high levels of intra-group heterogeneity. The Earth Mover's Distance (EMD) algorithm instead computes the \"work\" needed to transform one distribution into another, thus providing a metric of the overall difference in shape between two distributions. Permutation of sample labels is used to generate q-values for the observed EMD scores. This package also incorporates the Komolgorov-Smirnov (K-S) test and the Cramer von Mises test (CVM), which are both common distribution comparison tests.", "biocViews": [ "DifferentialExpression", "GeneExpression", "Microarray", "Software" ], "Author": "Sadhika Malladi [aut, cre], Daniel Schmolze [aut, cre], Andrew Beck [aut], Sheida Nabavi [aut]", "Maintainer": "Sadhika Malladi and Daniel Schmolze ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/EMDomics_2.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/EMDomics_2.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/EMDomics_2.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/EMDomics_2.4.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/EMDomics/inst/doc/EMDomics.R" ], "htmlDocs": [ "vignettes/EMDomics/inst/doc/EMDomics.html" ], "htmlTitles": [ "EMDomics Vignette" ] }, "EmpiricalBrownsMethod": { "Package": "EmpiricalBrownsMethod", "Version": "1.2.0", "Depends": [ "R (>= 3.2.0)" ], "Suggests": [ "BiocStyle", "testthat", "knitr", "rmarkdown" ], "License": "MIT + file LICENSE", "MD5sum": "c8f49bd24ec89c908e785885eb4472f4", "NeedsCompilation": "no", "Title": "Uses Brown's method to combine p-values from dependent tests", "Description": "Combining P-values from multiple statistical tests is common in bioinformatics. However, this procedure is non-trivial for dependent P-values. This package implements an empirical adaptation of Brown’s Method (an extension of Fisher’s Method) for combining dependent P-values which is appropriate for highly correlated data sets found in high-throughput biological experiments.", "biocViews": [ "GeneExpression", "Pathways", "Software", "StatisticalMethod" ], "Author": "William Poole", "Maintainer": "David Gibbs ", "URL": "https://github.com/IlyaLab/CombiningDependentPvaluesUsingEBM.git", "VignetteBuilder": "knitr", "source.ver": "src/contrib/EmpiricalBrownsMethod_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/EmpiricalBrownsMethod_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/EmpiricalBrownsMethod_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/EmpiricalBrownsMethod_1.2.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/EmpiricalBrownsMethod/inst/doc/ebmVignette.R" ], "htmlDocs": [ "vignettes/EmpiricalBrownsMethod/inst/doc/ebmVignette.html" ], "htmlTitles": [ "Empirical Browns Method" ] }, "ENCODExplorer": { "Package": "ENCODExplorer", "Version": "2.0.6", "Depends": [ "R (>= 3.3)", "shiny", "DT", "shinythemes" ], "Imports": [ "tools", "jsonlite", "parallel", "RCurl", "tidyr", "data.table", "dplyr", "stringr", "stringi" ], "Suggests": [ "RUnit", "BiocGenerics", "knitr", "curl", "httr" ], "License": "Artistic-2.0", "MD5sum": "2201a50cc000505366ddb53d2b023e13", "NeedsCompilation": "no", "Title": "A compilation of ENCODE metadata", "Description": "This package allows user to quickly access ENCODE project files metadata and give access to helper functions to query the ENCODE rest api, download ENCODE datasets and save the database in SQLite format.", "biocViews": [ "DataImport", "Infrastructure", "Software" ], "Author": "Charles Joly Beauparlant [aut, cre], Audrey Lemacon [aut], Arnaud Droit [aut], Louis Gendron [ctb], Astrid-Louise Deschenes [ctb]", "Maintainer": "Charles Joly Beauparlant ", "VignetteBuilder": "knitr", "BugReports": "https://github.com/CharlesJB/ENCODExplorer/issues", "source.ver": "src/contrib/ENCODExplorer_2.0.6.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ENCODExplorer_2.0.6.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ENCODExplorer_2.0.6.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ENCODExplorer_2.0.6.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ENCODExplorer/inst/doc/DataUpdate.R", "vignettes/ENCODExplorer/inst/doc/DBmodel.R", "vignettes/ENCODExplorer/inst/doc/ENCODExplorer.R" ], "htmlDocs": [ "vignettes/ENCODExplorer/inst/doc/DataUpdate.html", "vignettes/ENCODExplorer/inst/doc/DBmodel.html", "vignettes/ENCODExplorer/inst/doc/ENCODExplorer.html" ], "htmlTitles": [ "Data update", "Database model", "Introduction to ENCODExplorer" ] }, "ENmix": { "Package": "ENmix", "Version": "1.10.0", "Depends": [ "minfi", "parallel", "doParallel", "Biobase (>= 2.17.8)", "foreach" ], "Imports": [ "MASS", "preprocessCore", "wateRmelon", "sva", "geneplotter", "impute", "grDevices", "graphics", "stats" ], "Suggests": [ "minfiData (>= 0.4.1)", "RPMM", "RUnit", "BiocGenerics" ], "License": "Artistic-2.0", "MD5sum": "2c44baf7cc05c58e1968b113c16f69ec", "NeedsCompilation": "no", "Title": "Data preprocessing and quality control for Illumina HumanMethylation450 and MethylationEPIC BeadChip", "Description": "Illumina Methylation BeadChip array measurements have intrinsic levels of background noise that degrade methylation measurement. The ENmix package provides an efficient data pre-processing tool designed to reduce background noise and improve signal for DNA methylation estimation. Several efficient novel methods were incorporated in the package: ENmix is a model based background correction method that can significantly improve accuracy and reproducibility of methylation measures; RCP taking advantage of the high spatial correlation of DNA methylation levels between nearby type I and II probe pairs to reduce probe type bias and improve data quality on type II probe measures.The data structure used by the ENmix package is compatible with several other related R packages, such as minfi, wateRmelon and ChAMP, providing straightforward integration of ENmix-corrected datasets for subsequent data analysis. The software is designed to support large scale data analysis, and provides multi-processor parallel computing wrappers for some commonly used but computation intensive data preprocessing methods. In addition ENmix package has selectable complementary functions for efficient data visualization (such as data distribution plotting), quality control (identification and filtering of low quality data points, samples, probes, and outliers, along with imputation of missing values), inter-array normalization (3 different quantile normalizations), identification of probes with multimodal distributions due to SNPs and other factors, and exploration of data variance structure using principal component regression analysis plots. Together these provide a set of flexible and transparent tools for preprocessing of EWAS data in a computationally-efficient and user-friendly package.", "biocViews": [ "BatchEffect", "DNAMethylation", "DataImport", "MethylationArray", "Microarray", "Normalization", "OneChannel", "Preprocessing", "PrincipalComponent", "QualityControl", "Regression", "Software", "TwoChannel" ], "Author": "Zongli Xu [cre, aut], Liang Niu [aut], Leping Li [ctb], Jack Taylor [ctb]", "Maintainer": "Zongli Xu ", "source.ver": "src/contrib/ENmix_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ENmix_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ENmix_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ENmix_1.10.0.tgz", "vignettes": [ "vignettes/ENmix/inst/doc/ENmix.pdf" ], "vignetteTitles": [ "ENmix User's Guide" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ENmix/inst/doc/ENmix.R" ] }, "EnrichedHeatmap": { "Package": "EnrichedHeatmap", "Version": "1.4.0", "Depends": [ "R (>= 3.1.2)", "grid", "ComplexHeatmap (>= 1.11.1)", "GenomicRanges", "IRanges", "locfit" ], "Imports": [ "methods", "matrixStats", "stats", "GetoptLong" ], "Suggests": [ "testthat (>= 0.3)", "knitr", "markdown", "circlize (>= 0.3.1)" ], "License": "GPL (>= 2)", "MD5sum": "e5278b5981542a99689b539ba0801b26", "NeedsCompilation": "no", "Title": "Making Enriched Heatmaps", "Description": "Enriched heatmap is a special type of heatmap which visualizes the enrichment of genomic signals on specific target regions. Here we implement enriched heatmap by ComplexHeatmap package. Since this type of heatmap is just a normal heatmap but with some special settings, with the functionality of ComplexHeatmap, it would be much easier to customize the heatmap as well as concatenating to a list of heatmaps to show correspondance between different data sources.", "biocViews": [ "Coverage", "GenomeAnnotation", "Sequencing", "Software", "Visualization" ], "Author": "Zuguang Gu", "Maintainer": "Zuguang Gu ", "URL": "https://github.com/jokergoo/EnrichedHeatmap", "VignetteBuilder": "knitr", "source.ver": "src/contrib/EnrichedHeatmap_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/EnrichedHeatmap_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/EnrichedHeatmap_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/EnrichedHeatmap_1.4.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/EnrichedHeatmap/inst/doc/EnrichedHeatmap.R" ], "htmlDocs": [ "vignettes/EnrichedHeatmap/inst/doc/EnrichedHeatmap.html" ], "htmlTitles": [ "Make Enriched Heatmaps" ] }, "EnrichmentBrowser": { "Package": "EnrichmentBrowser", "Version": "2.4.6", "Depends": [ "R(>= 3.0.0)", "Biobase", "GSEABase", "pathview" ], "Imports": [ "AnnotationDbi", "ComplexHeatmap", "DESeq2", "EDASeq", "GO.db", "KEGGREST", "KEGGgraph", "MASS", "ReportingTools", "Rgraphviz", "S4Vectors", "SPIA", "SummarizedExperiment", "biocGraph", "edgeR", "geneplotter", "graph", "hwriter", "limma", "methods", "safe", "topGO" ], "Suggests": [ "ALL", "BiocStyle", "airway", "hgu95av2.db" ], "License": "Artistic-2.0", "MD5sum": "6688b6e75a81d148b8cc5245c495c765", "NeedsCompilation": "no", "Title": "Seamless navigation through combined results of set-based and network-based enrichment analysis", "Description": "The EnrichmentBrowser package implements essential functionality for the enrichment analysis of gene expression data. The analysis combines the advantages of set-based and network-based enrichment analysis in order to derive high-confidence gene sets and biological pathways that are differentially regulated in the expression data under investigation. Besides, the package facilitates the visualization and exploration of such sets and pathways.", "biocViews": [ "DifferentialExpression", "GeneExpression", "GeneSetEnrichment", "GraphAndNetwork", "Microarray", "Network", "NetworkEnrichment", "Pathways", "RNASeq", "ReportWriting", "Software", "Visualization" ], "Author": "Ludwig Geistlinger, Gergely Csaba, Ralf Zimmer", "Maintainer": "Ludwig Geistlinger ", "source.ver": "src/contrib/EnrichmentBrowser_2.4.6.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/EnrichmentBrowser_2.4.6.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/EnrichmentBrowser_2.4.6.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/EnrichmentBrowser_2.4.6.tgz", "vignettes": [ "vignettes/EnrichmentBrowser/inst/doc/EnrichmentBrowser.pdf" ], "vignetteTitles": [ "EnrichmentBrowser Manual" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/EnrichmentBrowser/inst/doc/EnrichmentBrowser.R" ] }, "ensembldb": { "Package": "ensembldb", "Version": "1.6.2", "Depends": [ "BiocGenerics (>= 0.15.10)", "GenomicRanges (>= 1.23.21)", "GenomicFeatures (>= 1.23.18)" ], "Imports": [ "methods", "RSQLite", "DBI", "Biobase", "GenomeInfoDb", "AnnotationDbi (>= 1.31.19)", "rtracklayer", "S4Vectors", "AnnotationHub", "Rsamtools", "IRanges" ], "Suggests": [ "BiocStyle", "knitr", "rmarkdown", "EnsDb.Hsapiens.v75 (>= 0.99.7)", "RUnit", "shiny", "Gviz", "BSgenome.Hsapiens.UCSC.hg19" ], "Enhances": [ "RMySQL" ], "License": "LGPL", "MD5sum": "f7642a87638f6d4373cfabae899aaae0", "NeedsCompilation": "no", "Title": "Utilities to create and use an Ensembl based annotation database", "Description": "The package provides functions to create and use transcript centric annotation databases/packages. The annotation for the databases are directly fetched from Ensembl using their Perl API. The functionality and data is similar to that of the TxDb packages from the GenomicFeatures package, but, in addition to retrieve all gene/transcript models and annotations from the database, the ensembldb package provides also a filter framework allowing to retrieve annotations for specific entries like genes encoded on a chromosome region or transcript models of lincRNA genes.", "biocViews": [ "AnnotationData", "Coverage", "Genetics", "Sequencing", "Software" ], "Author": "Johannes Rainer , Tim Triche ", "Maintainer": "Johannes Rainer ", "URL": "https://github.com/jotsetung/ensembldb", "VignetteBuilder": "knitr", "BugReports": "https://github.com/jotsetung/ensembldb/issues", "source.ver": "src/contrib/ensembldb_1.6.2.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ensembldb_1.6.2.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ensembldb_1.6.2.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ensembldb_1.6.2.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ensembldb/inst/doc/ensembldb.R", "vignettes/ensembldb/inst/doc/MySQL-backend.R" ], "htmlDocs": [ "vignettes/ensembldb/inst/doc/ensembldb.html", "vignettes/ensembldb/inst/doc/MySQL-backend.html" ], "htmlTitles": [ "Generating an using Ensembl based annotation packages", "Using a MySQL server backend" ], "importsMe": [ "biovizBase", "ChIPpeakAnno", "ggbio", "TVTB" ], "suggestsMe": [ "alpine" ], "dependsOnMe": [ "EnsDb.Hsapiens.v75", "EnsDb.Hsapiens.v79", "EnsDb.Hsapiens.v86", "EnsDb.Mmusculus.v75", "EnsDb.Mmusculus.v79", "EnsDb.Rnorvegicus.v75", "EnsDb.Rnorvegicus.v79" ] }, "ensemblVEP": { "Package": "ensemblVEP", "Version": "1.14.0", "Depends": [ "methods", "BiocGenerics", "GenomicRanges", "VariantAnnotation" ], "Imports": [ "S4Vectors (>= 0.9.25)", "Biostrings", "SummarizedExperiment", "GenomeInfoDb" ], "Suggests": [ "RUnit" ], "License": "Artistic-2.0", "MD5sum": "335bdb275bf79dbaf7960d0762df511b", "NeedsCompilation": "no", "Title": "R Interface to Ensembl Variant Effect Predictor", "Description": "Query the Ensembl Variant Effect Predictor via the perl API", "biocViews": [ "Annotation", "SNP", "Software", "VariantAnnotation" ], "Author": "Valerie Obenchain", "Maintainer": "Bioconductor Package Maintainer ", "SystemRequirements": "Ensembl VEP (API version 86) and the Perl package DBD::mysql must be installed. See the package README and Ensembl web site, http://www.ensembl.org/info/docs/tools/vep/index.html for installation instructions.", "source.ver": "src/contrib/ensemblVEP_1.14.0.tar.gz", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ensemblVEP_1.14.0.tgz", "vignettes": [ "vignettes/ensemblVEP/inst/doc/ensemblVEP.pdf" ], "vignetteTitles": [ "ensemblVEP" ], "hasREADME": true, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ensemblVEP/inst/doc/ensemblVEP.R" ], "importsMe": [ "TVTB" ] }, "ENVISIONQuery": { "Package": "ENVISIONQuery", "Version": "1.22.0", "Depends": [ "rJava", "XML", "utils" ], "License": "GPL-2", "MD5sum": "3337c90cae18975b5c7df7a3368874aa", "NeedsCompilation": "no", "Title": "Retrieval from the ENVISION bioinformatics data portal into R", "Description": "Tools to retrieve data from ENVISION, the Database for Annotation, Visualization and Integrated Discovery portal", "biocViews": [ "Annotation", "Software" ], "Author": "Alex Lisovich, Roger Day", "Maintainer": "Alex Lisovich , Roger Day ", "source.ver": "src/contrib/ENVISIONQuery_1.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ENVISIONQuery_1.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ENVISIONQuery_1.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ENVISIONQuery_1.22.0.tgz", "vignettes": [ "vignettes/ENVISIONQuery/inst/doc/ENVISIONQuery.pdf" ], "vignetteTitles": [ "An R Package for retrieving data from EnVision into R objects." ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ENVISIONQuery/inst/doc/ENVISIONQuery.R" ], "importsMe": [ "IdMappingRetrieval" ] }, "epigenomix": { "Package": "epigenomix", "Version": "1.14.0", "Depends": [ "R (>= 3.2.0)", "methods", "Biobase", "S4Vectors", "IRanges", "GenomicRanges", "SummarizedExperiment" ], "Imports": [ "BiocGenerics", "MCMCpack", "Rsamtools", "parallel", "GenomeInfoDb", "beadarray" ], "License": "LGPL-3", "MD5sum": "6f93379a1d79d6a5758ab7048fa80df7", "NeedsCompilation": "no", "Title": "Epigenetic and gene transcription data normalization and integration with mixture models", "Description": "A package for the integrative analysis of RNA-seq or microarray based gene transcription and histone modification data obtained by ChIP-seq. The package provides methods for data preprocessing and matching as well as methods for fitting bayesian mixture models in order to detect genes with differences in both data types.", "biocViews": [ "ChIPSeq", "Classification", "DifferentialExpression", "GeneExpression", "Software" ], "Author": "Hans-Ulrich Klein, Martin Schaefer", "Maintainer": "Hans-Ulrich Klein ", "source.ver": "src/contrib/epigenomix_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/epigenomix_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/epigenomix_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/epigenomix_1.14.0.tgz", "vignettes": [ "vignettes/epigenomix/inst/doc/epigenomix.pdf" ], "vignetteTitles": [ "epigenomix package vignette" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/epigenomix/inst/doc/epigenomix.R" ] }, "epivizr": { "Package": "epivizr", "Version": "2.4.1", "Depends": [ "R (>= 3.3)", "methods" ], "Imports": [ "epivizrServer (>= 1.1.1)", "epivizrData (>= 1.1.1)", "GenomicRanges", "S4Vectors", "IRanges" ], "Suggests": [ "testthat", "roxygen2", "knitr", "Biobase", "SummarizedExperiment", "antiProfilesData", "hgu133plus2.db", "Mus.musculus", "BiocStyle" ], "License": "Artistic-2.0", "MD5sum": "3dfe1f592f6a7ce307441c6fd8a4e2b2", "NeedsCompilation": "no", "Title": "R Interface to epiviz web app", "Description": "This package provides connections to the epiviz web app (http://epiviz.cbcb.umd.edu) for interactive visualization of genomic data. Objects in R/bioc interactive sessions can be displayed in genome browser tracks or plots to be explored by navigation through genomic regions. Fundamental Bioconductor data structures are supported (e.g., GenomicRanges and RangedSummarizedExperiment objects), while providing an easy mechanism to support other data structures (through package epivizrData). Visualizations (using d3.js) can be easily added to the web app as well.", "biocViews": [ "GUI", "Infrastructure", "Software", "Visualization" ], "Author": "Hector Corrada Bravo, Florin Chelaru, Llewellyn Smith, Naomi Goldstein, Jayaram Kancherla, Morgan Walter", "Maintainer": "Hector Corrada Bravo ", "VignetteBuilder": "knitr", "Video": "https://www.youtube.com/watch?v=099c4wUxozA", "source.ver": "src/contrib/epivizr_2.4.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/epivizr_2.4.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/epivizr_2.4.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/epivizr_2.4.1.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/epivizr/inst/doc/IntroToEpivizr.R" ], "htmlDocs": [ "vignettes/epivizr/inst/doc/IntroToEpivizr.html" ], "htmlTitles": [ "Introduction to epivizr" ], "dependsOnMe": [ "epivizrStandalone" ] }, "epivizrData": { "Package": "epivizrData", "Version": "1.2.0", "Depends": [ "R (>= 3.3)", "methods", "epivizrServer (>= 1.1.1)", "Biobase" ], "Imports": [ "S4Vectors", "GenomicRanges", "SummarizedExperiment (>= 0.2.0)", "OrganismDbi", "GenomicFeatures", "GenomeInfoDb", "IRanges" ], "Suggests": [ "testthat", "roxygen2", "bumphunter", "hgu133plus2.db", "Mus.musculus", "TxDb.Mmusculus.UCSC.mm10.knownGene", "rjson", "knitr", "rmarkdown", "BiocStyle" ], "License": "MIT + file LICENSE", "MD5sum": "28177ed75cfab06dce7bd4dd388c5124", "NeedsCompilation": "no", "Title": "Data Management API for epiviz interactive visualization app", "Description": "Serve data from Bioconductor Objects through a WebSocket connection.", "biocViews": [ "Infrastructure", "Software", "Visualization" ], "Author": "Hector Corrada Bravo [aut, cre], Florin Chelaru [aut]", "Maintainer": "Hector Corrada Bravo ", "URL": "http://epiviz.github.io", "VignetteBuilder": "knitr", "BugReports": "https://github.com/epiviz/epivizrData/issues", "source.ver": "src/contrib/epivizrData_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/epivizrData_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/epivizrData_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/epivizrData_1.2.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/epivizrData/inst/doc/epivizrData.R" ], "htmlDocs": [ "vignettes/epivizrData/inst/doc/epivizrData.html" ], "htmlTitles": [ "Vignette Title" ], "importsMe": [ "epivizr" ] }, "epivizrServer": { "Package": "epivizrServer", "Version": "1.2.0", "Depends": [ "R (>= 3.2.3)", "methods" ], "Imports": [ "httpuv (>= 1.3.0)", "R6 (>= 2.0.0)", "rjson", "mime (>= 0.2)" ], "Suggests": [ "testthat", "knitr", "rmarkdown", "BiocStyle" ], "License": "MIT + file LICENSE", "MD5sum": "7de5394a791dafcacdb90f1088818aad", "NeedsCompilation": "no", "Title": "WebSocket server infrastructure for epivizr apps and packages", "Description": "This package provides objects to manage WebSocket connections to epiviz apps. Other epivizr package use this infrastructure.", "biocViews": [ "Infrastructure", "Software", "Visualization" ], "Author": "Hector Corrada Bravo [aut, cre]", "Maintainer": "Hector Corrada Bravo ", "URL": "https://epiviz.github.io", "VignetteBuilder": "knitr", "BugReports": "https://github.com/epiviz/epivizrServer", "source.ver": "src/contrib/epivizrServer_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/epivizrServer_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/epivizrServer_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/epivizrServer_1.2.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "htmlDocs": [ "vignettes/epivizrServer/inst/doc/epivizrServer.html" ], "htmlTitles": [ "epivizrServer Usage" ], "dependsOnMe": [ "epivizrData" ], "importsMe": [ "epivizr", "epivizrStandalone" ] }, "epivizrStandalone": { "Package": "epivizrStandalone", "Version": "1.2.0", "Depends": [ "R (>= 3.2.3)", "epivizr (>= 2.3.6)", "methods" ], "Imports": [ "git2r", "epivizrServer", "GenomeInfoDb", "BiocGenerics", "GenomicFeatures", "S4Vectors" ], "Suggests": [ "testthat", "knitr", "rmarkdown", "OrganismDbi (>= 1.13.9)", "Mus.musculus", "Biobase", "BiocStyle" ], "License": "MIT + file LICENSE", "MD5sum": "6e074ee44572522fa87bbd7ba2a6097b", "NeedsCompilation": "no", "Title": "Run Epiviz Interactive Genomic Data Visualization App within R", "Description": "This package imports the epiviz visualization JavaScript app for genomic data interactive visualization. The 'epivizrServer' package is used to provide a web server running completely within R. This standalone version allows to browse arbitrary genomes through genome annotations provided by Bioconductor packages.", "biocViews": [ "GUI", "Infrastructure", "Software", "Visualization" ], "Author": "Hector Corrada Bravo, Jayaram Kancherla", "Maintainer": "Hector Corrada Bravo ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/epivizrStandalone_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/epivizrStandalone_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/epivizrStandalone_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/epivizrStandalone_1.2.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "htmlDocs": [ "vignettes/epivizrStandalone/inst/doc/EpivizrStandalone.html" ], "htmlTitles": [ "Introduction to epivizrStandalone" ] }, "erccdashboard": { "Package": "erccdashboard", "Version": "1.8.0", "Depends": [ "R (>= 3.2)", "ggplot2 (>= 2.1.0)", "gridExtra (>= 2.0.0)" ], "Imports": [ "edgeR", "gplots", "grid", "gtools", "limma", "locfit", "MASS", "plyr", "QuasiSeq", "qvalue", "reshape2", "ROCR", "scales", "stringr" ], "License": "GPL (>=2)", "MD5sum": "daabce5759d62d35fd5a0e4fe3521ed7", "NeedsCompilation": "no", "Title": "Assess Differential Gene Expression Experiments with ERCC Controls", "Description": "Technical performance metrics for differential gene expression experiments using External RNA Controls Consortium (ERCC) spike-in ratio mixtures.", "biocViews": [ "AlternativeSplicing", "BatchEffect", "DifferentialExpression", "DifferentialSplicing", "GeneExpression", "Genetics", "Microarray", "MultipleComparison", "QualityControl", "RNASeq", "Software", "Transcription", "mRNAMicroarray" ], "Author": "Sarah Munro, Steve Lund", "Maintainer": "Sarah Munro ", "URL": "http://www.nist.gov/mml/bbd/erccdashboard.cfm, https://github.com/usnistgov/erccdashboard, http://tinyurl.com/erccsrm", "BugReports": "https://github.com/usnistgov/erccdashboard/issues", "source.ver": "src/contrib/erccdashboard_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/erccdashboard_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/erccdashboard_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/erccdashboard_1.8.0.tgz", "vignettes": [ "vignettes/erccdashboard/inst/doc/erccdashboard.pdf" ], "vignetteTitles": [ "erccdashboard examples" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/erccdashboard/inst/doc/erccdashboard.R" ] }, "erma": { "Package": "erma", "Version": "0.6.0", "Depends": [ "R (>= 3.1)", "methods", "Homo.sapiens" ], "Imports": [ "GenomicFiles (>= 1.5.2)", "rtracklayer", "S4Vectors", "BiocGenerics", "GenomicRanges", "SummarizedExperiment", "ggplot2", "Biobase", "shiny", "foreach", "AnnotationDbi" ], "Suggests": [ "rmarkdown", "BiocStyle", "knitr", "GO.db", "BiocParallel", "png", "DT", "doParallel" ], "License": "Artistic-2.0", "MD5sum": "1d3c5967beb4771d03d2c24ed574d77c", "NeedsCompilation": "no", "Title": "epigenomic road map adventures", "Description": "Software and data to support epigenomic road map adventures.", "Author": "VJ Carey ", "Maintainer": "VJ Carey ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/erma_0.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/erma_0.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/erma_0.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/erma_0.6.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/erma/inst/doc/erma.R" ], "htmlDocs": [ "vignettes/erma/inst/doc/erma.html" ], "htmlTitles": [ "ermaInteractive" ], "suggestsMe": [ "gQTLBase", "yriMulti" ], "biocViews": [ "Software" ] }, "esetVis": { "Package": "esetVis", "Version": "1.0.1", "Imports": [ "mpm", "hexbin", "Rtsne", "MLP", "grid", "Biobase", "MASS", "stats", "utils", "grDevices" ], "Suggests": [ "ggplot2", "ggvis", "rbokeh", "ggrepel", "knitr", "rmarkdown", "ALL", "hgu95av2.db", "AnnotationDbi", "pander", "SummarizedExperiment" ], "License": "GPL-3", "MD5sum": "3f5ba26e9d42db3d3549f6797d1efdce", "NeedsCompilation": "no", "Title": "Visualizations of expressionSet Bioconductor object", "Description": "Utility functions for visualization of expressionSet (or SummarizedExperiment) Bioconductor object, including spectral map, tsne and linear discriminant analysis. Static plot via the ggplot2 package or interactive via the ggvis or rbokeh packages are available.", "biocViews": [ "DataRepresentation", "DimensionReduction", "Pathways", "PrincipalComponent", "Software", "Visualization" ], "Author": "Laure Cougnaud ", "Maintainer": "Laure Cougnaud ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/esetVis_1.0.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/esetVis_1.0.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/esetVis_1.0.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/esetVis_1.0.1.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/esetVis/inst/doc/esetVis-vignette.R" ], "htmlDocs": [ "vignettes/esetVis/inst/doc/esetVis-vignette.html" ], "htmlTitles": [ "esetVis package" ] }, "eudysbiome": { "Package": "eudysbiome", "Version": "1.4.0", "Depends": [ "R (>= 3.1.0)" ], "Imports": [ "plyr", "Rsamtools", "R.utils", "Biostrings" ], "License": "GPL-2", "MD5sum": "f2fcd93acf10b8835c75848cc14b7383", "NeedsCompilation": "no", "Title": "Cartesian plot and contingency test on 16S Microbial data", "Description": "eudysbiome a package that permits to annotate the differential genera as harmful/harmless based on their ability to contribute to host diseases (as indicated in literature) or unknown based on their ambiguous genus classification. Further, the package statistically measures the eubiotic (harmless genera increase or harmful genera decrease) or dysbiotic(harmless genera decrease or harmful genera increase) impact of a given treatment or environmental change on the (gut-intestinal, GI) microbiome in comparison to the microbiome of the reference condition.", "Author": "Xiaoyuan Zhou, Christine Nardini", "Maintainer": "Xiaoyuan Zhou ", "source.ver": "src/contrib/eudysbiome_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/eudysbiome_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/eudysbiome_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/eudysbiome_1.4.0.tgz", "vignettes": [ "vignettes/eudysbiome/inst/doc/eudysbiome.pdf" ], "vignetteTitles": [ "eudysbiome User Manual" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/eudysbiome/inst/doc/eudysbiome.R" ], "biocViews": [ "Software" ] }, "EWCE": { "Package": "EWCE", "Version": "1.2.0", "Depends": [ "R(>= 3.3)" ], "Imports": [ "ggplot2", "reshape2", "biomaRt" ], "Suggests": [ "knitr", "BiocStyle" ], "License": "Artistic-2.0", "MD5sum": "5702e4b3d8621d5f9661acfe861284e5", "NeedsCompilation": "no", "Title": "Expression Weighted Celltype Enrichment", "Description": "Used to determine which cell types are enriched within gene lists. The package provides tools for testing enrichments within simple gene lists (such as human disease associated genes) and those resulting from differential expression studies. The package does not depend upon any particular Single Cell Transcriptome dataset and user defined datasets can be loaded in and used in the analyses.", "biocViews": [ "BiomedicalInformatics", "DifferentialExpression", "FunctionalGenomics", "GeneExpression", "GeneSetEnrichment", "Genetics", "Microarray", "OneChannel", "Proteomics", "RNASeq", "Software", "Transcription", "Visualization", "mRNAMicroarray" ], "Author": "Dr Nathan Skene", "Maintainer": "Nathan Skene ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/EWCE_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/EWCE_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/EWCE_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/EWCE_1.2.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/EWCE/inst/doc/EWCE.R" ], "htmlDocs": [ "vignettes/EWCE/inst/doc/EWCE.html" ], "htmlTitles": [ "Expression Weighted Celltype Enrichment with EWCE" ] }, "ExiMiR": { "Package": "ExiMiR", "Version": "2.16.0", "Depends": [ "R (>= 2.10)", "Biobase (>= 2.5.5)", "affy (>= 1.26.1)", "limma" ], "Imports": [ "affyio(>= 1.13.3)", "Biobase(>= 2.5.5)", "preprocessCore(>= 1.10.0)" ], "Suggests": [ "mirna10cdf" ], "License": "GPL-2", "MD5sum": "d73f52efcc95a43f0924dffa2d88313c", "NeedsCompilation": "no", "Title": "R functions for the normalization of Exiqon miRNA array data", "Description": "This package contains functions for reading raw data in ImaGene TXT format obtained from Exiqon miRCURY LNA arrays, annotating them with appropriate GAL files, and normalizing them using a spike-in probe-based method. Other platforms and data formats are also supported.", "biocViews": [ "GeneExpression", "Microarray", "OneChannel", "Preprocessing", "Software", "Transcription", "TwoChannel" ], "Author": "Sylvain Gubian , Alain Sewer , PMP SA", "Maintainer": "Sylvain Gubian ", "source.ver": "src/contrib/ExiMiR_2.16.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ExiMiR_2.16.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ExiMiR_2.16.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ExiMiR_2.16.0.tgz", "vignettes": [ "vignettes/ExiMiR/inst/doc/ExiMiR-vignette.pdf" ], "vignetteTitles": [ "Description of ExiMiR" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/ExiMiR/inst/doc/ExiMiR-vignette.R" ] }, "exomeCopy": { "Package": "exomeCopy", "Version": "1.20.0", "Depends": [ "IRanges (>= 2.5.27)", "GenomicRanges (>= 1.23.16)", "Rsamtools" ], "Imports": [ "stats4", "methods", "GenomeInfoDb" ], "Suggests": [ "Biostrings" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "cc3c723a6966a33db0aabac02af35312", "NeedsCompilation": "yes", "Title": "Copy number variant detection from exome sequencing read depth", "Description": "Detection of copy number variants (CNV) from exome sequencing samples, including unpaired samples. The package implements a hidden Markov model which uses positional covariates, such as background read depth and GC-content, to simultaneously normalize and segment the samples into regions of constant copy count.", "biocViews": [ "CopyNumberVariation", "Genetics", "Sequencing", "Software" ], "Author": "Michael Love", "Maintainer": "Michael Love ", "source.ver": "src/contrib/exomeCopy_1.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/exomeCopy_1.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/exomeCopy_1.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/exomeCopy_1.20.0.tgz", "vignettes": [ "vignettes/exomeCopy/inst/doc/exomeCopy.pdf" ], "vignetteTitles": [ "Copy number variant detection in exome sequencing data" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/exomeCopy/inst/doc/exomeCopy.R" ], "importsMe": [ "cn.mops", "CNVPanelizer", "contiBAIT", "Rariant", "SomaticCancerAlterations" ] }, "exomePeak": { "Package": "exomePeak", "Version": "2.8.0", "Depends": [ "Rsamtools", "GenomicFeatures (>= 1.14.5)", "rtracklayer", "GenomicAlignments" ], "License": "GPL-2", "MD5sum": "3e9971570ce4deaf96a0d368ecff51eb", "NeedsCompilation": "no", "Title": "exome-based anlaysis of MeRIP-Seq data: peak calling and differential analysis", "Description": "The package is developed for the analysis of affinity-based epitranscriptome shortgun sequencing data from MeRIP-seq (maA-seq). It was built on the basis of the exomePeak MATLAB package (Meng, Jia, et al. \"Exome-based analysis for RNA epigenome sequencing data.\" Bioinformatics 29.12 (2013): 1565-1567.) with new functions for differential analysis of two experimental conditions to unveil the dynamics in post-transcriptional regulation of the RNA methylome. The exomePeak R-package accepts and statistically supports multiple biological replicates, internally removes PCR artifacts and multi-mapping reads, outputs exome-based binding sites (RNA methylation sites) and detects differential post-transcriptional RNA modification sites between two experimental conditions in term of percentage rather the absolute amount. The package is still under active development, and we welcome all biology and computation scientist for all kinds of collaborations and communications. Please feel free to contact Dr. Jia Meng if you have any questions.", "biocViews": [ "HighThroughputSequencing", "Methylseq", "RNAseq", "Sequencing", "Software" ], "Author": "Lin Zhang , Lian Liu , Jia Meng ", "Maintainer": "Lin Zhang , Lian Liu , Jia Meng ", "source.ver": "src/contrib/exomePeak_2.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/exomePeak_2.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/exomePeak_2.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/exomePeak_2.8.0.tgz", "vignettes": [ "vignettes/exomePeak/inst/doc/exomePeak-Overview.pdf" ], "vignetteTitles": [ "An introduction to exomePeak" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/exomePeak/inst/doc/exomePeak-Overview.R" ] }, "ExperimentHub": { "Package": "ExperimentHub", "Version": "1.0.0", "Depends": [ "methods", "BiocGenerics (>= 0.15.10)", "AnnotationHub (>= 2.5.9)" ], "Imports": [ "utils", "S4Vectors", "BiocInstaller" ], "Suggests": [ "knitr", "BiocStyle" ], "Enhances": [ "ExperimentHubData" ], "License": "Artistic-2.0", "MD5sum": "b1a59f56f9cb0156ca7516ac2ddb751d", "NeedsCompilation": "no", "Title": "Client to access ExperimentHub resources", "Description": "This package provides a client for the Bioconductor ExperimentHub web resource. ExperimentHub provides a central location where curated data from experiments, publications or training courses can be accessed. Each resource has associated metadata, tags and date of modification. The client creates and manages a local cache of files retrieved enabling quick and reproducible access.", "biocViews": [ "DataImport", "GUI", "Infrastructure", "Software", "ThirdPartyClient" ], "Author": "Bioconductor Package Maintainer ", "Maintainer": "Bioconductor Package Maintainer ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/ExperimentHub_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ExperimentHub_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ExperimentHub_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ExperimentHub_1.0.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "importsMe": [ "ExperimentHubData" ], "suggestsMe": [ "CellMapper", "GSE62944" ], "dependsOnMe": [ "alpineData", "CellMapperData", "curatedMetagenomicData", "HumanAffyData" ] }, "ExperimentHubData": { "Package": "ExperimentHubData", "Version": "1.0.0", "Depends": [ "utils", "BiocGenerics (>= 0.15.10)", "S4Vectors", "AnnotationHubData (>= 1.1.4)" ], "Imports": [ "methods", "ExperimentHub", "BiocInstaller", "DBI", "BiocCheck", "httr", "curl" ], "Suggests": [ "GenomeInfoDb", "RUnit", "knitr", "BiocStyle" ], "License": "Artistic-2.0", "MD5sum": "31330cd6b319d9051fdb8608cdc475da", "NeedsCompilation": "no", "Title": "Add resources to ExperimentHub", "Description": "Functions to add metadata to ExperimentHub db and resource files to AWS S3 buckets.", "biocViews": [ "DataImport", "GUI", "Infrastructure", "Software", "ThirdPartyClient" ], "Author": "Bioconductor Maintainer [cre]", "Maintainer": "Bioconductor Package Maintainer ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/ExperimentHubData_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ExperimentHubData_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ExperimentHubData_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ExperimentHubData_1.0.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ExperimentHubData/inst/doc/ExperimentHubData.R" ], "htmlDocs": [ "vignettes/ExperimentHubData/inst/doc/ExperimentHubData.html" ], "htmlTitles": [ "Introduction to ExperimentHubData" ], "dependsOnMe": [ "alpineData" ] }, "explorase": { "Package": "explorase", "Version": "1.38.0", "Depends": [ "R (>= 2.6.2)" ], "Imports": [ "limma", "rggobi", "RGtk2" ], "Suggests": [ "cairoDevice" ], "License": "GPL-2", "MD5sum": "3d97bc0825a3f97b1da20c2e6a20b7ca", "NeedsCompilation": "no", "Title": "GUI for exploratory data analysis of systems biology data", "Description": "explore and analyze *omics data with R and GGobi", "biocViews": [ "GUI", "Microarray", "Software", "Visualization" ], "Author": "Michael Lawrence, Eun-kyung Lee, Dianne Cook, Jihong Kim, Hogeun An, and Dongshin Kim", "Maintainer": "Michael Lawrence ", "URL": "http://www.metnetdb.org/MetNet_exploRase.htm", "source.ver": "src/contrib/explorase_1.38.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/explorase_1.38.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/explorase_1.38.0.zip", "vignettes": [ "vignettes/explorase/inst/doc/explorase.pdf" ], "vignetteTitles": [ "Introduction to exploRase" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false }, "ExpressionAtlas": { "Package": "ExpressionAtlas", "Version": "1.2.0", "Depends": [ "R (>= 3.2.0)", "methods", "Biobase", "SummarizedExperiment", "limma", "S4Vectors", "xml2" ], "Imports": [ "utils", "XML", "httr" ], "Suggests": [ "knitr", "testthat", "rmarkdown" ], "License": "GPL (>= 3)", "MD5sum": "cc1be402c2ab2735350f55ee79d5e6b4", "NeedsCompilation": "no", "Title": "Download datasets from EMBL-EBI Expression Atlas", "Description": "This package is for searching for datasets in EMBL-EBI Expression Atlas, and downloading them into R for further analysis. Each Expression Atlas dataset is represented as a SimpleList object with one element per platform. Sequencing data is contained in a SummarizedExperiment object, while microarray data is contained in an ExpressionSet or MAList object.", "biocViews": [ "ArrayExpress", "ExperimentData", "ExpressionData", "MicroarrayData", "SequencingData", "Software" ], "Author": "Maria Keays", "Maintainer": "Maria Keays ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/ExpressionAtlas_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ExpressionAtlas_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ExpressionAtlas_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ExpressionAtlas_1.2.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ExpressionAtlas/inst/doc/ExpressionAtlas.R" ], "htmlDocs": [ "vignettes/ExpressionAtlas/inst/doc/ExpressionAtlas.html" ], "htmlTitles": [ "ExpressionAtlas" ] }, "ExpressionView": { "Package": "ExpressionView", "Version": "1.26.0", "Depends": [ "caTools", "bitops", "methods", "isa2", "eisa", "GO.db", "KEGG.db", "AnnotationDbi" ], "Imports": [ "methods", "isa2", "eisa", "GO.db", "KEGG.db", "AnnotationDbi" ], "Suggests": [ "ALL", "hgu95av2.db", "biclust", "affy" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "fc36131ee3ed7b1c4bd8f3275f559d1b", "NeedsCompilation": "yes", "Title": "Visualize biclusters identified in gene expression data", "Description": "ExpressionView visualizes possibly overlapping biclusters in a gene expression matrix. It can use the result of the ISA method (eisa package) or the algorithms in the biclust package or others. The viewer itself was developed using Adobe Flex and runs in a flash-enabled web browser.", "biocViews": [ "Classification", "GO", "GeneExpression", "KEGG", "Microarray", "Software", "Visualization" ], "Author": "Andreas Luscher ", "Maintainer": "Gabor Csardi ", "source.ver": "src/contrib/ExpressionView_1.26.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ExpressionView_1.26.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ExpressionView_1.26.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ExpressionView_1.26.0.tgz", "vignettes": [ "vignettes/ExpressionView/inst/doc/ExpressionView.format.pdf", "vignettes/ExpressionView/inst/doc/ExpressionView.ordering.pdf", "vignettes/ExpressionView/inst/doc/ExpressionView.tutorial.pdf" ], "vignetteTitles": [ "ExpressionView file format", "How the ordering algorithm works", "ExpressionView" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ExpressionView/inst/doc/ExpressionView.ordering.R", "vignettes/ExpressionView/inst/doc/ExpressionView.tutorial.R" ] }, "fabia": { "Package": "fabia", "Version": "2.20.0", "Depends": [ "R (>= 2.8.0)", "Biobase" ], "Imports": [ "methods", "graphics", "grDevices", "stats", "utils" ], "License": "LGPL (>= 2.1)", "Archs": "i386, x64", "MD5sum": "9f75b316a6e38d4639b884b001d2185e", "NeedsCompilation": "yes", "Title": "FABIA: Factor Analysis for Bicluster Acquisition", "Description": "Biclustering by \"Factor Analysis for Bicluster Acquisition\" (FABIA). FABIA is a model-based technique for biclustering, that is clustering rows and columns simultaneously. Biclusters are found by factor analysis where both the factors and the loading matrix are sparse. FABIA is a multiplicative model that extracts linear dependencies between samples and feature patterns. It captures realistic non-Gaussian data distributions with heavy tails as observed in gene expression measurements. FABIA utilizes well understood model selection techniques like the EM algorithm and variational approaches and is embedded into a Bayesian framework. FABIA ranks biclusters according to their information content and separates spurious biclusters from true biclusters. The code is written in C.", "biocViews": [ "Clustering", "DifferentialExpression", "Microarray", "MultipleComparison", "Software", "StatisticalMethod", "Visualization" ], "Author": "Sepp Hochreiter ", "Maintainer": "Sepp Hochreiter ", "URL": "http://www.bioinf.jku.at/software/fabia/fabia.html", "source.ver": "src/contrib/fabia_2.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/fabia_2.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/fabia_2.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/fabia_2.20.0.tgz", "vignettes": [ "vignettes/fabia/inst/doc/fabia.pdf" ], "vignetteTitles": [ "FABIA: Manual for the R package" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/fabia/inst/doc/fabia.R" ], "dependsOnMe": [ "hapFabia" ], "suggestsMe": [ "fabiaData" ] }, "facopy": { "Package": "facopy", "Version": "1.8.0", "Depends": [ "R (>= 3.0)", "methods", "cgdsr (>= 1.1.30)", "coin (>= 1.0)", "ggplot2", "gridExtra", "facopy.annot", "grid" ], "Imports": [ "annotate", "data.table", "DOSE", "FactoMineR", "GO.db", "GOstats", "graphite", "igraph", "S4Vectors", "IRanges", "MASS", "nnet", "reshape2", "Rgraphviz", "scales" ], "License": "CC BY-NC 4.0", "MD5sum": "a86a495e4adfceeb783d8eadd55be2f5", "NeedsCompilation": "no", "Title": "Feature-based association and gene-set enrichment for copy number alteration analysis in cancer", "Description": "facopy is an R package for fine-tuned cancer CNA association modeling. Association is measured directly at the genomic features of interest and, in the case of genes, downstream gene-set enrichment analysis can be performed thanks to novel internal processing of the data. The software opens a way to systematically scrutinize the differences in CNA distribution across tumoral phenotypes, such as those that relate to tumor type, location and progression. Currently, the output format from 11 different methods that analyze data from whole-genome/exome sequencing and SNP microarrays, is supported. Multiple genomes, alteration types and variable types are also supported.", "biocViews": [ "CopyNumberVariation", "GeneSetEnrichment", "Genetics", "GenomicVariation", "Microarray", "Sequencing", "Software", "Visualization" ], "Author": "David Mosen-Ansorena", "Maintainer": "David Mosen-Ansorena ", "source.ver": "src/contrib/facopy_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/facopy_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/facopy_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/facopy_1.8.0.tgz", "vignettes": [ "vignettes/facopy/inst/doc/facopy.pdf" ], "vignetteTitles": [ "facopy" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/facopy/inst/doc/facopy.R" ] }, "factDesign": { "Package": "factDesign", "Version": "1.50.0", "Depends": [ "Biobase (>= 2.5.5)" ], "Imports": [ "stats" ], "Suggests": [ "affy", "genefilter", "multtest" ], "License": "LGPL", "MD5sum": "0214c3677d83a601b85498f1853a6f5a", "NeedsCompilation": "no", "Title": "Factorial designed microarray experiment analysis", "Description": "This package provides a set of tools for analyzing data from a factorial designed microarray experiment, or any microarray experiment for which a linear model is appropriate. The functions can be used to evaluate tests of contrast of biological interest and perform single outlier detection.", "biocViews": [ "DifferentialExpression", "Microarray", "Software" ], "Author": "Denise Scholtens", "Maintainer": "Denise Scholtens ", "source.ver": "src/contrib/factDesign_1.50.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/factDesign_1.50.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/factDesign_1.50.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/factDesign_1.50.0.tgz", "vignettes": [ "vignettes/factDesign/inst/doc/factDesign.pdf" ], "vignetteTitles": [ "factDesign" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/factDesign/inst/doc/factDesign.R" ] }, "FamAgg": { "Package": "FamAgg", "Version": "1.2.1", "Depends": [ "methods", "kinship2", "igraph" ], "Imports": [ "gap", "BiocGenerics", "Matrix", "utils", "survey" ], "Suggests": [ "BiocStyle", "knitr", "RUnit", "rmarkdown" ], "License": "MIT + file LICENSE", "MD5sum": "ea1ee5251e169264893ff9d7413f99fb", "NeedsCompilation": "no", "Title": "Pedigree Analysis and Familial Aggregation", "Description": "Framework providing basic pedigree analysis and plotting utilities as well as a variety of methods to evaluate familial aggregation of traits in large pedigrees.", "biocViews": [ "Genetics", "Software" ], "Author": "J. Rainer, D. Taliun, C.X. Weichenberger", "Maintainer": "Johannes Rainer ", "URL": "https://github.com/jotsetung/FamAgg", "VignetteBuilder": "knitr", "BugReports": "https://github.com/jotsetung/FamAgg/issues", "source.ver": "src/contrib/FamAgg_1.2.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/FamAgg_1.2.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/FamAgg_1.2.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/FamAgg_1.2.1.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/FamAgg/inst/doc/FamAgg.R" ], "htmlDocs": [ "vignettes/FamAgg/inst/doc/FamAgg.html" ], "htmlTitles": [ "Pedigree Analysis and Familial Aggregation" ] }, "farms": { "Package": "farms", "Version": "1.26.0", "Depends": [ "R (>= 2.8)", "affy (>= 1.20.0)", "MASS", "methods" ], "Imports": [ "affy", "MASS", "Biobase (>= 1.13.41)", "methods", "graphics" ], "Suggests": [ "affydata", "Biobase", "utils" ], "License": "LGPL (>= 2.1)", "MD5sum": "7b01082a566e30bc63042a115f446cc5", "NeedsCompilation": "no", "Title": "FARMS - Factor Analysis for Robust Microarray Summarization", "Description": "The package provides the summarization algorithm called Factor Analysis for Robust Microarray Summarization (FARMS) and a novel unsupervised feature selection criterion called \"I/NI-calls\"", "biocViews": [ "GeneExpression", "Microarray", "Preprocessing", "QualityControl", "Software" ], "Author": "Djork-Arne Clevert ", "Maintainer": "Djork-Arne Clevert ", "URL": "http://www.bioinf.jku.at/software/farms/farms.html", "source.ver": "src/contrib/farms_1.26.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/farms_1.26.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/farms_1.26.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/farms_1.26.0.tgz", "vignettes": [ "vignettes/farms/inst/doc/farms.pdf" ], "vignetteTitles": [ "Using farms" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/farms/inst/doc/farms.R" ] }, "fastLiquidAssociation": { "Package": "fastLiquidAssociation", "Version": "1.10.0", "Depends": [ "methods", "LiquidAssociation", "parallel", "stats", "Hmisc" ], "Imports": [ "WGCNA" ], "Suggests": [ "GOstats", "yeastCC", "org.Sc.sgd.db" ], "License": "GPL-2", "MD5sum": "53bac77200ac684c2d1f688a59e7a8ed", "NeedsCompilation": "no", "Title": "functions for genome-wide application of Liquid Association", "Description": "This package extends the function of the LiquidAssociation package for genome-wide application. It integrates a screening method into the LA analysis to reduce the number of triplets to be examined for a high LA value and provides code for use in subsequent significance analyses.", "biocViews": [ "CellBiology", "GeneExpression", "Genetics", "Pathways", "Software" ], "Author": "Tina Gunderson", "Maintainer": "Tina Gunderson ", "source.ver": "src/contrib/fastLiquidAssociation_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/fastLiquidAssociation_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/fastLiquidAssociation_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/fastLiquidAssociation_1.10.0.tgz", "vignettes": [ "vignettes/fastLiquidAssociation/inst/doc/fastLiquidAssociation.pdf" ], "vignetteTitles": [ "fastLiquidAssociation Vignette" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/fastLiquidAssociation/inst/doc/fastLiquidAssociation.R" ] }, "fastseg": { "Package": "fastseg", "Version": "1.20.0", "Depends": [ "R (>= 2.13)", "GenomicRanges", "Biobase" ], "Imports": [ "methods", "graphics", "stats", "BiocGenerics", "S4Vectors", "IRanges" ], "Suggests": [ "DNAcopy", "oligo" ], "License": "LGPL (>= 2.0)", "Archs": "i386, x64", "MD5sum": "1840f449546b1d89983e95a6280006c1", "NeedsCompilation": "yes", "Title": "fastseg - a fast segmentation algorithm", "Description": "fastseg implements a very fast and efficient segmentation algorithm. It has similar functionality as DNACopy (Olshen and Venkatraman 2004), but is considerably faster and more flexible. fastseg can segment data from DNA microarrays and data from next generation sequencing for example to detect copy number segments. Further it can segment data from RNA microarrays like tiling arrays to identify transcripts. Most generally, it can segment data given as a matrix or as a vector. Various data formats can be used as input to fastseg like expression set objects for microarrays or GRanges for sequencing data. The segmentation criterion of fastseg is based on a statistical test in a Bayesian framework, namely the cyber t-test (Baldi 2001). The speed-up arises from the facts, that sampling is not necessary in for fastseg and that a dynamic programming approach is used for calculation of the segments' first and higher order moments.", "biocViews": [ "Classification", "CopyNumberVariation", "Software" ], "Author": "Guenter Klambauer", "Maintainer": "Guenter Klambauer ", "URL": "http://www.bioinf.jku.at/software/fastseg/fastseg.html", "source.ver": "src/contrib/fastseg_1.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/fastseg_1.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/fastseg_1.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/fastseg_1.20.0.tgz", "vignettes": [ "vignettes/fastseg/inst/doc/fastseg.pdf" ], "vignetteTitles": [ "fastseg: Manual for the R package" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/fastseg/inst/doc/fastseg.R" ], "importsMe": [ "methylKit" ] }, "fCCAC": { "Package": "fCCAC", "Version": "1.0.0", "Depends": [ "R (>= 3.3.0)", "S4Vectors", "IRanges", "GenomicRanges", "grid" ], "Imports": [ "fda", "RColorBrewer", "genomation", "ggplot2", "ComplexHeatmap", "grDevices", "stats", "utils" ], "Suggests": [ "RUnit", "BiocGenerics", "BiocStyle" ], "License": "Artistic-2.0", "MD5sum": "0b12dd3da4695f8fe789cb6a98ff916c", "NeedsCompilation": "no", "Title": "functional Canonical Correlation Analysis to evaluate Covariance between nucleic acid sequencing datasets", "Description": "An application of functional canonical correlation analysis to assess covariance of nucleic acid sequencing datasets such as chromatin immunoprecipitation followed by deep sequencing (ChIP-seq).", "biocViews": [ "Coverage", "Genetics", "Sequencing", "Software", "Transcription" ], "Author": "Pedro Madrigal ", "Maintainer": "Pedro Madrigal ", "source.ver": "src/contrib/fCCAC_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/fCCAC_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/fCCAC_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/fCCAC_1.0.0.tgz", "vignettes": [ "vignettes/fCCAC/inst/doc/fCCAC.pdf" ], "vignetteTitles": [ "fCCAC Vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/fCCAC/inst/doc/fCCAC.R" ] }, "fCI": { "Package": "fCI", "Version": "1.4.0", "Depends": [ "R (>= 3.1)", "FNN", "psych", "gtools", "zoo", "rgl", "grid", "VennDiagram" ], "Suggests": [ "knitr", "rmarkdown", "BiocStyle" ], "License": "GPL (>= 2)", "MD5sum": "0ce525981c4c70fe28af6e03260c98cb", "NeedsCompilation": "no", "Title": "f-divergence Cutoff Index for Differential Expression Analysis in Transcriptomics and Proteomics", "Description": "(f-divergence Cutoff Index), is to find DEGs in the transcriptomic & proteomic data, and identify DEGs by computing the difference between the distribution of fold-changes for the control-control and remaining (non-differential) case-control gene expression ratio data. fCI provides several advantages compared to existing methods.", "biocViews": [ "Proteomics", "Software" ], "Author": "Shaojun Tang", "Maintainer": "Shaojun Tang ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/fCI_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/fCI_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/fCI_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/fCI_1.4.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/fCI/inst/doc/fCI.R" ], "htmlDocs": [ "vignettes/fCI/inst/doc/fCI.html" ], "htmlTitles": [ "fCI" ] }, "fdrame": { "Package": "fdrame", "Version": "1.46.0", "Imports": [ "tcltk", "graphics", "grDevices", "stats", "utils" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "305abb43c81017ba726d6672167bc766", "NeedsCompilation": "yes", "Title": "FDR adjustments of Microarray Experiments (FDR-AME)", "Description": "This package contains two main functions. The first is fdr.ma which takes normalized expression data array, experimental design and computes adjusted p-values It returns the fdr adjusted p-values and plots, according to the methods described in (Reiner, Yekutieli and Benjamini 2002). The second, is fdr.gui() which creates a simple graphic user interface to access fdr.ma", "biocViews": [ "DifferentialExpression", "Microarray", "MultipleComparison", "Software" ], "Author": "Yoav Benjamini, Effi Kenigsberg, Anat Reiner, Daniel Yekutieli", "Maintainer": "Effi Kenigsberg ", "source.ver": "src/contrib/fdrame_1.46.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/fdrame_1.46.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/fdrame_1.46.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/fdrame_1.46.0.tgz", "vignettes": [ "vignettes/fdrame/inst/doc/fdrame.pdf" ], "vignetteTitles": [ "Annotation Overview" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false }, "FEM": { "Package": "FEM", "Version": "3.2.0", "Depends": [ "AnnotationDbi", "Matrix", "marray", "corrplot", "igraph", "impute", "limma", "org.Hs.eg.db", "graph", "BiocGenerics" ], "Imports": [ "graph" ], "License": "GPL (>=2)", "MD5sum": "ebd681f5e1e6243814f1445ba398c9a3", "NeedsCompilation": "no", "Title": "Identification of Functional Epigenetic Modules", "Description": "The FEM package performs a systems-level integrative analysis of DNA methylation and gene expression data. It seeks modules of functionally related genes which exhibit differential promoter DNA methylation and differential expression, where an inverse association between promoter DNA methylation and gene expression is assumed. For full details, see Jiao et al Bioinformatics 2014.", "biocViews": [ "DifferentialExpression", "DifferentialMethylation", "NetworkEnrichment", "Software", "SystemsBiology" ], "Author": "Andrew E. Teschendorff and Zhen Yang", "Maintainer": "Zhen Yang ", "source.ver": "src/contrib/FEM_3.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/FEM_3.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/FEM_3.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/FEM_3.2.0.tgz", "vignettes": [ "vignettes/FEM/inst/doc/IntroDoFEM.pdf" ], "vignetteTitles": [ "The FEM package performs a systems-level integrative analysis of DNA methylationa and gene expression. It seeks modules of functionally related genes which exhibit differential promoter DNA methylation and differential expression, where an inverse association between promoter DNA methylation and gene expression is assumed. For full details, see Jiao et al Bioinformatics 2014." ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/FEM/inst/doc/IntroDoFEM.R" ], "dependsOnMe": [ "ChAMP" ] }, "ffpe": { "Package": "ffpe", "Version": "1.18.0", "Depends": [ "R (>= 2.10.0)", "TTR", "methods" ], "Imports": [ "Biobase", "BiocGenerics", "affy", "lumi", "methylumi", "sfsmisc" ], "Suggests": [ "genefilter", "ffpeExampleData" ], "License": "GPL (>2)", "MD5sum": "e508953bf1aaec46be32f5ba3ce00f32", "NeedsCompilation": "no", "Title": "Quality assessment and control for FFPE microarray expression data", "Description": "Identify low-quality data using metrics developed for expression data derived from Formalin-Fixed, Paraffin-Embedded (FFPE) data. Also a function for making Concordance at the Top plots (CAT-plots).", "biocViews": [ "GeneExpression", "Microarray", "QualityControl", "Software" ], "Author": "Levi Waldron", "Maintainer": "Levi Waldron ", "source.ver": "src/contrib/ffpe_1.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ffpe_1.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ffpe_1.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ffpe_1.18.0.tgz", "vignettes": [ "vignettes/ffpe/inst/doc/ffpe.pdf" ], "vignetteTitles": [ "ffpe package user guide" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ffpe/inst/doc/ffpe.R" ] }, "FGNet": { "Package": "FGNet", "Version": "3.8.0", "Depends": [ "R (>= 2.15)" ], "Imports": [ "igraph (>= 0.6)", "hwriter", "R.utils", "XML", "plotrix", "reshape2", "RColorBrewer", "png" ], "Suggests": [ "RGtk2", "RCurl", "RDAVIDWebService", "gage", "topGO", "KEGGprofile", "GO.db", "KEGG.db", "reactome.db", "RUnit", "BiocGenerics", "org.Sc.sgd.db", "knitr", "rmarkdown", "AnnotationDbi" ], "License": "GPL (>= 2)", "MD5sum": "eeb6efac0d95333b2fa171570c19279e", "NeedsCompilation": "no", "Title": "Functional Gene Networks derived from biological enrichment analyses", "Description": "Build and visualize functional gene and term networks from clustering of enrichment analyses in multiple annotation spaces. The package includes a graphical user interface (GUI) and functions to perform the functional enrichment analysis through DAVID, GeneTerm Linker, gage (GSEA) and topGO.", "biocViews": [ "Annotation", "Clustering", "FunctionalGenomics", "GO", "GeneSetEnrichment", "Network", "NetworkEnrichment", "Pathways", "Software", "Visualization" ], "Author": "Sara Aibar, Celia Fontanillo, Conrad Droste and Javier De Las Rivas.", "Maintainer": "Sara Aibar ", "URL": "http://www.cicancer.org", "VignetteBuilder": "knitr", "source.ver": "src/contrib/FGNet_3.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/FGNet_3.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/FGNet_3.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/FGNet_3.8.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/FGNet/inst/doc/FGNet.R" ], "htmlDocs": [ "vignettes/FGNet/inst/doc/FGNet.html" ], "htmlTitles": [ "FGNet" ] }, "fgsea": { "Package": "fgsea", "Version": "1.0.2", "Depends": [ "R (>= 3.3)", "Rcpp" ], "Imports": [ "data.table", "BiocParallel", "stats", "ggplot2 (>= 2.2.0)", "gridExtra", "grid", "fastmatch" ], "LinkingTo": [ "Rcpp" ], "Suggests": [ "testthat", "knitr", "rmarkdown", "reactome.db", "AnnotationDbi", "parallel" ], "License": "MIT + file LICENCE", "Archs": "i386, x64", "MD5sum": "7cf097058e524d43558cb17ea0a11ff1", "NeedsCompilation": "yes", "Title": "Fast Gene Set Enrichment Analysis", "Description": "The package implements an algorithm for fast gene set enrichment analysis. Using the fast algorithm allows to make more permutations and get more fine grained p-values, which allows to use accurate stantard approaches to multiple hypothesis correction.", "biocViews": [ "DifferentialExpression", "GeneExpression", "GeneSetEnrichment", "Pathways", "Software" ], "Author": "Alexey Sergushichev [aut, cre]", "Maintainer": "Alexey Sergushichev ", "URL": "https://github.com/ctlab/fgsea/", "SystemRequirements": "C++11", "VignetteBuilder": "knitr", "BugReports": "https://github.com/ctlab/fgsea/issues", "source.ver": "src/contrib/fgsea_1.0.2.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/fgsea_1.0.2.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/fgsea_1.0.2.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/fgsea_1.0.2.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/fgsea/inst/doc/fgsea-tutorial.R" ], "htmlDocs": [ "vignettes/fgsea/inst/doc/fgsea-tutorial.html" ], "htmlTitles": [ "Using fgsea package" ], "importsMe": [ "DOSE", "piano" ], "suggestsMe": [ "Pi" ] }, "FindMyFriends": { "Package": "FindMyFriends", "Version": "1.4.0", "Imports": [ "methods", "BiocGenerics", "Biobase", "tools", "dplyr", "IRanges", "Biostrings", "S4Vectors", "kebabs", "igraph", "Matrix", "digest", "filehash", "Rcpp", "ggplot2", "gtable", "grid", "reshape2", "ggdendro", "BiocParallel", "utils", "stats" ], "LinkingTo": [ "Rcpp" ], "Suggests": [ "BiocStyle", "testthat", "knitr", "rmarkdown", "reutils" ], "License": "GPL (>=2)", "Archs": "i386, x64", "MD5sum": "b8d665f06288ab3d194516ca5927cda7", "NeedsCompilation": "yes", "Title": "Microbial Comparative Genomics in R", "Description": "A framework for doing microbial comparative genomics in R. The main purpose of the package is assisting in the creation of pangenome matrices where genes from related organisms are grouped by similarity, as well as the analysis of these data. FindMyFriends provides many novel approaches to doing pangenome analysis and supports a gene grouping algorithm that scales linearly, thus making the creation of huge pangenomes feasible.", "biocViews": [ "Clustering", "ComparativeGenomics", "DataRepresentation", "GenomicVariation", "GraphAndNetwork", "SequenceMatching", "Software" ], "Author": "Thomas Lin Pedersen", "Maintainer": "Thomas Lin Pedersen ", "URL": "https://github.com/thomasp85/FindMyFriends", "VignetteBuilder": "knitr", "BugReports": "https://github.com/thomasp85/FindMyFriends/issues", "source.ver": "src/contrib/FindMyFriends_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/FindMyFriends_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/FindMyFriends_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/FindMyFriends_1.4.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/FindMyFriends/inst/doc/FindMyFriends_intro.R" ], "htmlDocs": [ "vignettes/FindMyFriends/inst/doc/FindMyFriends_intro.html" ], "htmlTitles": [ "Creating pangenomes using FindMyFriends" ], "importsMe": [ "PanVizGenerator" ] }, "FISHalyseR": { "Package": "FISHalyseR", "Version": "1.8.0", "Depends": [ "EBImage", "abind" ], "Suggests": [ "knitr" ], "License": "Artistic-2.0", "MD5sum": "f11d5e038bdb2e51b224d11e827ba244", "NeedsCompilation": "no", "Title": "FISHalyseR a package for automated FISH quantification", "Description": "FISHalyseR provides functionality to process and analyse digital cell culture images, in particular to quantify FISH probes within nuclei. Furthermore, it extract the spatial location of each nucleus as well as each probe enabling spatial co-localisation analysis.", "biocViews": [ "CellBiology", "Software" ], "Author": "Karesh Arunakirinathan , Andreas Heindl ", "Maintainer": "Karesh Arunakirinathan , Andreas Heindl ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/FISHalyseR_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/FISHalyseR_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/FISHalyseR_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/FISHalyseR_1.8.0.tgz", "vignettes": [ "vignettes/FISHalyseR/inst/doc/FISHalyseR.pdf" ], "vignetteTitles": [ "FISHAlyseR Automated fluorescence in situ hybridisation quantification in R" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/FISHalyseR/inst/doc/FISHalyseR.R" ] }, "FitHiC": { "Package": "FitHiC", "Version": "1.0.0", "Imports": [ "data.table", "fdrtool", "grDevices", "graphics", "Rcpp", "stats", "utils" ], "LinkingTo": [ "Rcpp" ], "Suggests": [ "knitr", "rmarkdown" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "78e48b7349cb444b86114cc74fbf2605", "NeedsCompilation": "yes", "Title": "Confidence estimation for intra-chromosomal contact maps", "Description": "Fit-Hi-C is a tool for assigning statistical confidence estimates to intra-chromosomal contact maps produced by genome-wide genome architecture assays such as Hi-C.", "biocViews": [ "DNA3DStructure", "Software" ], "Author": "Ferhat Ay [aut] (Python original, https://noble.gs.washington.edu/proj/fit-hi-c/), Timothy L. Bailey [aut], William S. Noble [aut], Ruyu Tan [aut, cre, trl] (R port)", "Maintainer": "Ruyu Tan ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/FitHiC_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/FitHiC_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/FitHiC_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/FitHiC_1.0.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/FitHiC/inst/doc/fithic.R" ], "htmlDocs": [ "vignettes/FitHiC/inst/doc/fithic.html" ], "htmlTitles": [ "Vignette Title" ] }, "flagme": { "Package": "flagme", "Version": "1.30.0", "Depends": [ "gcspikelite", "xcms", "CAMERA" ], "Imports": [ "gplots", "graphics", "MASS", "methods", "SparseM", "stats", "utils" ], "License": "LGPL (>= 2)", "Archs": "i386, x64", "MD5sum": "bd6ce5caa90ffe121e43c18924269ba7", "NeedsCompilation": "yes", "Title": "Analysis of Metabolomics GC/MS Data", "Description": "Fragment-level analysis of gas chromatography - mass spectrometry metabolomics data", "biocViews": [ "DifferentialExpression", "MassSpectrometry", "Software" ], "Author": "Mark Robinson , Riccardo Romoli ", "Maintainer": "Mark Robinson , Riccardo Romoli ", "source.ver": "src/contrib/flagme_1.30.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/flagme_1.30.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/flagme_1.30.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/flagme_1.30.0.tgz", "vignettes": [ "vignettes/flagme/inst/doc/flagme.pdf" ], "vignetteTitles": [ "Using flagme -- Fragment-level analysis of GC-MS-based metabolomics data" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/flagme/inst/doc/flagme.R" ] }, "flipflop": { "Package": "flipflop", "Version": "1.12.0", "Depends": [ "R (>= 2.10.0)" ], "Imports": [ "methods", "Matrix", "IRanges", "GenomicRanges", "parallel" ], "Suggests": [ "GenomicFeatures" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "b16a4c45e7ae0224f48853ed7a4a1a53", "NeedsCompilation": "yes", "Title": "Fast lasso-based isoform prediction as a flow problem", "Description": "Flipflop discovers which isoforms of a gene are expressed in a given sample together with their abundances, based on RNA-Seq read data. It takes an alignment file in SAM format as input. It can also discover transcripts from several samples simultaneously, increasing statistical power.", "biocViews": [ "AlternativeSplicing", "RNASeq", "RNASeqData", "Regression", "Software" ], "Author": "Elsa Bernard, Laurent Jacob, Julien Mairal and Jean-Philippe Vert", "Maintainer": "Elsa Bernard ", "URL": "http://cbio.ensmp.fr/flipflop", "SystemRequirements": "GNU make", "source.ver": "src/contrib/flipflop_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/flipflop_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/flipflop_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/flipflop_1.12.0.tgz", "vignettes": [ "vignettes/flipflop/inst/doc/flipflop.pdf" ], "vignetteTitles": [ "FlipFlop: Fast Lasso-based Isoform Prediction as a Flow Problem" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/flipflop/inst/doc/flipflop.R" ] }, "flowAI": { "Package": "flowAI", "Version": "1.2.10", "Depends": [ "R (>= 3.2)" ], "Imports": [ "ggplot2", "flowCore", "plyr", "changepoint", "knitr", "reshape2", "RColorBrewer", "scales" ], "Suggests": [ "testthat", "shiny", "rmarkdown" ], "License": "GPL", "MD5sum": "c67305383cecfff3b8735dd481ef3ec9", "NeedsCompilation": "no", "Title": "Automatic and interactive quality control for flow cytometry data", "Description": "The package is able to perform an automatic or interactive quality control on FCS data acquired using flow cytometry instruments. By evaluating three different properties: 1) flow rate, 2) signal acquisition, 3) dynamic range, the quality control enables the detection and removal of anomalies.", "biocViews": [ "BiomedicalInformatics", "FlowCytometry", "QualityControl", "Software" ], "Author": "Gianni Monaco, Hao Chen", "Maintainer": "Gianni Monaco ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/flowAI_1.2.10.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/flowAI_1.2.10.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/flowAI_1.2.10.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/flowAI_1.2.10.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/flowAI/inst/doc/flowAI.R" ], "htmlDocs": [ "vignettes/flowAI/inst/doc/flowAI.html" ], "htmlTitles": [ "Automatic and GUI methods to do quality control on Flow cytometry Data" ] }, "flowBeads": { "Package": "flowBeads", "Version": "1.12.0", "Depends": [ "R (>= 2.15.0)", "methods", "Biobase", "rrcov", "flowCore" ], "Imports": [ "flowCore", "rrcov", "knitr", "xtable" ], "Suggests": [ "flowViz" ], "License": "Artistic-2.0", "MD5sum": "607ab174f6e7104db20cf9163876554e", "NeedsCompilation": "no", "Title": "flowBeads: Analysis of flow bead data", "Description": "This package extends flowCore to provide functionality specific to bead data. One of the goals of this package is to automate analysis of bead data for the purpose of normalisation.", "biocViews": [ "CellBasedAssays", "FlowCytometry", "Infrastructure", "Software" ], "Author": "Nikolas Pontikos", "Maintainer": "Nikolas Pontikos ", "source.ver": "src/contrib/flowBeads_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/flowBeads_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/flowBeads_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/flowBeads_1.12.0.tgz", "vignettes": [ "vignettes/flowBeads/inst/doc/HowTo-flowBeads.pdf" ], "vignetteTitles": [ "Analysis of Flow Cytometry Bead Data" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/flowBeads/inst/doc/HowTo-flowBeads.R" ] }, "flowBin": { "Package": "flowBin", "Version": "1.10.0", "Depends": [ "methods", "flowCore", "flowFP", "R (>= 2.10)" ], "Imports": [ "class", "limma", "snow", "BiocGenerics" ], "Suggests": [ "parallel" ], "License": "Artistic-2.0", "MD5sum": "20fb9a4abd154ba8c2c2625724d6043c", "NeedsCompilation": "no", "Title": "Combining multitube flow cytometry data by binning", "Description": "Software to combine flow cytometry data that has been multiplexed into multiple tubes with common markers between them, by establishing common bins across tubes in terms of the common markers, then determining expression within each tube for each bin in terms of the tube-specific markers.", "biocViews": [ "CellBasedAssays", "FlowCytometry", "Software" ], "Author": "Kieran O'Neill", "Maintainer": "Kieran O'Neill ", "source.ver": "src/contrib/flowBin_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/flowBin_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/flowBin_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/flowBin_1.10.0.tgz", "vignettes": [ "vignettes/flowBin/inst/doc/flowBin.pdf" ], "vignetteTitles": [ "flowBin" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/flowBin/inst/doc/flowBin.R" ] }, "flowcatchR": { "Package": "flowcatchR", "Version": "1.8.0", "Depends": [ "R (>= 2.10)", "methods", "EBImage" ], "Imports": [ "rgl", "colorRamps", "abind", "BiocParallel" ], "Suggests": [ "BiocStyle", "knitr", "shiny" ], "License": "BSD_3_clause + file LICENSE", "MD5sum": "98e792b93a10a90d97284774320614a1", "NeedsCompilation": "no", "Title": "Tools to analyze in vivo microscopy imaging data focused on tracking flowing blood cells", "Description": "flowcatchR is a set of tools to analyze in vivo microscopy imaging data, focused on tracking flowing blood cells. It guides the steps from segmentation to calculation of features, filtering out particles not of interest, providing also a set of utilities to help checking the quality of the performed operations (e.g. how good the segmentation was). It allows investigating the issue of tracking flowing cells such as in blood vessels, to categorize the particles in flowing, rolling and adherent. This classification is applied in the study of phenomena such as hemostasis and study of thrombosis development. Moreover, flowcatchR presents an integrated workflow solution, based on the integration with a Shiny App and Jupyter notebooks, which is delivered alongside the package, and can enable fully reproducible bioimage analysis in the R environment.", "biocViews": [ "CellBiology", "Classification", "GUI", "Infrastructure", "Software", "Visualization" ], "Author": "Federico Marini [aut, cre]", "Maintainer": "Federico Marini ", "URL": "https://github.com/federicomarini/flowcatchR", "SystemRequirements": "ImageMagick", "VignetteBuilder": "knitr", "BugReports": "https://github.com/federicomarini/flowcatchR/issues", "source.ver": "src/contrib/flowcatchR_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/flowcatchR_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/flowcatchR_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/flowcatchR_1.8.0.tgz", "vignettes": [ "vignettes/flowcatchR/inst/doc/flowcatchR-vignette.pdf" ], "vignetteTitles": [ "flowcatchR: tracking and analyzing cells in time lapse microscopy images" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/flowcatchR/inst/doc/flowcatchR-vignette.R" ] }, "flowCHIC": { "Package": "flowCHIC", "Version": "1.8.0", "Depends": [ "R (>= 3.1.0)" ], "Imports": [ "methods", "flowCore", "EBImage", "vegan", "hexbin", "ggplot2", "grid" ], "License": "GPL-2", "MD5sum": "8f10364ad27d4c3e6417775eddfc8b0c", "NeedsCompilation": "no", "Title": "Analyze flow cytometric data using histogram information", "Description": "A package to analyze flow cytometric data of complex microbial communities based on histogram images", "biocViews": [ "CellBasedAssays", "Clustering", "FlowCytometry", "Software", "Visualization" ], "Author": "Joachim Schumann , Christin Koch , Ingo Fetzer , Susann Müller ", "Maintainer": "Author: Joachim Schumann ", "URL": "http://www.ufz.de/index.php?en=16773", "source.ver": "src/contrib/flowCHIC_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/flowCHIC_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/flowCHIC_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/flowCHIC_1.8.0.tgz", "vignettes": [ "vignettes/flowCHIC/inst/doc/flowCHICmanual.pdf" ], "vignetteTitles": [ "Analyze flow cytometric data using histogram information" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/flowCHIC/inst/doc/flowCHICmanual.R" ] }, "flowCL": { "Package": "flowCL", "Version": "1.12.0", "Depends": [ "R (>= 3.3)", "Rgraphviz", "SPARQL" ], "Imports": [ "methods", "grDevices", "utils", "graph" ], "Suggests": [ "RUnit", "BiocGenerics" ], "License": "Artistic-2.0", "MD5sum": "69d1d0781cd2736953dea840ad2e6283", "NeedsCompilation": "no", "Title": "Semantic labelling of flow cytometric cell populations", "Description": "Semantic labelling of flow cytometric cell populations.", "biocViews": [ "FlowCytometry", "Software" ], "Author": "Justin Meskas, Radina Droumeva", "Maintainer": "Justin Meskas ", "source.ver": "src/contrib/flowCL_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/flowCL_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/flowCL_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/flowCL_1.12.0.tgz", "vignettes": [ "vignettes/flowCL/inst/doc/flowCL.pdf" ], "vignetteTitles": [ "flowCL package" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/flowCL/inst/doc/flowCL.R" ] }, "flowClean": { "Package": "flowClean", "Version": "1.12.0", "Depends": [ "R (>= 2.15.0)", "flowCore" ], "Imports": [ "bit", "changepoint", "sfsmisc" ], "Suggests": [ "flowViz", "grid", "gridExtra" ], "License": "Artistic-2.0", "MD5sum": "0f267495060d2cd82700e2c3dbc5bb15", "NeedsCompilation": "no", "Title": "flowClean", "Description": "A quality control tool for flow cytometry data based on compositional data analysis.", "biocViews": [ "FlowCytometry", "QualityControl", "Software" ], "Author": "Kipper Fletez-Brant", "Maintainer": "Kipper Fletez-Brant ", "source.ver": "src/contrib/flowClean_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/flowClean_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/flowClean_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/flowClean_1.12.0.tgz", "vignettes": [ "vignettes/flowClean/inst/doc/flowClean.pdf" ], "vignetteTitles": [ "flowClean" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/flowClean/inst/doc/flowClean.R" ] }, "flowClust": { "Package": "flowClust", "Version": "3.12.2", "Depends": [ "R(>= 2.5.0)" ], "Imports": [ "BiocGenerics", "MCMCpack", "methods", "Biobase", "graph", "RBGL", "ellipse", "flowViz", "flowCore", "clue", "mnormt" ], "Suggests": [ "testthat", "flowWorkspace", "flowWorkspaceData" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "e037fad976c28c846cd7515b9f22faba", "NeedsCompilation": "yes", "Title": "Clustering for Flow Cytometry", "Description": "Robust model-based clustering using a t-mixture model with Box-Cox transformation. Note: users should have GSL installed. Windows users: 'consult the README file available in the inst directory of the source distribution for necessary configuration instructions'.", "biocViews": [ "Clustering", "FlowCytometry", "Software", "Visualization" ], "Author": "Raphael Gottardo , Kenneth Lo , Greg Finak ", "Maintainer": "Greg Finak , Mike Jiang ", "SystemRequirements": "GNU make", "source.ver": "src/contrib/flowClust_3.12.2.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/flowClust_3.12.2.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/flowClust_3.12.2.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/flowClust_3.12.2.tgz", "vignettes": [ "vignettes/flowClust/inst/doc/flowClust.pdf" ], "vignetteTitles": [ "flowClust package" ], "hasREADME": true, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/flowClust/inst/doc/flowClust.R" ], "importsMe": [ "CONFESS", "flowTrans", "flowType", "openCyto" ], "suggestsMe": [ "BiocGenerics" ], "dependsOnMe": [ "flowMerge", "flowTrans" ] }, "flowCore": { "Package": "flowCore", "Version": "1.40.6", "Depends": [ "R (>= 2.10.0)" ], "Imports": [ "Biobase", "BiocGenerics (>= 0.1.14)", "graph", "graphics", "methods", "rrcov", "stats", "utils", "stats4", "corpcor", "Rcpp", "matrixStats" ], "LinkingTo": [ "Rcpp", "BH(>= 1.62.0-1)" ], "Suggests": [ "Rgraphviz", "flowViz", "flowStats", "testthat", "flowWorkspace", "flowWorkspaceData", "openCyto", "knitr", "ggcyto", "gridExtra" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "142b8bcf038f87af68921d2a6a8f5d1c", "NeedsCompilation": "yes", "Title": "flowCore: Basic structures for flow cytometry data", "Description": "Provides S4 data structures and basic functions to deal with flow cytometry data.", "biocViews": [ "CellBasedAssays", "FlowCytometry", "Infrastructure", "Software" ], "Author": "B. Ellis, P. Haaland, F. Hahne, N. Le Meur, N. Gopalakrishnan, J. Spidlen, M. Jiang", "Maintainer": "M.Jiang ", "SystemRequirements": "GNU make, C++11", "VignetteBuilder": "knitr", "source.ver": "src/contrib/flowCore_1.40.6.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/flowCore_1.40.6.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/flowCore_1.40.6.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/flowCore_1.40.6.tgz", "vignettes": [ "vignettes/flowCore/inst/doc/HowTo-flowCore.pdf" ], "vignetteTitles": [ "Basic Functions for Flow Cytometry Data" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/flowCore/inst/doc/HowTo-flowCore.R" ], "dependsOnMe": [ "flowBeads", "flowBin", "flowClean", "flowFitExampleData", "flowFP", "flowMatch", "flowStats", "flowTrans", "flowViz", "flowVS", "flowWorkspace", "ggcyto", "healthyFlowData", "immunoClust", "ncdfFlow", "plateCore", "QUALIFIER" ], "importsMe": [ "CONFESS", "cytofkit", "CytoML", "flowAI", "flowBeads", "flowCHIC", "flowClust", "flowDensity", "flowFit", "flowMeans", "flowMerge", "flowPloidy", "flowQ", "flowQB", "FlowSOM", "flowStats", "flowTrans", "flowType", "flowUtils", "flowViz", "ncdfFlow", "openCyto", "plateCore", "QUALIFIER" ], "suggestsMe": [ "COMPASS", "flowPloidyData", "FlowRepositoryR", "RchyOptimyx" ] }, "flowCyBar": { "Package": "flowCyBar", "Version": "1.10.0", "Depends": [ "R (>= 3.0.0)" ], "Imports": [ "gplots", "vegan", "methods" ], "License": "GPL-2", "MD5sum": "285eab7db4e97e5aeb061fb28dd6c6e0", "NeedsCompilation": "no", "Title": "Analyze flow cytometric data using gate information", "Description": "A package to analyze flow cytometric data using gate information to follow population/community dynamics", "biocViews": [ "CellBasedAssays", "Clustering", "FlowCytometry", "Software", "Visualization" ], "Author": "Joachim Schumann , Christin Koch , Susanne Günther , Ingo Fetzer , Susann Müller ", "Maintainer": "Joachim Schumann ", "URL": "http://www.ufz.de/index.php?de=16773", "source.ver": "src/contrib/flowCyBar_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/flowCyBar_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/flowCyBar_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/flowCyBar_1.10.0.tgz", "vignettes": [ "vignettes/flowCyBar/inst/doc/flowCyBar-manual.pdf" ], "vignetteTitles": [ "Analyze flow cytometric data using gate information" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/flowCyBar/inst/doc/flowCyBar-manual.R" ] }, "flowDensity": { "Package": "flowDensity", "Version": "1.8.0", "Depends": [ "R (>= 2.10.0)", "methods" ], "Imports": [ "flowCore", "graphics", "car", "gplots", "RFOC", "GEOmap", "methods", "grDevices" ], "License": "Artistic-2.0", "MD5sum": "8f583b7d26d941c1f23d3e7115c9cc8e", "NeedsCompilation": "no", "Title": "Sequential Flow Cytometry Data Gating", "Description": "This package provides tools for automated sequential gating analogous to the manual gating strategy based on the density of the data.", "biocViews": [ "Bioinformatics", "Cancer", "CellBiology", "Clustering", "DensityGating", "FlowCytData", "FlowCytometry", "Software", "StemCells" ], "Author": "M. Jafar Taghiyar, Mehrnoush Malek", "Maintainer": "Mehrnoush Malek ", "source.ver": "src/contrib/flowDensity_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/flowDensity_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/flowDensity_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/flowDensity_1.8.0.tgz", "vignettes": [ "vignettes/flowDensity/inst/doc/flowDensityVignette.pdf" ], "vignetteTitles": [ "Automated alternative to the current manual gating practice" ], "hasREADME": true, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/flowDensity/inst/doc/flowDensityVignette.R" ] }, "flowFit": { "Package": "flowFit", "Version": "1.12.0", "Depends": [ "R (>= 2.12.2)" ], "Imports": [ "flowCore", "flowViz", "graphics", "kza", "methods", "minpack.lm", "gplots" ], "Suggests": [ "flowFitExampleData" ], "License": "Artistic-2.0", "MD5sum": "83d510c6c7d8bd30c4670b31feb76fca", "NeedsCompilation": "no", "Title": "Estimate proliferation in cell-tracking dye studies", "Description": "This package estimate the proliferation of a cell population in cell-tracking dye studies. The package uses an R implementation of the Levenberg-Marquardt algorithm (minpack.lm) to fit a set of peaks (corresponding to different generations of cells) over the proliferation-tracking dye distribution in a FACS experiment.", "biocViews": [ "CellBasedAssays", "FlowCytometry", "Software" ], "Author": "Davide Rambaldi", "Maintainer": "Davide Rambaldi ", "BugReports": "Davide Rambaldi ", "source.ver": "src/contrib/flowFit_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/flowFit_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/flowFit_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/flowFit_1.12.0.tgz", "vignettes": [ "vignettes/flowFit/inst/doc/HowTo-flowFit.pdf" ], "vignetteTitles": [ "Fitting Functions for Flow Cytometry Data" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/flowFit/inst/doc/HowTo-flowFit.R" ] }, "flowFP": { "Package": "flowFP", "Version": "1.32.0", "Depends": [ "R (>= 2.10)", "flowCore", "flowViz" ], "Imports": [ "Biobase", "BiocGenerics (>= 0.1.6)", "graphics", "grDevices", "methods", "stats", "stats4" ], "Suggests": [ "RUnit" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "d8e46632b4b5340c9d4ed6ac601cdcab", "NeedsCompilation": "yes", "Title": "Fingerprinting for Flow Cytometry", "Description": "Fingerprint generation of flow cytometry data, used to facilitate the application of machine learning and datamining tools for flow cytometry.", "biocViews": [ "CellBasedAssays", "Clustering", "FlowCytometry", "Software", "Visualization" ], "Author": "Herb Holyst , Wade Rogers ", "Maintainer": "Herb Holyst ", "source.ver": "src/contrib/flowFP_1.32.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/flowFP_1.32.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/flowFP_1.32.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/flowFP_1.32.0.tgz", "vignettes": [ "vignettes/flowFP/inst/doc/flowFP_HowTo.pdf" ], "vignetteTitles": [ "Fingerprinting for Flow Cytometry" ], "hasREADME": true, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/flowFP/inst/doc/flowFP_HowTo.R" ], "dependsOnMe": [ "flowBin" ] }, "flowMap": { "Package": "flowMap", "Version": "1.12.0", "Depends": [ "R (>= 3.0.1)", "ade4(>= 1.5-2)", "doParallel(>= 1.0.3)", "abind(>= 1.4.0)", "reshape2(>= 1.2.2)", "scales(>= 0.2.3)", "Matrix(>= 1.1-4)", "methods (>= 2.14)" ], "Suggests": [ "BiocStyle", "knitr" ], "License": "GPL (>=2)", "MD5sum": "7af14450faf6f98d232298679e4d27f9", "NeedsCompilation": "no", "Title": "Mapping cell populations in flow cytometry data for cross-sample comparisons using the Friedman-Rafsky Test", "Description": "flowMap quantifies the similarity of cell populations across multiple flow cytometry samples using a nonparametric multivariate statistical test. The method is able to map cell populations of different size, shape, and proportion across multiple flow cytometry samples. The algorithm can be incorporate in any flow cytometry work flow that requires accurat quantification of similarity between cell populations.", "biocViews": [ "FlowCytometry", "MultipleComparison", "Software" ], "Author": "Chiaowen Joyce Hsiao, Yu Qian, and Richard H. Scheuermann", "Maintainer": "Chiaowen Joyce Hsiao ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/flowMap_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/flowMap_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/flowMap_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/flowMap_1.12.0.tgz", "vignettes": [ "vignettes/flowMap/inst/doc/flowMap.pdf" ], "vignetteTitles": [ "Mapping cell populations in flow cytometry data flowMap-FR" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/flowMap/inst/doc/flowMap.R" ] }, "flowMatch": { "Package": "flowMatch", "Version": "1.10.0", "Depends": [ "R (>= 3.0.0)", "Rcpp (>= 0.11.0)", "methods", "flowCore" ], "Imports": [ "Biobase" ], "LinkingTo": [ "Rcpp" ], "Suggests": [ "healthyFlowData" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "f1403f10a87fd56eacfd3f017fc2b6f5", "NeedsCompilation": "yes", "Title": "Matching and meta-clustering in flow cytometry", "Description": "Matching cell populations and building meta-clusters and templates from a collection of FC samples.", "biocViews": [ "Clustering", "FlowCytometry", "Software" ], "Author": "Ariful Azad", "Maintainer": "Ariful Azad ", "source.ver": "src/contrib/flowMatch_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/flowMatch_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/flowMatch_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/flowMatch_1.10.0.tgz", "vignettes": [ "vignettes/flowMatch/inst/doc/flowMatch.pdf" ], "vignetteTitles": [ "flowMatch: Cell population matching and meta-clustering in Flow Cytometry" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/flowMatch/inst/doc/flowMatch.R" ] }, "flowMeans": { "Package": "flowMeans", "Version": "1.34.0", "Depends": [ "R (>= 2.10.0)" ], "Imports": [ "Biobase", "graphics", "grDevices", "methods", "rrcov", "stats", "feature", "flowCore" ], "License": "Artistic-2.0", "MD5sum": "9bf65c78e53f6264bc3ddd9f1857f4c7", "NeedsCompilation": "no", "Title": "Non-parametric Flow Cytometry Data Gating", "Description": "Identifies cell populations in Flow Cytometry data using non-parametric clustering and segmented-regression-based change point detection. Note: R 2.11.0 or newer is required.", "biocViews": [ "CellBiology", "Clustering", "FlowCytometry", "Software" ], "Author": "Nima Aghaeepour", "Maintainer": "Nima Aghaeepour ", "source.ver": "src/contrib/flowMeans_1.34.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/flowMeans_1.34.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/flowMeans_1.34.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/flowMeans_1.34.0.tgz", "vignettes": [ "vignettes/flowMeans/inst/doc/flowMeans.pdf" ], "vignetteTitles": [ "flowMeans: Non-parametric Flow Cytometry Data Gating" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/flowMeans/inst/doc/flowMeans.R" ], "importsMe": [ "CONFESS", "flowType" ] }, "flowMerge": { "Package": "flowMerge", "Version": "2.22.0", "Depends": [ "graph", "feature", "flowClust", "Rgraphviz", "foreach", "snow" ], "Imports": [ "rrcov", "flowCore", "graphics", "methods", "stats", "utils" ], "Enhances": [ "doMC", "multicore" ], "License": "Artistic-2.0", "MD5sum": "098c8f84436a2ededbf2ad93420e7bdc", "NeedsCompilation": "no", "Title": "Cluster Merging for Flow Cytometry Data", "Description": "Merging of mixture components for model-based automated gating of flow cytometry data using the flowClust framework. Note: users should have a working copy of flowClust 2.0 installed.", "biocViews": [ "Clustering", "FlowCytometry", "Software" ], "Author": "Greg Finak , Raphael Gottardo ", "Maintainer": "Greg Finak ", "source.ver": "src/contrib/flowMerge_2.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/flowMerge_2.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/flowMerge_2.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/flowMerge_2.22.0.tgz", "vignettes": [ "vignettes/flowMerge/inst/doc/flowMerge.pdf" ], "vignetteTitles": [ "flowMerge package" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/flowMerge/inst/doc/flowMerge.R" ], "importsMe": [ "CONFESS", "flowType" ] }, "flowPeaks": { "Package": "flowPeaks", "Version": "1.18.0", "Depends": [ "R (>= 2.12.0)" ], "Enhances": [ "flowCore" ], "License": "Artistic-1.0", "Archs": "i386, x64", "MD5sum": "43ece343eb31544dcabda42d80c0a849", "NeedsCompilation": "yes", "Title": "An R package for flow data clustering", "Description": "A fast and automatic clustering to classify the cells into subpopulations based on finding the peaks from the overall density function generated by K-means.", "biocViews": [ "Clustering", "FlowCytometry", "Gating", "Software" ], "Author": "Yongchao Ge", "Maintainer": "Yongchao Ge", "SystemRequirements": "gsl", "source.ver": "src/contrib/flowPeaks_1.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/flowPeaks_1.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/flowPeaks_1.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/flowPeaks_1.18.0.tgz", "vignettes": [ "vignettes/flowPeaks/inst/doc/flowPeaks-guide.pdf" ], "vignetteTitles": [ "Tutorial of flowPeaks package" ], "hasREADME": true, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/flowPeaks/inst/doc/flowPeaks-guide.R" ], "importsMe": [ "CONFESS" ] }, "flowPloidy": { "Package": "flowPloidy", "Version": "1.0.0", "Depends": [ "R (>= 3.3)" ], "Imports": [ "flowCore", "car", "caTools", "knitr", "rmarkdown", "minpack.lm", "shiny", "methods", "graphics", "stats", "utils" ], "Suggests": [ "flowPloidyData" ], "License": "GPL-3", "MD5sum": "e7918ab27eeb3ced0bbbfcce2d87875b", "NeedsCompilation": "no", "Title": "Analyze flow cytometer data to determine sample ploidy", "Description": "Determine sample ploidy via flow cytometry histogram analysis. Reads Flow Cytometry Standard (FCS) files via the flowCore bioconductor package, and provides functions for determining the DNA ploidy of samples based on internal standards.", "biocViews": [ "FlowCytometry", "GUI", "Regression", "Software", "Visualization" ], "Author": "Tyler Smith ", "Maintainer": "Tyler Smith ", "URL": "https://github.com/plantarum/flowPloidy", "VignetteBuilder": "knitr", "BugReports": "https://github.com/plantarum/flowPloidy/issues", "source.ver": "src/contrib/flowPloidy_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/flowPloidy_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/flowPloidy_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/flowPloidy_1.0.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/flowPloidy/inst/doc/flowPloidy-overview.R" ], "htmlDocs": [ "vignettes/flowPloidy/inst/doc/flowPloidy-overview.html" ], "htmlTitles": [ "flowPloidy: Overview" ] }, "flowPlots": { "Package": "flowPlots", "Version": "1.22.0", "Depends": [ "R (>= 2.13.0)", "methods" ], "Suggests": [ "vcd" ], "License": "Artistic-2.0", "MD5sum": "3914e96cbb043838f50dd769dc1a87dd", "NeedsCompilation": "no", "Title": "flowPlots: analysis plots and data class for gated flow cytometry data", "Description": "Graphical displays with embedded statistical tests for gated ICS flow cytometry data, and a data class which stores \"stacked\" data and has methods for computing summary measures on stacked data, such as marginal and polyfunctional degree data.", "biocViews": [ "CellBasedAssays", "DataRepresentation", "FlowCytometry", "Software", "Visualization" ], "Author": "N. Hawkins, S. Self", "Maintainer": "N. Hawkins ", "source.ver": "src/contrib/flowPlots_1.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/flowPlots_1.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/flowPlots_1.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/flowPlots_1.22.0.tgz", "vignettes": [ "vignettes/flowPlots/inst/doc/flowPlots.pdf" ], "vignetteTitles": [ "Plots with Embedded Tests for Gated Flow Cytometry Data" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/flowPlots/inst/doc/flowPlots.R" ] }, "flowQ": { "Package": "flowQ", "Version": "1.34.0", "Depends": [ "R (>= 2.10.0)", "methods", "BiocGenerics", "outliers", "lattice", "flowViz", "mvoutlier", "bioDist", "parody", "RColorBrewer", "latticeExtra" ], "Imports": [ "methods", "BiocGenerics", "geneplotter", "flowCore", "flowViz", "IRanges" ], "Suggests": [ "flowStats" ], "License": "Artistic-2.0", "MD5sum": "88669985820b5eaba8a9b4d94a3422c0", "NeedsCompilation": "no", "Title": "Quality control for flow cytometry", "Description": "Provides quality control and quality assessment tools for flow cytometry data.", "biocViews": [ "CellBasedAssays", "FlowCytometry", "Infrastructure", "Software" ], "Author": "R. Gentleman, F. Hahne, J. Kettman, N. Le Meur, N. Gopalakrishnan", "Maintainer": "Mike Jiang ", "SystemRequirements": "ImageMagick", "source.ver": "src/contrib/flowQ_1.34.0.tar.gz", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/flowQ_1.34.0.tgz", "vignettes": [ "vignettes/flowQ/inst/doc/DataQualityAssessment.pdf", "vignettes/flowQ/inst/doc/Extending-flowQ.pdf" ], "vignetteTitles": [ "Data Quality Assesment for Ungated Flow Cytometry Data", "Basic Functions for Flow Cytometry Data" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/flowQ/inst/doc/DataQualityAssessment.R", "vignettes/flowQ/inst/doc/Extending-flowQ.R" ] }, "flowQB": { "Package": "flowQB", "Version": "2.2.0", "Imports": [ "methods", "flowCore (>= 1.32.0)", "stats", "extremevalues" ], "Suggests": [ "flowQBData", "FlowRepositoryR", "xlsx", "RUnit", "BiocGenerics" ], "License": "Artistic-2.0", "MD5sum": "8abcfec155937a720bc6fd5cef91fc1b", "NeedsCompilation": "no", "Title": "Automated Quadratic Characterization of Flow Cytometer Instrument Sensitivity: Q, B and CV instrinsic calculations", "Description": "flowQB is a fully automated R Bioconductor package to calculate automatically the detector efficiency (Q), optical background (B) and intrinsic CV of the beads.", "biocViews": [ "FlowCytometry", "MultiChannel", "OneChannel", "PeakDetection", "QualityControl", "Regression", "Software" ], "Author": "Josef Spidlen, Faysal El Khettabi, Wayne Moore, David Parks, Ryan Brinkman", "Maintainer": "Josef Spidlen ", "source.ver": "src/contrib/flowQB_2.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/flowQB_2.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/flowQB_2.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/flowQB_2.2.0.tgz", "vignettes": [ "vignettes/flowQB/inst/doc/flowQBVignettes.pdf" ], "vignetteTitles": [ "flowQB package" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/flowQB/inst/doc/flowQBVignettes.R" ], "suggestsMe": [ "flowQBData" ] }, "FlowRepositoryR": { "Package": "FlowRepositoryR", "Version": "1.6.0", "Depends": [ "R (>= 3.2)" ], "Imports": [ "XML", "RCurl", "tools", "utils", "jsonlite" ], "Suggests": [ "RUnit", "BiocGenerics", "flowCore", "methods" ], "License": "Artistic-2.0", "MD5sum": "6569a1e55a47a17638e49293303f29e8", "NeedsCompilation": "no", "Title": "FlowRepository R Interface", "Description": "This package provides an interface to search and download data and annotations from FlowRepository (flowrepository.org). It uses the FlowRepository programming interface to communicate with a FlowRepository server.", "biocViews": [ "FlowCytometry", "Infrastructure", "Software" ], "Author": "Josef Spidlen [aut, cre]", "Maintainer": "Josef Spidlen ", "source.ver": "src/contrib/FlowRepositoryR_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/FlowRepositoryR_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/FlowRepositoryR_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/FlowRepositoryR_1.6.0.tgz", "vignettes": [ "vignettes/FlowRepositoryR/inst/doc/HowTo-FlowRepositoryR.pdf" ], "vignetteTitles": [ "FlowRepository R Interface" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/FlowRepositoryR/inst/doc/HowTo-FlowRepositoryR.R" ], "suggestsMe": [ "flowQB" ] }, "FlowSOM": { "Package": "FlowSOM", "Version": "1.6.0", "Depends": [ "R (>= 3.2)", "igraph" ], "Imports": [ "flowCore", "ConsensusClusterPlus", "BiocGenerics", "tsne", "flowUtils", "XML" ], "Suggests": [ "BiocStyle" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "663ae3bdf4b442cc6bd31e343c5c4d73", "NeedsCompilation": "yes", "Title": "Using self-organizing maps for visualization and interpretation of cytometry data", "Description": "FlowSOM offers visualization options for cytometry data, by using Self-Organizing Map clustering and Minimal Spanning Trees.", "biocViews": [ "CellBasedAssays", "CellBiology", "Clustering", "FlowCytometry", "Software", "Visualization" ], "Author": "Sofie Van Gassen, Britt Callebaut and Yvan Saeys", "Maintainer": "Sofie Van Gassen ", "URL": "http://www.r-project.org, http://dambi.ugent.be", "source.ver": "src/contrib/FlowSOM_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/FlowSOM_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/FlowSOM_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/FlowSOM_1.6.0.tgz", "vignettes": [ "vignettes/FlowSOM/inst/doc/FlowSOM.pdf" ], "vignetteTitles": [ "Using SOMs for visualization of cytometry data" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/FlowSOM/inst/doc/FlowSOM.R" ], "importsMe": [ "cytofkit" ] }, "flowStats": { "Package": "flowStats", "Version": "3.32.0", "Depends": [ "R (>= 2.10)", "flowCore", "fda (>= 2.2.6)", "cluster", "flowWorkspace", "ncdfFlow(>= 2.19.5)" ], "Imports": [ "BiocGenerics", "MASS", "flowViz", "flowCore", "fda (>= 2.2.6)", "Biobase", "methods", "grDevices", "graphics", "stats", "utils", "KernSmooth", "lattice", "ks" ], "Suggests": [ "xtable" ], "Enhances": [ "RBGL", "ncdfFlow", "graph" ], "License": "Artistic-2.0", "MD5sum": "20c2ace027d69fbf773dc4e486301c01", "NeedsCompilation": "no", "Title": "Statistical methods for the analysis of flow cytometry data", "Description": "Methods and functionality to analyse flow data that is beyond the basic infrastructure provided by the flowCore package.", "biocViews": [ "CellBasedAssays", "FlowCytometry", "Software" ], "Author": "Florian Hahne, Nishant Gopalakrishnan, Alireza Hadj Khodabakhshi, Chao-Jen Wong, Kyongryun Lee", "Maintainer": "Greg Finak and Mike Jiang ", "source.ver": "src/contrib/flowStats_3.32.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/flowStats_3.32.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/flowStats_3.32.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/flowStats_3.32.0.tgz", "vignettes": [ "vignettes/flowStats/inst/doc/GettingStartedWithFlowStats.pdf" ], "vignetteTitles": [ "flowStats Overview" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/flowStats/inst/doc/GettingStartedWithFlowStats.R" ], "dependsOnMe": [ "flowVS" ], "importsMe": [ "openCyto", "plateCore" ], "suggestsMe": [ "flowCore", "flowQ", "flowViz", "ggcyto" ] }, "flowTrans": { "Package": "flowTrans", "Version": "1.26.0", "Depends": [ "R (>= 2.11.0)", "flowCore", "flowViz", "flowClust" ], "Imports": [ "flowCore", "methods", "flowViz", "stats", "flowClust" ], "License": "Artistic-2.0", "MD5sum": "23365c76903716916f37e2d44d19d0c0", "NeedsCompilation": "no", "Title": "Parameter Optimization for Flow Cytometry Data Transformation", "Description": "Profile maximum likelihood estimation of parameters for flow cytometry data transformations.", "biocViews": [ "FlowCytometry", "Software" ], "Author": "Greg Finak , Juan Manuel-Perez , Raphael Gottardo ", "Maintainer": "Greg Finak ", "source.ver": "src/contrib/flowTrans_1.26.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/flowTrans_1.26.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/flowTrans_1.26.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/flowTrans_1.26.0.tgz", "vignettes": [ "vignettes/flowTrans/inst/doc/flowTrans.pdf" ], "vignetteTitles": [ "flowTrans package" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/flowTrans/inst/doc/flowTrans.R" ] }, "flowType": { "Package": "flowType", "Version": "2.12.0", "Depends": [ "R (>= 2.10)", "Rcpp (>= 0.10.4)", "BH (>= 1.51.0-3)" ], "Imports": [ "Biobase", "graphics", "grDevices", "methods", "flowCore", "flowMeans", "sfsmisc", "rrcov", "flowClust", "flowMerge", "stats" ], "LinkingTo": [ "Rcpp", "BH" ], "Suggests": [ "xtable" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "98635b1620c744db66fc1f34995546a7", "NeedsCompilation": "yes", "Title": "Phenotyping Flow Cytometry Assays", "Description": "Phenotyping Flow Cytometry Assays using multidimentional expansion of single dimentional partitions.", "biocViews": [ "FlowCytometry", "Software" ], "Author": "Nima Aghaeepour, Kieran O'Neill, Adrin Jalali", "Maintainer": "Nima Aghaeepour ", "source.ver": "src/contrib/flowType_2.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/flowType_2.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/flowType_2.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/flowType_2.12.0.tgz", "vignettes": [ "vignettes/flowType/inst/doc/flowType.pdf" ], "vignetteTitles": [ "flowType package" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/flowType/inst/doc/flowType.R" ], "importsMe": [ "RchyOptimyx" ] }, "flowUtils": { "Package": "flowUtils", "Version": "1.38.0", "Depends": [ "R (>= 2.2.0)" ], "Imports": [ "Biobase", "graph", "methods", "stats", "utils", "corpcor", "RUnit", "XML", "flowCore (>= 1.32.0)" ], "Suggests": [ "gatingMLData" ], "License": "Artistic-2.0", "MD5sum": "f7173dce195bcc31576538e13fe668eb", "NeedsCompilation": "no", "Title": "Utilities for flow cytometry", "Description": "Provides utilities for flow cytometry data.", "biocViews": [ "CellBasedAssays", "DecisionTree", "FlowCytometry", "Infrastructure", "Software" ], "Author": "J. Spidlen., N. Gopalakrishnan, F. Hahne, B. Ellis, R. Gentleman, M. Dalphin, N. Le Meur, B. Purcell, W. Jiang", "Maintainer": "Josef Spidlen ", "URL": "https://github.com/jspidlen/flowUtils", "BugReports": "https://github.com/jspidlen/flowUtils/issues", "source.ver": "src/contrib/flowUtils_1.38.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/flowUtils_1.38.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/flowUtils_1.38.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/flowUtils_1.38.0.tgz", "vignettes": [ "vignettes/flowUtils/inst/doc/HowTo-flowUtils.pdf" ], "vignetteTitles": [ "Gating-ML support in R" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/flowUtils/inst/doc/HowTo-flowUtils.R" ], "importsMe": [ "CytoML", "FlowSOM" ], "suggestsMe": [ "gatingMLData" ] }, "flowViz": { "Package": "flowViz", "Version": "1.38.0", "Depends": [ "R (>= 2.7.0)", "flowCore", "lattice" ], "Imports": [ "stats4", "Biobase", "flowCore", "graphics", "grDevices", "grid", "KernSmooth", "lattice", "latticeExtra", "MASS", "methods", "RColorBrewer", "stats", "utils", "hexbin", "IDPmisc" ], "Suggests": [ "colorspace", "flowStats", "knitr" ], "License": "Artistic-2.0", "MD5sum": "ca001789da5bf4d21a63d222d69255c7", "NeedsCompilation": "no", "Title": "Visualization for flow cytometry", "Description": "Provides visualization tools for flow cytometry data.", "biocViews": [ "CellBasedAssays", "FlowCytometry", "Infrastructure", "Software", "Visualization" ], "Author": "B. Ellis, R. Gentleman, F. Hahne, N. Le Meur, D. Sarkar, M. Jiang", "Maintainer": "Mike Jiang ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/flowViz_1.38.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/flowViz_1.38.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/flowViz_1.38.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/flowViz_1.38.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/flowViz/inst/doc/filters.R" ], "htmlDocs": [ "vignettes/flowViz/inst/doc/filters.html" ], "htmlTitles": [ "Visualizing Gates with Flow Cytometry Data" ], "dependsOnMe": [ "flowFP", "flowQ", "flowTrans", "flowVS", "plateCore", "QUALIFIER" ], "importsMe": [ "flowClust", "flowFit", "flowQ", "flowStats", "flowTrans", "flowWorkspace", "ncdfFlow", "openCyto", "QUALIFIER" ], "suggestsMe": [ "flowBeads", "flowClean", "flowCore", "ggcyto" ] }, "flowVS": { "Package": "flowVS", "Version": "1.6.0", "Depends": [ "R (>= 3.2)", "methods", "flowCore", "flowViz", "flowStats" ], "Suggests": [ "knitr", "vsn" ], "License": "Artistic-2.0", "MD5sum": "a4ad62ab4911bb10b5ae196a66f83d17", "NeedsCompilation": "no", "Title": "Variance stabilization in flow cytometry (and microarrays)", "Description": "Per-channel variance stabilization from a collection of flow cytometry samples by Bertlett test for homogeneity of variances. The approach is applicable to microarrays data as well.", "biocViews": [ "CellBasedAssays", "FlowCytometry", "Microarray", "Software" ], "Author": "Ariful Azad", "Maintainer": "Ariful Azad ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/flowVS_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/flowVS_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/flowVS_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/flowVS_1.6.0.tgz", "vignettes": [ "vignettes/flowVS/inst/doc/flowVS.pdf" ], "vignetteTitles": [ "flowVS: Cell population matching and meta-clustering in Flow Cytometry" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/flowVS/inst/doc/flowVS.R" ] }, "flowWorkspace": { "Package": "flowWorkspace", "Version": "3.20.5", "Depends": [ "R (>= 2.16.0)", "flowCore(>= 1.39.9)", "ncdfFlow(>= 2.19.5)" ], "Imports": [ "Biobase", "BiocGenerics", "graph", "graphics", "lattice", "methods", "stats", "stats4", "utils", "RBGL", "XML", "tools", "gridExtra", "Rgraphviz", "data.table", "dplyr", "latticeExtra", "Rcpp", "RColorBrewer", "stringr", "scales", "flowViz" ], "LinkingTo": [ "Rcpp", "BH(>= 1.62.0-1)" ], "Suggests": [ "testthat", "flowWorkspaceData", "RSVGTipsDevice", "knitr", "ggcyto" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "6edfea0f1de577f5ba464c9c33153dce", "NeedsCompilation": "yes", "Title": "Infrastructure for representing and interacting with the gated cytometry", "Description": "This package is designed to facilitate comparison of automated gating methods against manual gating done in flowJo. This package allows you to import basic flowJo workspaces into BioConductor and replicate the gating from flowJo using the flowCore functionality. Gating hierarchies, groups of samples, compensation, and transformation are performed so that the output matches the flowJo analysis.", "biocViews": [ "DataImport", "DataRepresentation", "FlowCytometry", "Preprocessing", "Software" ], "Author": "Greg Finak, Mike Jiang", "Maintainer": "Greg Finak ,Mike Jiang ", "SystemRequirements": "xml2, GNU make", "VignetteBuilder": "knitr", "source.ver": "src/contrib/flowWorkspace_3.20.5.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/flowWorkspace_3.20.5.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/flowWorkspace_3.20.5.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/flowWorkspace_3.20.5.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": true, "hasLICENSE": false, "Rfiles": [ "vignettes/flowWorkspace/inst/doc/HowToMergeGatingSet.R", "vignettes/flowWorkspace/inst/doc/plotGate.R" ], "htmlDocs": [ "vignettes/flowWorkspace/inst/doc/HowToMergeGatingSet.html", "vignettes/flowWorkspace/inst/doc/plotGate.html" ], "htmlTitles": [ "How to merge GatingSets", "How to plot gated data" ], "dependsOnMe": [ "flowStats", "ggcyto", "openCyto", "QUALIFIER" ], "importsMe": [ "CytoML", "openCyto", "QUALIFIER" ], "suggestsMe": [ "COMPASS", "flowClust", "flowCore" ] }, "fmcsR": { "Package": "fmcsR", "Version": "1.16.0", "Depends": [ "R (>= 2.10.0)", "ChemmineR", "methods" ], "Imports": [ "RUnit", "methods", "ChemmineR", "BiocGenerics", "parallel" ], "Suggests": [ "BiocStyle", "knitr", "knitcitations", "knitrBootstrap" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "5bd457e200849f15b56c9a22e9f0d688", "NeedsCompilation": "yes", "Title": "Mismatch Tolerant Maximum Common Substructure Searching", "Description": "The fmcsR package introduces an efficient maximum common substructure (MCS) algorithms combined with a novel matching strategy that allows for atom and/or bond mismatches in the substructures shared among two small molecules. The resulting flexible MCSs (FMCSs) are often larger than strict MCSs, resulting in the identification of more common features in their source structures, as well as a higher sensitivity in finding compounds with weak structural similarities. The fmcsR package provides several utilities to use the FMCS algorithm for pairwise compound comparisons, structure similarity searching and clustering.", "biocViews": [ "BiomedicalInformatics", "CellBasedAssays", "Cheminformatics", "Clustering", "DataImport", "Infrastructure", "MicrotitrePlateAssay", "Pharmacogenetics", "Pharmacogenomics", "Proteomics", "Software", "Visualization" ], "Author": "Yan Wang, Tyler Backman, Kevin Horan, Thomas Girke", "Maintainer": "Thomas Girke ", "URL": "https://github.com/girke-lab/fmcsR", "VignetteBuilder": "knitr", "source.ver": "src/contrib/fmcsR_1.16.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/fmcsR_1.16.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/fmcsR_1.16.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/fmcsR_1.16.0.tgz", "hasREADME": true, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/fmcsR/inst/doc/fmcsR.R" ], "htmlDocs": [ "vignettes/fmcsR/inst/doc/fmcsR.html" ], "htmlTitles": [ "fmcsR" ], "importsMe": [ "Rcpi" ], "suggestsMe": [ "ChemmineR" ] }, "focalCall": { "Package": "focalCall", "Version": "1.8.0", "Depends": [ "R(>= 2.10.0)", "CGHcall" ], "Suggests": [ "RUnit", "BiocGenerics" ], "License": "GPL-2", "MD5sum": "51c3ec942b621a5c54b262712a6ae94f", "NeedsCompilation": "no", "Title": "Detection of focal aberrations in DNA copy number data", "Description": "Detection of genomic focal aberrations in high-resolution DNA copy number data", "biocViews": [ "Microarray", "Preprocessing", "Sequencing", "Software", "Visualization" ], "Author": "Oscar Krijgsman", "Maintainer": "Oscar Krijgsman ", "URL": "https://github.com/OscarKrijgsman/focalCall", "source.ver": "src/contrib/focalCall_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/focalCall_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/focalCall_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/focalCall_1.8.0.tgz", "vignettes": [ "vignettes/focalCall/inst/doc/focalCall.pdf" ], "vignetteTitles": [ "focalCall" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/focalCall/inst/doc/focalCall.R" ] }, "FourCSeq": { "Package": "FourCSeq", "Version": "1.8.0", "Depends": [ "R (>= 3.0)", "GenomicRanges", "ggplot2", "DESeq2 (>= 1.9.11)", "splines", "methods", "LSD" ], "Imports": [ "DESeq2", "Biobase", "Biostrings", "GenomicRanges", "SummarizedExperiment", "Rsamtools", "ggbio", "reshape2", "rtracklayer", "fda", "GenomicAlignments", "gtools", "Matrix" ], "Suggests": [ "BiocStyle", "knitr", "TxDb.Dmelanogaster.UCSC.dm3.ensGene" ], "License": "GPL (>= 3)", "MD5sum": "85adbe4417919cbf51b7a7b6edcce543", "NeedsCompilation": "no", "Title": "Package analyse 4C sequencing data", "Description": "FourCSeq is an R package dedicated to the analysis of (multiplexed) 4C sequencing data. The package provides a pipeline to detect specific interactions between DNA elements and identify differential interactions between conditions. The statistical analysis in R starts with individual bam files for each sample as inputs. To obtain these files, the package contains a python script (extdata/python/demultiplex.py) to demultiplex libraries and trim off primer sequences. With a standard alignment software the required bam files can be then be generated.", "biocViews": [ "Preprocessing", "Sequencing", "Software" ], "Author": "Felix A. Klein, EMBL Heidelberg", "Maintainer": "Felix A. Klein ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/FourCSeq_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/FourCSeq_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/FourCSeq_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/FourCSeq_1.8.0.tgz", "vignettes": [ "vignettes/FourCSeq/inst/doc/FourCSeq.pdf" ], "vignetteTitles": [ "FourCSeq" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/FourCSeq/inst/doc/FourCSeq.R" ] }, "FRGEpistasis": { "Package": "FRGEpistasis", "Version": "1.10.0", "Depends": [ "R (>= 2.15)", "MASS", "fda", "methods", "stats" ], "Imports": [ "utils" ], "License": "GPL-2", "MD5sum": "9c5f90b2cb02627e572886074b87c13d", "NeedsCompilation": "no", "Title": "Epistasis Analysis for Quantitative Traits by Functional Regression Model", "Description": "A Tool for Epistasis Analysis Based on Functional Regression Model", "biocViews": [ "GeneticVariability", "Genetics", "NetworkInference", "Software" ], "Author": "Futao Zhang", "Maintainer": "Futao Zhang ", "source.ver": "src/contrib/FRGEpistasis_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/FRGEpistasis_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/FRGEpistasis_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/FRGEpistasis_1.10.0.tgz", "vignettes": [ "vignettes/FRGEpistasis/inst/doc/FRGEpistasis.pdf" ], "vignetteTitles": [ "FRGEpistasis: A Tool for Epistasis Analysis Based on Functional Regression Model" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/FRGEpistasis/inst/doc/FRGEpistasis.R" ] }, "frma": { "Package": "frma", "Version": "1.26.0", "Depends": [ "R (>= 2.10.0)", "Biobase (>= 2.6.0)" ], "Imports": [ "Biobase", "MASS", "DBI", "affy", "methods", "oligo", "oligoClasses", "preprocessCore", "utils", "BiocGenerics" ], "Suggests": [ "hgu133afrmavecs", "frmaExampleData" ], "License": "GPL (>= 2)", "MD5sum": "2a965933dae0acd8efe0587be791d407", "NeedsCompilation": "no", "Title": "Frozen RMA and Barcode", "Description": "Preprocessing and analysis for single microarrays and microarray batches.", "biocViews": [ "Microarray", "Preprocessing", "Software" ], "Author": "Matthew N. McCall , Rafael A. Irizarry , with contributions from Terry Therneau", "Maintainer": "Matthew N. McCall ", "URL": "http://bioconductor.org", "source.ver": "src/contrib/frma_1.26.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/frma_1.26.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/frma_1.26.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/frma_1.26.0.tgz", "vignettes": [ "vignettes/frma/inst/doc/frma.pdf" ], "vignetteTitles": [ "frma: Preprocessing for single arrays and array batches" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/frma/inst/doc/frma.R" ], "importsMe": [ "ChIPXpress", "DeSousa2013" ], "suggestsMe": [ "antiProfilesData", "frmaTools" ] }, "frmaTools": { "Package": "frmaTools", "Version": "1.26.0", "Depends": [ "R (>= 2.10.0)", "affy" ], "Imports": [ "Biobase", "DBI", "methods", "preprocessCore", "stats", "utils" ], "Suggests": [ "oligo", "pd.huex.1.0.st.v2", "pd.hugene.1.0.st.v1", "frma", "affyPLM", "hgu133aprobe", "hgu133atagprobe", "hgu133plus2probe", "hgu133acdf", "hgu133atagcdf", "hgu133plus2cdf", "hgu133afrmavecs", "frmaExampleData" ], "License": "GPL (>= 2)", "MD5sum": "ee49579f3e48b86f5dc3825359263dc8", "NeedsCompilation": "no", "Title": "Frozen RMA Tools", "Description": "Tools for advanced use of the frma package.", "biocViews": [ "Microarray", "Preprocessing", "Software" ], "Author": "Matthew N. McCall , Rafael A. Irizarry ", "Maintainer": "Matthew N. McCall ", "URL": "http://bioconductor.org", "source.ver": "src/contrib/frmaTools_1.26.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/frmaTools_1.26.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/frmaTools_1.26.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/frmaTools_1.26.0.tgz", "vignettes": [ "vignettes/frmaTools/inst/doc/frmaTools.pdf" ], "vignetteTitles": [ "frmaTools: Create packages containing the vectors used by frma." ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/frmaTools/inst/doc/frmaTools.R" ], "importsMe": [ "DeSousa2013" ] }, "FunChIP": { "Package": "FunChIP", "Version": "1.0.0", "Depends": [ "R (>= 3.2)", "GenomicRanges" ], "Imports": [ "shiny", "fda", "doParallel", "GenomicAlignments", "Rcpp", "methods", "foreach", "parallel", "GenomeInfoDb", "Rsamtools", "grDevices", "graphics", "stats" ], "LinkingTo": [ "Rcpp" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "765c670db9c931a57a48858a35204be1", "NeedsCompilation": "yes", "Title": "Clustering and Alignment of ChIP-Seq peaks based on their shapes", "Description": "Preprocessing and smoothing of ChIP-Seq peaks and efficient implementation of the k-mean alignment algorithm to classify them.", "biocViews": [ "ChIPSeq", "Clustering", "Software", "StatisticalMethod" ], "Author": "Alice Parodi [aut, cre], Marco Morelli [aut, cre], Laura M. Sangalli [aut], Piercesare Secchi [aut], Simone Vantini [aut]", "Maintainer": "Alice Parodi ", "source.ver": "src/contrib/FunChIP_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/FunChIP_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/FunChIP_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/FunChIP_1.0.0.tgz", "vignettes": [ "vignettes/FunChIP/inst/doc/FunChIP.pdf" ], "vignetteTitles": [ "An introduction to FunChIP" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/FunChIP/inst/doc/FunChIP.R" ] }, "FunciSNP": { "Package": "FunciSNP", "Version": "1.18.0", "Depends": [ "R (>= 2.14.0)", "ggplot2", "TxDb.Hsapiens.UCSC.hg19.knownGene", "FunciSNP.data" ], "Imports": [ "methods", "BiocGenerics", "Biobase", "S4Vectors", "IRanges", "GenomicRanges", "Rsamtools (>= 1.6.1)", "rtracklayer (>= 1.14.1)", "ChIPpeakAnno (>= 2.2.0)", "VariantAnnotation", "plyr", "snpStats", "ggplot2 (>= 0.9.0)", "reshape (>= 0.8.4)", "scales" ], "Suggests": [ "org.Hs.eg.db" ], "Enhances": [ "parallel" ], "License": "GPL-3", "MD5sum": "a751ed9df193c00549a20e766f0139ee", "NeedsCompilation": "no", "Title": "Integrating Functional Non-coding Datasets with Genetic Association Studies to Identify Candidate Regulatory SNPs", "Description": "FunciSNP integrates information from GWAS, 1000genomes and chromatin feature to identify functional SNP in coding or non-coding regions.", "biocViews": [ "Annotation", "DataImport", "DataRepresentation", "Infrastructure", "SequenceMatching", "Software" ], "Author": "Simon G. Coetzee and Houtan Noushmehr, PhD ", "Maintainer": "Simon G. Coetzee ", "URL": "http://coetzeeseq.usc.edu/publication/Coetzee_SG_et_al_2012/", "source.ver": "src/contrib/FunciSNP_1.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/FunciSNP_1.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/FunciSNP_1.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/FunciSNP_1.18.0.tgz", "vignettes": [ "vignettes/FunciSNP/inst/doc/FunciSNP_vignette.pdf" ], "vignetteTitles": [ "FunciSNP Vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/FunciSNP/inst/doc/FunciSNP_vignette.R" ] }, "gaga": { "Package": "gaga", "Version": "2.20.0", "Depends": [ "R (>= 2.8.0)", "Biobase", "coda", "EBarrays", "mgcv" ], "Enhances": [ "parallel" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "99871317f2326ff4bf53cda843b028a1", "NeedsCompilation": "yes", "Title": "GaGa hierarchical model for high-throughput data analysis", "Description": "Implements the GaGa model for high-throughput data analysis, including differential expression analysis, supervised gene clustering and classification. Additionally, it performs sequential sample size calculations using the GaGa and LNNGV models (the latter from EBarrays package).", "biocViews": [ "Classification", "DifferentialExpression", "MassSpectrometry", "MultipleComparison", "OneChannel", "Software" ], "Author": "David Rossell .", "Maintainer": "David Rossell ", "source.ver": "src/contrib/gaga_2.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/gaga_2.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/gaga_2.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/gaga_2.20.0.tgz", "vignettes": [ "vignettes/gaga/inst/doc/gagamanual.pdf" ], "vignetteTitles": [ "Manual for the gaga library" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/gaga/inst/doc/gagamanual.R" ], "importsMe": [ "casper" ] }, "gage": { "Package": "gage", "Version": "2.24.0", "Depends": [ "R (>= 2.10)" ], "Imports": [ "graph", "KEGGREST", "AnnotationDbi" ], "Suggests": [ "pathview", "gageData", "GO.db", "org.Hs.eg.db", "hgu133a.db", "GSEABase", "Rsamtools", "GenomicAlignments", "TxDb.Hsapiens.UCSC.hg19.knownGene", "DESeq", "DESeq2", "edgeR", "limma" ], "License": "GPL (>=2.0)", "MD5sum": "5de8a0bf2b15968d72996a10c722941a", "NeedsCompilation": "no", "Title": "Generally Applicable Gene-set Enrichment for Pathway Analysis", "Description": "GAGE is a published method for gene set (enrichment or GSEA) or pathway analysis. GAGE is generally applicable independent of microarray or RNA-Seq data attributes including sample sizes, experimental designs, assay platforms, and other types of heterogeneity, and consistently achieves superior performance over other frequently used methods. In gage package, we provide functions for basic GAGE analysis, result processing and presentation. We have also built pipeline routines for of multiple GAGE analyses in a batch, comparison between parallel analyses, and combined analysis of heterogeneous data from different sources/studies. In addition, we provide demo microarray data and commonly used gene set data based on KEGG pathways and GO terms. These funtions and data are also useful for gene set analysis using other methods.", "biocViews": [ "DifferentialExpression", "GO", "GeneExpression", "GeneSetEnrichment", "Genetics", "Microarray", "MultipleComparison", "OneChannel", "Pathways", "RNASeq", "Sequencing", "Software", "SystemsBiology", "TwoChannel" ], "Author": "Weijun Luo", "Maintainer": "Weijun Luo ", "URL": "http://www.biomedcentral.com/1471-2105/10/161", "source.ver": "src/contrib/gage_2.24.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/gage_2.24.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/gage_2.24.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/gage_2.24.0.tgz", "vignettes": [ "vignettes/gage/inst/doc/dataPrep.pdf", "vignettes/gage/inst/doc/gage.pdf", "vignettes/gage/inst/doc/RNA-seqWorkflow.pdf" ], "vignetteTitles": [ "Gene set and data preparation", "Generally Applicable Gene-set/Pathway Analysis", "RNA-Seq Data Pathway and Gene-set Analysis Workflows" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/gage/inst/doc/dataPrep.R", "vignettes/gage/inst/doc/gage.R", "vignettes/gage/inst/doc/RNA-seqWorkflow.R" ], "dependsOnMe": [ "EGSEA" ], "suggestsMe": [ "FGNet", "gageData", "pathview" ] }, "gaggle": { "Package": "gaggle", "Version": "1.42.0", "Depends": [ "R (>= 2.3.0)", "rJava (>= 0.4)", "graph (>= 1.10.2)", "RUnit (>= 0.4.17)" ], "License": "GPL version 2 or newer", "MD5sum": "f28dd77356d82beeb360aa5e1e6ea13b", "NeedsCompilation": "no", "Title": "Broadcast data between R and Gaggle", "Description": "This package contains functions enabling data exchange between R and Gaggle enabled bioinformatics software, including Cytoscape, Firegoose and Gaggle Genome Browser.", "biocViews": [ "Annotation", "DataImport", "GraphAndNetwork", "Software", "ThirdPartyClient", "Visualization" ], "Author": "Paul Shannon ", "Maintainer": "Christopher Bare ", "URL": "http://gaggle.systemsbiology.net/docs/geese/r/", "source.ver": "src/contrib/gaggle_1.42.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/gaggle_1.42.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/gaggle_1.42.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/gaggle_1.42.0.tgz", "vignettes": [ "vignettes/gaggle/inst/doc/gaggle.pdf" ], "vignetteTitles": [ "Gaggle Overview" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/gaggle/inst/doc/gaggle.R" ] }, "gaia": { "Package": "gaia", "Version": "2.18.0", "Depends": [ "R (>= 2.10)" ], "License": "GPL-2", "MD5sum": "cec0ada4060f4bfc9f2afe2b39ae8a7d", "NeedsCompilation": "no", "Title": "GAIA: An R package for genomic analysis of significant chromosomal aberrations.", "Description": "This package allows to assess the statistical significance of chromosomal aberrations.", "biocViews": [ "CopyNumberVariation", "Software", "aCGH" ], "Author": "Sandro Morganella et al.", "Maintainer": "S. Morganella ", "source.ver": "src/contrib/gaia_2.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/gaia_2.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/gaia_2.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/gaia_2.18.0.tgz", "vignettes": [ "vignettes/gaia/inst/doc/gaia.pdf" ], "vignetteTitles": [ "gaia" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/gaia/inst/doc/gaia.R" ] }, "GAprediction": { "Package": "GAprediction", "Version": "1.0.0", "Depends": [ "R (>= 3.3)" ], "Imports": [ "glmnet", "stats", "utils", "Matrix" ], "Suggests": [ "knitr", "rmarkdown" ], "License": "GPL (>=2)", "MD5sum": "9fa2206c1762a7dc05a8c3584be397db", "NeedsCompilation": "no", "Title": "Prediction of gestational age with Illumina HumanMethylation450 data", "Description": "[GAprediction] predicts gestational age using Illumina HumanMethylation450 CpG data.", "biocViews": [ "BiomedicalInformatics", "DNAMethylation", "Epigenetics", "Regression", "Software" ], "Author": "Jon Bohlin", "Maintainer": "Jon Bohlin ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/GAprediction_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GAprediction_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GAprediction_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GAprediction_1.0.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GAprediction/inst/doc/GAprediction.R" ], "htmlDocs": [ "vignettes/GAprediction/inst/doc/GAprediction.html" ], "htmlTitles": [ "GAprediction" ] }, "garfield": { "Package": "garfield", "Version": "1.2.0", "Suggests": [ "knitr" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "3e794e6a29b152e90f298fdeeb2a6cc5", "NeedsCompilation": "yes", "Title": "GWAS Analysis of Regulatory or Functional Information Enrichment with LD correction", "Description": "GARFIELD is a non-parametric functional enrichment analysis approach described in the paper GARFIELD: GWAS analysis of regulatory or functional information enrichment with LD correction. Briefly, it is a method that leverages GWAS findings with regulatory or functional annotations (primarily from ENCODE and Roadmap epigenomics data) to find features relevant to a phenotype of interest. It performs greedy pruning of GWAS SNPs (LD r2 > 0.1) and then annotates them based on functional information overlap. Next, it quantifies Fold Enrichment (FE) at various GWAS significance cutoffs and assesses them by permutation testing, while matching for minor allele frequency, distance to nearest transcription start site and number of LD proxies (r2 > 0.8).", "biocViews": [ "Annotation", "FunctionalPrediction", "GenomeAnnotation", "Software", "StatisticalMethod" ], "Author": "Sandro Morganella ", "Maintainer": "Valentina Iotchkova ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/garfield_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/garfield_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/garfield_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/garfield_1.2.0.tgz", "vignettes": [ "vignettes/garfield/inst/doc/vignette.pdf" ], "vignetteTitles": [ "garfield Guide" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false }, "gaucho": { "Package": "gaucho", "Version": "1.10.0", "Depends": [ "R (>= 3.0.0)", "compiler", "GA", "graph", "heatmap.plus", "png", "Rgraphviz" ], "Suggests": [ "knitr" ], "License": "GPL-3", "MD5sum": "175d31df64eb152af31d62b5ba17bddb", "NeedsCompilation": "no", "Title": "Genetic Algorithms for Understanding Clonal Heterogeneity and Ordering", "Description": "Use genetic algorithms to determine the relationship between clones in heterogenous populations such as cancer sequencing samples", "biocViews": [ "Genetics", "SNP", "Sequencing", "Software", "SomaticMutation" ], "Author": "Alex Murison [aut, cre], Christopher Wardell [aut, cre]", "Maintainer": "Alex Murison , Christopher Wardell ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/gaucho_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/gaucho_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/gaucho_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/gaucho_1.10.0.tgz", "vignettes": [ "vignettes/gaucho/inst/doc/gaucho_vignette.pdf" ], "vignetteTitles": [ "An introduction to gaucho" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/gaucho/inst/doc/gaucho_vignette.R" ] }, "gcatest": { "Package": "gcatest", "Version": "1.4.0", "Depends": [ "R (>= 3.2)" ], "Imports": [ "lfa" ], "Suggests": [ "knitr", "ggplot2" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "95ad2edb8ea807e6eeba9a66ecdc6916", "NeedsCompilation": "yes", "Title": "Genotype Conditional Association TEST", "Description": "GCAT is an association test for genome wide association studies that controls for population structure under a general class of trait. models.", "biocViews": [ "DimensionReduction", "GenomeWideAssociation", "PrincipalComponent", "SNP", "Software" ], "Author": "Wei Hao, Minsun Song, John D. Storey", "Maintainer": "Wei Hao , John D. Storey ", "URL": "https://github.com/StoreyLab/gcatest", "VignetteBuilder": "knitr", "BugReports": "https://github.com/StoreyLab/gcatest/issues", "source.ver": "src/contrib/gcatest_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/gcatest_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/gcatest_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/gcatest_1.4.0.tgz", "vignettes": [ "vignettes/gcatest/inst/doc/gcatest.pdf" ], "vignetteTitles": [ "gcat Package" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/gcatest/inst/doc/gcatest.R" ] }, "gCMAP": { "Package": "gCMAP", "Version": "1.18.0", "Depends": [ "GSEABase", "limma (>= 3.20.0)" ], "Imports": [ "Biobase", "methods", "GSEAlm", "Category", "Matrix (>= 1.0.9)", "parallel", "annotate", "genefilter", "AnnotationDbi", "DESeq" ], "Suggests": [ "BiocGenerics", "KEGG.db", "reactome.db", "RUnit", "GO.db", "mgsa" ], "Enhances": [ "bigmemory", "bigmemoryExtras (>= 1.1.2)" ], "License": "Artistic-2.0", "MD5sum": "033cafeefb2625f08148e66b105acfaf", "NeedsCompilation": "no", "Title": "Tools for Connectivity Map-like analyses", "Description": "The gCMAP package provides a toolkit for comparing differential gene expression profiles through gene set enrichment analysis. Starting from normalized microarray or RNA-seq gene expression values (stored in lists of ExpressionSet and CountDataSet objects) the package performs differential expression analysis using the limma or DESeq packages. Supplying a simple list of gene identifiers, global differential expression profiles or data from complete experiments as input, users can use a unified set of several well-known gene set enrichment analysis methods to retrieve experiments with similar changes in gene expression. To take into account the directionality of gene expression changes, gCMAPQuery introduces the SignedGeneSet class, directly extending GeneSet from the GSEABase package. To increase performance of large queries, multiple gene sets are stored as sparse incidence matrices within CMAPCollection eSets. gCMAP offers implementations of 1. Fisher's exact test (Fisher, J R Stat Soc, 1922) 2. The \"connectivity map\" method (Lamb et al, Science, 2006) 3. Parametric and non-parametric t-statistic summaries (Jiang & Gentleman, Bioinformatics, 2007) and 4. Wilcoxon / Mann-Whitney rank sum statistics (Wilcoxon, Biometrics Bulletin, 1945) as well as wrappers for the 5. camera (Wu & Smyth, Nucleic Acid Res, 2012) 6. mroast and romer (Wu et al, Bioinformatics, 2010) functions from the limma package and 7. wraps the gsea method from the mgsa package (Bauer et al, NAR, 2010). All methods return CMAPResult objects, an S4 class inheriting from AnnotatedDataFrame, containing enrichment statistics as well as annotation data and providing simple high-level summary plots.", "biocViews": [ "Annotation", "Microarray", "Pathways", "Software" ], "Author": "Thomas Sandmann , Richard Bourgon and Sarah Kummerfeld ", "Maintainer": "Thomas Sandmann ", "source.ver": "src/contrib/gCMAP_1.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/gCMAP_1.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/gCMAP_1.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/gCMAP_1.18.0.tgz", "vignettes": [ "vignettes/gCMAP/inst/doc/diffExprAnalysis.pdf", "vignettes/gCMAP/inst/doc/gCMAP.pdf" ], "vignetteTitles": [ "Creating reference datasets", "gCMAP classes and methods" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/gCMAP/inst/doc/diffExprAnalysis.R", "vignettes/gCMAP/inst/doc/gCMAP.R" ], "dependsOnMe": [ "gCMAPWeb" ] }, "gCMAPWeb": { "Package": "gCMAPWeb", "Version": "1.14.0", "Depends": [ "Biobase", "gCMAP (>= 1.3.0)", "methods", "R (>= 3.3.0)", "Rook" ], "Imports": [ "brew", "BiocGenerics", "annotate", "AnnotationDbi", "grDevices", "GSEABase", "hwriter", "parallel", "yaml" ], "Suggests": [ "affy", "ArrayExpress", "hgfocus.db", "hgu133a.db", "mgug4104a.db", "org.Hs.eg.db", "org.Mm.eg.db", "RUnit" ], "Enhances": [ "bigmemory", "bigmemoryExtras" ], "License": "Artistic-2.0", "MD5sum": "115446e32af2f57b719f35302b93f4ab", "NeedsCompilation": "no", "Title": "A web interface for gene-set enrichment analyses", "Description": "The gCMAPWeb R package provides a graphical user interface for the gCMAP package. gCMAPWeb uses the Rook package and can be used either on a local machine, leveraging R's internal web server, or run on a dedicated rApache web server installation. gCMAPWeb allows users to search their own data sources and instructions to generate reference datasets from public repositories are included with the package. The package supports three common types of analyses, specifically queries with 1. one or two sets of query gene identifiers, whose members are expected to show changes in gene expression in a consistent direction. For example, an up-regulated gene set might contain genes activated by a transcription factor, a down-regulated geneset targets repressed by the same factor. 2. a single set of query gene identifiers, whose members are expected to show divergent differential expression (non-directional query). For example, members of a particular signaling pathway, some of which may be up- some down-regulated in response to a stimulus. 3. a query with the complete results of a differential expression profiling experiment. For example, gene identifiers and z-scores from a previous perturbation experiment. gCMAPWeb accepts three types of identifiers: EntreIds, gene Symbols and microarray probe ids and can be configured to work with any species supported by Bioconductor. For each query submission, significantly similar reference datasets will be identified and reported in graphical and tabular form.", "biocViews": [ "GUI", "GeneSetEnrichment", "Software", "Visualization" ], "Author": "Thomas Sandmann", "Maintainer": "Thomas Sandmann ", "source.ver": "src/contrib/gCMAPWeb_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/gCMAPWeb_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/gCMAPWeb_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/gCMAPWeb_1.14.0.tgz", "vignettes": [ "vignettes/gCMAPWeb/inst/doc/gCMAPWeb.pdf", "vignettes/gCMAPWeb/inst/doc/referenceDatasets.pdf" ], "vignetteTitles": [ "gCMAPWeb configuration", "Recreating the Broad Connectivity Map v1" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/gCMAPWeb/inst/doc/gCMAPWeb.R", "vignettes/gCMAPWeb/inst/doc/referenceDatasets.R" ] }, "gCrisprTools": { "Package": "gCrisprTools", "Version": "1.0.0", "Depends": [ "R (>= 3.3)" ], "Imports": [ "Biobase", "limma", "RobustRankAggreg", "ggplot2", "parallel", "PANTHER.db", "BiocParallel", "rmarkdown", "grDevices", "graphics", "stats", "utils" ], "Suggests": [ "edgeR", "knitr", "grid", "AnnotationDbi", "org.Mm.eg.db", "org.Hs.eg.db" ], "License": "Artistic-2.0", "MD5sum": "619761c4784729d34f8c194cde055d4e", "NeedsCompilation": "no", "Title": "Suite of Functions for Pooled Crispr Screen QC and Analysis", "Description": "Set of tools for evaluating pooled high-throughput screening experiments, typically employing CRISPR/Cas9 or shRNA expression cassettes. Contains methods for interrogating library and cassette behavior within an experiment, identifying differentially abundant cassettes, aggregating signals to identify candidate targets for empirical validation, hypothesis testing, and comprehensive reporting.", "biocViews": [ "BiomedicalInformatics", "CRISPR", "CellBiology", "DifferentialExpression", "ExperimentalDesign", "FunctionalGenomics", "GeneSetEnrichment", "Genetics", "MultipleComparison", "Normalization", "Pharmacogenetics", "Pharmacogenomics", "PooledScreens", "Preprocessing", "QualityControl", "RNASeq", "Regression", "Software", "SystemsBiology", "Visualization" ], "Author": "Russell Bainer, Dariusz Ratman, Pete Haverty, Steve Lianoglou", "Maintainer": "Russell Bainer ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/gCrisprTools_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/gCrisprTools_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/gCrisprTools_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/gCrisprTools_1.0.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/gCrisprTools/inst/doc/Crispr_example_workflow.R", "vignettes/gCrisprTools/inst/doc/gCrisprTools_Vignette.R" ], "htmlDocs": [ "vignettes/gCrisprTools/inst/doc/Crispr_example_workflow.html", "vignettes/gCrisprTools/inst/doc/gCrisprTools_Vignette.html" ], "htmlTitles": [ "gCrisprTools_Vignette", "gCrisprTools_Vignette" ] }, "gcrma": { "Package": "gcrma", "Version": "2.46.0", "Depends": [ "R (>= 2.6.0)", "affy (>= 1.23.2)", "graphics", "methods", "stats", "utils" ], "Imports": [ "Biobase", "affy (>= 1.23.2)", "affyio (>= 1.13.3)", "XVector", "Biostrings (>= 2.11.32)", "splines", "BiocInstaller" ], "Suggests": [ "affydata", "tools", "splines", "hgu95av2cdf", "hgu95av2probe" ], "License": "LGPL", "Archs": "i386, x64", "MD5sum": "f4dcc2f63a74049cab8c8f4ba00a3a4d", "NeedsCompilation": "yes", "Title": "Background Adjustment Using Sequence Information", "Description": "Background adjustment using sequence information", "biocViews": [ "Microarray", "OneChannel", "Preprocessing", "Software" ], "Author": "Jean(ZHIJIN) Wu, Rafael Irizarry with contributions from James MacDonald Jeff Gentry", "Maintainer": "Z. Wu ", "source.ver": "src/contrib/gcrma_2.46.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/gcrma_2.46.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/gcrma_2.46.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/gcrma_2.46.0.tgz", "vignettes": [ "vignettes/gcrma/inst/doc/gcrma2.0.pdf" ], "vignetteTitles": [ "gcrma1.2" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "dependsOnMe": [ "affyILM", "affyPLM", "bgx", "maPredictDSC", "maskBAD", "simpleaffy", "webbioc" ], "importsMe": [ "affycoretools", "affylmGUI", "limmaGUI", "simpleaffy" ], "suggestsMe": [ "AffyExpress", "ArrayTools", "BiocCaseStudies", "panp" ] }, "gdsfmt": { "Package": "gdsfmt", "Version": "1.10.1", "Depends": [ "R (>= 2.15.0)" ], "Imports": [ "methods" ], "Suggests": [ "parallel", "digest", "crayon", "RUnit", "knitr", "BiocGenerics" ], "License": "LGPL-3", "Archs": "i386, x64", "MD5sum": "712765fe2a9bc321908d3b4bbf5c780b", "NeedsCompilation": "yes", "Title": "R Interface to CoreArray Genomic Data Structure (GDS) Files", "Description": "This package provides a high-level R interface to CoreArray Genomic Data Structure (GDS) data files, which are portable across platforms with hierarchical structure to store multiple scalable array-oriented data sets with metadata information. It is suited for large-scale datasets, especially for data which are much larger than the available random-access memory. The gdsfmt package offers the efficient operations specifically designed for integers of less than 8 bits, since a diploid genotype, like single-nucleotide polymorphism (SNP), usually occupies fewer bits than a byte. Data compression and decompression are available with relatively efficient random access. It is also allowed to read a GDS file in parallel with multiple R processes supported by the package parallel.", "biocViews": [ "DataImport", "Infrastructure", "Software" ], "Author": "Xiuwen Zheng [aut, cre], Stephanie Gogarten [ctb], Jean-loup Gailly and Mark Adler [ctb] (for the included zlib sources), Yann Collet [ctb] (for the included LZ4 sources), xz contributors (for the included liblzma sources)", "Maintainer": "Xiuwen Zheng ", "URL": "http://corearray.sourceforge.net/, http://github.com/zhengxwen/gdsfmt", "VignetteBuilder": "knitr", "BugReports": "http://github.com/zhengxwen/gdsfmt/issues", "source.ver": "src/contrib/gdsfmt_1.10.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/gdsfmt_1.10.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/gdsfmt_1.10.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/gdsfmt_1.10.1.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/gdsfmt/inst/doc/gdsfmt_vignette.R" ], "htmlDocs": [ "vignettes/gdsfmt/inst/doc/gdsfmt_vignette.html" ], "htmlTitles": [ "Introduction to GDS Format" ], "dependsOnMe": [ "bigmelon", "SeqArray", "SNPRelate" ], "importsMe": [ "GENESIS", "GWASTools", "SeqVarTools" ], "suggestsMe": [ "HIBAG" ] }, "geecc": { "Package": "geecc", "Version": "1.8.0", "Depends": [ "R (>= 3.3.0)", "methods" ], "Imports": [ "MASS", "hypergea (>= 1.3.0)", "gplots", "Rcpp (>= 0.11.3)", "graphics", "stats", "utils" ], "LinkingTo": [ "Rcpp" ], "Suggests": [ "hgu133plus2.db", "GO.db", "AnnotationDbi" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "da7eb4a8df95b7e8e6a6631ddd6bad83", "NeedsCompilation": "yes", "Title": "Gene Set Enrichment Analysis Extended to Contingency Cubes", "Description": "Use log-linear models to perform hypergeometric and chi-squared tests for gene set enrichments for two (based on contingency tables) or three categories (contingency cubes). Categories can be differentially expressed genes, GO terms, sequence length, GC content, chromosomal position, phylostrata, divergence-strata, ....", "biocViews": [ "BiologicalQuestion", "GO", "GeneExpression", "GeneSetEnrichment", "Microarray", "RNASeq", "Software", "StatisticalMethod", "Transcription", "WorkflowStep" ], "Author": "Markus Boenn", "Maintainer": "Markus Boenn ", "SystemRequirements": "Rcpp", "source.ver": "src/contrib/geecc_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/geecc_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/geecc_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/geecc_1.8.0.tgz", "vignettes": [ "vignettes/geecc/inst/doc/geecc.pdf" ], "vignetteTitles": [ "geecc User's Guide" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/geecc/inst/doc/geecc.R" ] }, "GEM": { "Package": "GEM", "Version": "1.0.0", "Depends": [ "R (>= 3.3)" ], "Imports": [ "tcltk", "ggplot2", "methods", "stats", "grDevices", "graphics", "utils" ], "Suggests": [ "knitr", "RUnit", "testthat", "BiocGenerics" ], "License": "Artistic-2.0", "MD5sum": "3cd2be88710dff507a818bbf70677748", "NeedsCompilation": "no", "Title": "GEM: fast association study for the interplay of Gene, Environment and Methylation", "Description": "Tools for analyzing EWAS, methQTL and GxE genome widely.", "biocViews": [ "DNAMethylation", "GUI", "GeneExpression", "GenomeWideAssociation", "MethylSeq", "MethylationArray", "Regression", "SNP", "Software" ], "Author": "Hong Pan, Joanna D Holbrook, Neerja Karnani, Chee-Keong Kwoh", "Maintainer": "Hong Pan ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/GEM_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GEM_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GEM_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GEM_1.0.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GEM/inst/doc/user_guide.R" ], "htmlDocs": [ "vignettes/GEM/inst/doc/user_guide.html" ], "htmlTitles": [ "The GEM User's Guide" ] }, "genArise": { "Package": "genArise", "Version": "1.50.0", "Depends": [ "R (>= 1.7.1)", "locfit", "tkrplot", "methods" ], "Imports": [ "graphics", "grDevices", "methods", "stats", "tcltk", "utils", "xtable" ], "License": "file LICENSE", "License_restricts_use": "yes", "MD5sum": "2aacab464c4b73150b235b5d602aa9da", "NeedsCompilation": "no", "Title": "Microarray Analysis tool", "Description": "genArise is an easy to use tool for dual color microarray data. Its GUI-Tk based environment let any non-experienced user performs a basic, but not simple, data analysis just following a wizard. In addition it provides some tools for the developer.", "biocViews": [ "Microarray", "Preprocessing", "Software", "TwoChannel" ], "Author": "Ana Patricia Gomez Mayen ,\\\\ Gustavo Corral Guille , \\\\ Lina Riego Ruiz ,\\\\ Gerardo Coello Coutino ", "Maintainer": "IFC Development Team ", "URL": "http://www.ifc.unam.mx/genarise", "source.ver": "src/contrib/genArise_1.50.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/genArise_1.50.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/genArise_1.50.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/genArise_1.50.0.tgz", "vignettes": [ "vignettes/genArise/inst/doc/genArise.pdf" ], "vignetteTitles": [ "genAriseGUI Vignette" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/genArise/inst/doc/genArise.R" ] }, "genbankr": { "Package": "genbankr", "Version": "1.2.1", "Depends": [ "methods" ], "Imports": [ "BiocGenerics", "IRanges", "GenomicRanges(>= 1.23.24)", "GenomicFeatures", "Biostrings", "VariantAnnotation", "rtracklayer", "S4Vectors", "GenomeInfoDb", "Biobase" ], "Suggests": [ "RUnit", "rentrez", "rmarkdown", "knitr", "BiocStyle" ], "License": "Artistic-2.0", "MD5sum": "95fa6d34cfd72605bc00a486dd37258e", "NeedsCompilation": "no", "Title": "Parsing GenBank files into semantically useful objects", "Description": "Reads Genbank files.", "biocViews": [ "DataImport", "Infrastructure", "Software" ], "Author": "Gabriel Becker [aut, cre], Michael Lawrence [aut]", "Maintainer": "Gabriel Becker ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/genbankr_1.2.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/genbankr_1.2.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/genbankr_1.2.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/genbankr_1.2.1.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/genbankr/inst/doc/genbankr.R" ], "htmlDocs": [ "vignettes/genbankr/inst/doc/genbankr.html" ], "htmlTitles": [ "genbankr" ] }, "GENE.E": { "Package": "GENE.E", "Version": "1.14.0", "Depends": [ "R (>= 2.7.0)", "rhdf5 (>= 2.8.0)", "RCurl (>= 1.6-6)" ], "Imports": [ "rhdf5", "RCurl" ], "Suggests": [ "RUnit", "BiocGenerics", "knitr", "golubEsets (>= 1.0)" ], "License": "GPL-2", "MD5sum": "dbb560cc71453a43919a31cbba095647", "NeedsCompilation": "no", "Title": "Interact with GENE-E from R", "Description": "Interactive exploration of matrices in GENE-E.", "biocViews": [ "Software", "ThirdPartyClient" ], "Author": "Joshua Gould", "Maintainer": "Joshua Gould ", "URL": "http://www.broadinstitute.org/cancer/software/GENE-E", "SystemRequirements": "GENE-E software.", "VignetteBuilder": "knitr", "source.ver": "src/contrib/GENE.E_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GENE.E_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GENE.E_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GENE.E_1.14.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GENE.E/inst/doc/GENE.E-vignette.R" ], "htmlDocs": [ "vignettes/GENE.E/inst/doc/GENE.E-vignette.html" ], "htmlTitles": [ "GENE.E Overview" ] }, "GeneAnswers": { "Package": "GeneAnswers", "Version": "2.16.0", "Depends": [ "R (>= 3.0.0)", "igraph", "RCurl", "annotate", "Biobase (>= 1.12.0)", "methods", "XML", "RSQLite", "MASS", "Heatplus", "RColorBrewer" ], "Imports": [ "RBGL", "annotate", "downloader" ], "Suggests": [ "GO.db", "KEGG.db", "reactome.db", "biomaRt", "AnnotationDbi", "org.Hs.eg.db", "org.Rn.eg.db", "org.Mm.eg.db", "org.Dm.eg.db", "graph" ], "License": "LGPL (>= 2)", "MD5sum": "947b2dcd80145b1152640d6a7bf9f9a4", "NeedsCompilation": "no", "Title": "Integrated Interpretation of Genes", "Description": "GeneAnswers provides an integrated tool for biological or medical interpretation of the given one or more groups of genes by means of statistical test.", "biocViews": [ "DataRepresentation", "GraphsAndNetworks", "Infrastructure", "Software", "Visualization" ], "Author": "Lei Huang, Gang Feng, Pan Du, Tian Xia, Xishu Wang, Jing, Wen, Warren Kibbe and Simon Lin", "Maintainer": "Lei Huang and Gang Feng ", "source.ver": "src/contrib/GeneAnswers_2.16.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GeneAnswers_2.16.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GeneAnswers_2.16.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GeneAnswers_2.16.0.tgz", "vignettes": [ "vignettes/GeneAnswers/inst/doc/geneAnswers.pdf", "vignettes/GeneAnswers/inst/doc/getListGIF.pdf" ], "vignetteTitles": [ "GeneAnswers", "GeneAnswers web-based visualization module" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GeneAnswers/inst/doc/geneAnswers.R", "vignettes/GeneAnswers/inst/doc/getListGIF.R" ] }, "geneAttribution": { "Package": "geneAttribution", "Version": "1.0.1", "Imports": [ "utils", "GenomicRanges", "org.Hs.eg.db", "BiocGenerics", "GenomeInfoDb", "GenomicFeatures", "IRanges", "rtracklayer" ], "Suggests": [ "TxDb.Hsapiens.UCSC.hg38.knownGene", "TxDb.Hsapiens.UCSC.hg19.knownGene", "knitr", "rmarkdown", "testthat" ], "License": "Artistic-2.0", "MD5sum": "fddf4b37ee5c134362649465ce16639c", "NeedsCompilation": "no", "Title": "Identification of candidate genes associated with genetic variation", "Description": "Identification of the most likely gene or genes through which variation at a given genomic locus in the human genome acts. The most basic functionality assumes that the closer gene is to the input locus, the more likely the gene is to be causative. Additionally, any empirical data that links genomic regions to genes (e.g. eQTL or genome conformation data) can be used if it is supplied in the UCSC .BED file format.", "biocViews": [ "GenePrediction", "GenomeWideAssociation", "GenomicVariation", "SNP", "Software", "VariantAnnotation" ], "Author": "Arthur Wuster", "Maintainer": "Arthur Wuster ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/geneAttribution_1.0.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/geneAttribution_1.0.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/geneAttribution_1.0.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/geneAttribution_1.0.1.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "htmlDocs": [ "vignettes/geneAttribution/inst/doc/geneAttribution.html" ], "htmlTitles": [ "Vignette Title" ] }, "GeneBreak": { "Package": "GeneBreak", "Version": "1.4.0", "Depends": [ "R(>= 3.2)", "QDNAseq", "CGHcall", "CGHbase", "GenomicRanges" ], "Imports": [ "graphics", "methods" ], "License": "GPL-2", "MD5sum": "dad705c997102ffb7f8c9bb3c5d19f00", "NeedsCompilation": "no", "Title": "Gene Break Detection", "Description": "Recurrent breakpoint gene detection on copy number aberration profiles.", "biocViews": [ "CopyNumberVariation", "DNASeq", "Genetics", "Sequencing", "Software", "Visualization", "WholeGenome", "aCGH" ], "Author": "Evert van den Broek, Stef van Lieshout", "Maintainer": "Evert van den Broek ", "URL": "https://github.com/stefvanlieshout/GeneBreak", "source.ver": "src/contrib/GeneBreak_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GeneBreak_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GeneBreak_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GeneBreak_1.4.0.tgz", "vignettes": [ "vignettes/GeneBreak/inst/doc/GeneBreak.pdf" ], "vignetteTitles": [ "GeneBreak" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GeneBreak/inst/doc/GeneBreak.R" ] }, "GeneExpressionSignature": { "Package": "GeneExpressionSignature", "Version": "1.20.0", "Depends": [ "R (>= 2.13)", "Biobase", "PGSEA" ], "Suggests": [ "apcluster", "GEOquery" ], "License": "GPL-2", "MD5sum": "829aab889c27167c3db2494668a5cdfd", "NeedsCompilation": "no", "Title": "Gene Expression Signature based Similarity Metric", "Description": "This package gives the implementations of the gene expression signature and its distance to each. Gene expression signature is represented as a list of genes whose expression is correlated with a biological state of interest. And its distance is defined using a nonparametric, rank-based pattern-matching strategy based on the Kolmogorov-Smirnov statistic. Gene expression signature and its distance can be used to detect similarities among the signatures of drugs, diseases, and biological states of interest.", "biocViews": [ "GeneExpression", "Software" ], "Author": "Yang Cao", "Maintainer": "Yang Cao , Fei Li ,Lu Han ", "source.ver": "src/contrib/GeneExpressionSignature_1.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GeneExpressionSignature_1.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GeneExpressionSignature_1.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GeneExpressionSignature_1.20.0.tgz", "vignettes": [ "vignettes/GeneExpressionSignature/inst/doc/GeneExpressionSignature.pdf" ], "vignetteTitles": [ "GeneExpressionSignature" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GeneExpressionSignature/inst/doc/GeneExpressionSignature.R" ] }, "genefilter": { "Package": "genefilter", "Version": "1.56.0", "Imports": [ "S4Vectors (>= 0.9.42)", "AnnotationDbi", "annotate", "Biobase", "graphics", "methods", "stats", "survival" ], "Suggests": [ "class", "hgu95av2.db", "tkWidgets", "ALL", "ROC", "DESeq", "pasilla", "BiocStyle", "knitr" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "919e4deb451ca4e9dbea1e125e15cf98", "NeedsCompilation": "yes", "Title": "genefilter: methods for filtering genes from high-throughput experiments", "Description": "Some basic functions for filtering genes", "biocViews": [ "Microarray", "Software" ], "Author": "R. Gentleman, V. Carey, W. Huber, F. Hahne", "Maintainer": "Bioconductor Package Maintainer ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/genefilter_1.56.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/genefilter_1.56.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/genefilter_1.56.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/genefilter_1.56.0.tgz", "vignettes": [ "vignettes/genefilter/inst/doc/howtogenefilter.pdf", "vignettes/genefilter/inst/doc/howtogenefinder.pdf", "vignettes/genefilter/inst/doc/independent_filtering_plots.pdf", "vignettes/genefilter/inst/doc/independent_filtering.pdf" ], "vignetteTitles": [ "Using the genefilter function to filter genes from a microarray dataset", "How to find genes whose expression profile is similar to that of specified genes", "Additional plots for: Independent filtering increases power for detecting differentially expressed genes, Bourgon et al., PNAS (2010)", "Diagnostics for independent filtering" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/genefilter/inst/doc/howtogenefilter.R", "vignettes/genefilter/inst/doc/howtogenefinder.R", "vignettes/genefilter/inst/doc/independent_filtering_plots.R", "vignettes/genefilter/inst/doc/independent_filtering.R" ], "dependsOnMe": [ "a4Base", "ampliQueso", "cellHTS2", "charm", "CNTools", "GeneMeta", "Hiiragi2013", "simpleaffy", "SISPA", "sva" ], "importsMe": [ "affyQCReport", "annmap", "arrayQualityMetrics", "Category", "covRNA", "DESeq", "DESeq2", "DEXSeq", "eisa", "gCMAP", "GGBase", "GSRI", "IHWpaper", "JunctionSeq", "methyAnalysis", "methylumi", "minfi", "MLInterfaces", "mogsa", "pcaExplorer", "PECA", "phenoTest", "Ringo", "RNAinteractMAPK", "simpleaffy", "TCGAbiolinks", "tilingArray", "XDE" ], "suggestsMe": [ "AffyExpress", "annotate", "ArrayTools", "BiocCaseStudies", "BioNet", "categoryCompare", "clusterStab", "codelink", "compcodeR", "curatedBladderData", "curatedCRCData", "curatedOvarianData", "factDesign", "ffpe", "ffpeExampleData", "gageData", "GenoGAM", "GenomicFiles", "GOstats", "GSAR", "GSEAlm", "GSVA", "HDF5Array", "logicFS", "lumi", "MAQCsubset", "MCRestimate", "npGSEA", "oligo", "oneChannelGUI", "phyloseq", "pvac", "qpgraph", "RforProteomics", "rheumaticConditionWOLLBOLD", "rtracklayer", "siggenes", "Single.mTEC.Transcriptomes", "SSPA", "topGO", "XDE" ] }, "genefu": { "Package": "genefu", "Version": "2.6.0", "Depends": [ "survcomp", "mclust", "limma", "biomaRt", "iC10", "AIMS", "R (>= 2.10)" ], "Imports": [ "amap" ], "Suggests": [ "GeneMeta", "breastCancerVDX", "breastCancerMAINZ", "breastCancerTRANSBIG", "breastCancerUPP", "breastCancerUNT", "breastCancerNKI", "rmeta", "Biobase", "xtable", "knitr", "caret", "survival" ], "License": "Artistic-2.0", "MD5sum": "345fda72b11c54d0edaa2ba34fc962b0", "NeedsCompilation": "no", "Title": "Computation of Gene Expression-Based Signatures in Breast Cancer", "Description": "Description: This package contains functions implementing various tasks usually required by gene expression analysis, especially in breast cancer studies: gene mapping between different microarray platforms, identification of molecular subtypes, implementation of published gene signatures, gene selection, and survival analysis.", "biocViews": [ "Classification", "Clustering", "DifferentialExpression", "GeneExpression", "Software", "Visualization" ], "Author": "Deena M.A. Gendoo, Natchar Ratanasirigulchai, Markus S. Schroder, Laia Pare, Joel S. Parker, Aleix Prat, and Benjamin Haibe-Kains", "Maintainer": "Benjamin Haibe-Kains , Markus Schroeder ", "URL": "http://www.pmgenomics.ca/bhklab/software/genefu", "VignetteBuilder": "knitr", "source.ver": "src/contrib/genefu_2.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/genefu_2.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/genefu_2.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/genefu_2.6.0.tgz", "vignettes": [ "vignettes/genefu/inst/doc/genefu.pdf" ], "vignetteTitles": [ "genefu An Introduction (HowTo)" ], "hasREADME": true, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/genefu/inst/doc/genefu.R" ], "dependsOnMe": [ "pbcmc" ], "suggestsMe": [ "breastCancerMAINZ", "breastCancerNKI", "breastCancerTRANSBIG", "breastCancerUNT", "breastCancerUPP", "breastCancerVDX" ] }, "GeneGA": { "Package": "GeneGA", "Version": "1.24.0", "Depends": [ "seqinr", "hash", "methods" ], "License": "GPL version 2", "MD5sum": "630008973a05590fc4459b2cacd94ea6", "NeedsCompilation": "no", "Title": "Design gene based on both mRNA secondary structure and codon usage bias using Genetic algorithm", "Description": "R based Genetic algorithm for gene expression optimization by considering both mRNA secondary structure and codon usage bias, GeneGA includes the information of highly expressed genes of almost 200 genomes. Meanwhile, Vienna RNA Package is needed to ensure GeneGA to function properly.", "biocViews": [ "GeneExpression", "Software" ], "Author": "Zhenpeng Li and Haixiu Huang", "Maintainer": "Zhenpeng Li ", "URL": "http://www.tbi.univie.ac.at/~ivo/RNA/", "source.ver": "src/contrib/GeneGA_1.24.0.tar.gz", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GeneGA_1.24.0.tgz", "vignettes": [ "vignettes/GeneGA/inst/doc/GeneGA.pdf" ], "vignetteTitles": [ "GeneGA" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GeneGA/inst/doc/GeneGA.R" ] }, "GeneGeneInteR": { "Package": "GeneGeneInteR", "Version": "1.0.0", "Depends": [ "R (>= 3.3)" ], "Imports": [ "snpStats", "mvtnorm", "GGtools", "Rsamtools", "igraph", "kernlab", "FactoMineR", "plspm", "IRanges", "GenomicRanges", "data.table", "rioja", "grDevices", "graphics", "stats", "utils" ], "License": "GPL (>= 2)", "MD5sum": "2c5dfe955fc42c0cd021453143c3735a", "NeedsCompilation": "no", "Title": "Tools for Testing Gene-Gene Interaction at the Gene Level", "Description": "The aim of this package is to propose several methods for testing gene-gene interaction in case-control association studies. Such a test can be done by aggregating SNP-SNP interaction tests performed at the SNP level (SSI) or by using gene-gene multidimensionnal methods (GGI) methods. The package also proposes tools for a graphic display of the results.", "biocViews": [ "GeneticVariability", "Genetics", "GenomeWideAssociation", "SNP", "Software" ], "Author": "Mathieu Emily, Nicolas Sounac, Florian Kroell, Magalie Houee-Bigot", "Maintainer": "Mathieu Emily , Magalie Houee-Bigot ", "source.ver": "src/contrib/GeneGeneInteR_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GeneGeneInteR_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GeneGeneInteR_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GeneGeneInteR_1.0.0.tgz", "vignettes": [ "vignettes/GeneGeneInteR/inst/doc/GenePair.pdf", "vignettes/GeneGeneInteR/inst/doc/VignetteGeneGeneInteR_Introduction.pdf" ], "vignetteTitles": [ "Pairwise interaction tests", "GeneGeneInteR Introduction" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GeneGeneInteR/inst/doc/GenePair.R", "vignettes/GeneGeneInteR/inst/doc/VignetteGeneGeneInteR_Introduction.R" ] }, "GeneMeta": { "Package": "GeneMeta", "Version": "1.46.0", "Depends": [ "R (>= 2.10)", "methods", "Biobase (>= 2.5.5)", "genefilter" ], "Imports": [ "methods", "Biobase (>= 2.5.5)" ], "Suggests": [ "RColorBrewer" ], "License": "Artistic-2.0", "MD5sum": "5fb0add9baf68495202dbc728ce799c0", "NeedsCompilation": "no", "Title": "MetaAnalysis for High Throughput Experiments", "Description": "A collection of meta-analysis tools for analysing high throughput experimental data", "biocViews": [ "GeneExpression", "Microarray", "Sequencing", "Software" ], "Author": "Lara Lusa , R. Gentleman, M. Ruschhaupt", "Maintainer": "Bioconductor Package Maintainer ", "source.ver": "src/contrib/GeneMeta_1.46.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GeneMeta_1.46.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GeneMeta_1.46.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GeneMeta_1.46.0.tgz", "vignettes": [ "vignettes/GeneMeta/inst/doc/GeneMeta.pdf" ], "vignetteTitles": [ "GeneMeta Vignette" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GeneMeta/inst/doc/GeneMeta.R" ], "suggestsMe": [ "genefu", "XDE" ] }, "GeneNetworkBuilder": { "Package": "GeneNetworkBuilder", "Version": "1.16.0", "Depends": [ "R (>= 2.15.1)", "Rcpp (>= 0.9.13)" ], "Imports": [ "plyr", "graph" ], "LinkingTo": [ "Rcpp" ], "Suggests": [ "RUnit", "BiocGenerics", "Rgraphviz", "XML", "RCytoscape", "RBGL", "knitr" ], "License": "GPL (>= 2)", "MD5sum": "010715945e9bcbcbe6f5fe4507882754", "NeedsCompilation": "yes", "Title": "Build Regulatory Network from ChIP-chip/ChIP-seq and Expression Data", "Description": "Appliation for discovering direct or indirect targets of transcription factors using ChIP-chip or ChIP-seq, and microarray or RNA-seq gene expression data. Inputting a list of genes of potential targets of one TF from ChIP-chip or ChIP-seq, and the gene expression results, GeneNetworkBuilder generates a regulatory network of the TF.", "biocViews": [ "GraphAndNetwork", "Microarray", "Sequencing", "Software" ], "Author": "Jianhong Ou , Haibo Liu, Heidi A Tissenbaum and Lihua Julie Zhu", "Maintainer": "Jianhong Ou ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/GeneNetworkBuilder_1.16.0.tar.gz", "vignettes": [ "vignettes/GeneNetworkBuilder/inst/doc/GeneNetworkBuilder.pdf" ], "vignetteTitles": [ "GeneNetworkBuilder Vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GeneNetworkBuilder/inst/doc/GeneNetworkBuilder.R" ] }, "GeneOverlap": { "Package": "GeneOverlap", "Version": "1.10.0", "Imports": [ "stats", "RColorBrewer", "gplots", "methods" ], "Suggests": [ "RUnit", "BiocGenerics", "BiocStyle" ], "License": "GPL-3", "MD5sum": "c2a2f860a087a5328a98c4e699971424", "NeedsCompilation": "no", "Title": "Test and visualize gene overlaps", "Description": "Test two sets of gene lists and visualize the results.", "biocViews": [ "MultipleComparison", "Software", "Visualization" ], "Author": "Li Shen, Mount Sinai ", "Maintainer": "Li Shen, Mount Sinai ", "URL": "http://shenlab-sinai.github.io/shenlab-sinai/", "source.ver": "src/contrib/GeneOverlap_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GeneOverlap_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GeneOverlap_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GeneOverlap_1.10.0.tgz", "vignettes": [ "vignettes/GeneOverlap/inst/doc/GeneOverlap.pdf" ], "vignetteTitles": [ "Testing and visualizing gene overlaps with the \"GeneOverlap\" package" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GeneOverlap/inst/doc/GeneOverlap.R" ] }, "geneplast": { "Package": "geneplast", "Version": "1.0.0", "Depends": [ "R (>= 3.3)", "methods" ], "Imports": [ "snow", "ape", "grDevices", "graphics", "stats", "utils" ], "Suggests": [ "BiocStyle", "RUnit", "BiocGenerics" ], "License": "GPL (>= 2)", "MD5sum": "05f87dddd5213e0aa544e55c5d76afa0", "NeedsCompilation": "no", "Title": "Evolutionary and plasticity analysis based on orthologous groups distribution", "Description": "Geneplast is designed for evolutionary and plasticity analysis based on orthologous groups distribution in a given species tree. It uses Shannon information theory and orthologs abundance to estimate the Evolutionary Plasticity Index. Additionally, it implements the Bridge algorithm to determine the evolutionary root of a given gene based on its orthologs distribution.", "biocViews": [ "GeneRegulation", "Genetics", "Software", "SystemsBiology" ], "Author": "Rodrigo Dalmolin, Mauro Castro", "Maintainer": "Mauro Castro ", "source.ver": "src/contrib/geneplast_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/geneplast_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/geneplast_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/geneplast_1.0.0.tgz", "vignettes": [ "vignettes/geneplast/inst/doc/geneplast.pdf" ], "vignetteTitles": [ "Geneplast main vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/geneplast/inst/doc/geneplast.R" ] }, "geneplotter": { "Package": "geneplotter", "Version": "1.52.0", "Depends": [ "R (>= 2.10)", "methods", "Biobase", "BiocGenerics", "lattice", "annotate" ], "Imports": [ "AnnotationDbi", "graphics", "grDevices", "grid", "RColorBrewer", "stats", "utils" ], "Suggests": [ "Rgraphviz", "fibroEset", "hgu95av2.db", "hu6800.db", "hgu133a.db" ], "License": "Artistic-2.0", "MD5sum": "e59231f27b28e16b2bd7bbca79e44251", "NeedsCompilation": "no", "Title": "Graphics related functions for Bioconductor", "Description": "Functions for plotting genomic data", "biocViews": [ "Software", "Visualization" ], "Author": "R. Gentleman, Biocore", "Maintainer": "Bioconductor Package Maintainer ", "source.ver": "src/contrib/geneplotter_1.52.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/geneplotter_1.52.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/geneplotter_1.52.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/geneplotter_1.52.0.tgz", "vignettes": [ "vignettes/geneplotter/inst/doc/byChroms.pdf", "vignettes/geneplotter/inst/doc/visualize.pdf" ], "vignetteTitles": [ "How to assemble a chromLocation object", "Visualization of Microarray Data" ], "hasREADME": true, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/geneplotter/inst/doc/byChroms.R", "vignettes/geneplotter/inst/doc/visualize.R" ], "dependsOnMe": [ "HD2013SGI", "Hiiragi2013", "HMMcopy", "PGPC" ], "importsMe": [ "biocGraph", "DESeq", "DESeq2", "DEXSeq", "ENmix", "EnrichmentBrowser", "flowQ", "IsoGeneGUI", "JunctionSeq", "MethylSeekR", "RNAinteract", "RNAither" ], "suggestsMe": [ "AgiMicroRna", "BiocCaseStudies", "biocGraph", "Category", "chimera", "GOstats", "Single.mTEC.Transcriptomes" ] }, "geneRecommender": { "Package": "geneRecommender", "Version": "1.46.0", "Depends": [ "R (>= 1.8.0)", "Biobase (>= 1.4.22)", "methods" ], "Imports": [ "Biobase", "methods", "stats" ], "License": "GPL (>= 2)", "MD5sum": "6217fd1b2dc66683835035b01618dd06", "NeedsCompilation": "no", "Title": "A gene recommender algorithm to identify genes coexpressed with a query set of genes", "Description": "This package contains a targeted clustering algorithm for the analysis of microarray data. The algorithm can aid in the discovery of new genes with similar functions to a given list of genes already known to have closely related functions.", "biocViews": [ "Clustering", "Microarray", "Software" ], "Author": "Gregory J. Hather , with contributions from Art B. Owen and Terence P. Speed ", "Maintainer": "Greg Hather ", "source.ver": "src/contrib/geneRecommender_1.46.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/geneRecommender_1.46.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/geneRecommender_1.46.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/geneRecommender_1.46.0.tgz", "vignettes": [ "vignettes/geneRecommender/inst/doc/geneRecommender.pdf" ], "vignetteTitles": [ "Using the geneRecommender Package" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/geneRecommender/inst/doc/geneRecommender.R" ] }, "GeneRegionScan": { "Package": "GeneRegionScan", "Version": "1.30.0", "Depends": [ "methods", "Biobase (>= 2.5.5)", "Biostrings" ], "Imports": [ "S4Vectors (>= 0.9.25)", "Biobase (>= 2.5.5)", "affxparser", "RColorBrewer", "Biostrings" ], "Suggests": [ "BSgenome", "affy", "AnnotationDbi" ], "License": "GPL (>= 2)", "MD5sum": "69583c1ef58680956d2f8fbff8bc4ea3", "NeedsCompilation": "no", "Title": "GeneRegionScan", "Description": "A package with focus on analysis of discrete regions of the genome. This package is useful for investigation of one or a few genes using Affymetrix data, since it will extract probe level data using the Affymetrix Power Tools application and wrap these data into a ProbeLevelSet. A ProbeLevelSet directly extends the expressionSet, but includes additional information about the sequence of each probe and the probe set it is derived from. The package includes a number of functions used for plotting these probe level data as a function of location along sequences of mRNA-strands. This can be used for analysis of variable splicing, and is especially well suited for use with exon-array data.", "biocViews": [ "DataImport", "Microarray", "OneChannel", "SNP", "Software", "Visualization" ], "Author": "Lasse Folkersen, Diego Diez", "Maintainer": "Lasse Folkersen ", "source.ver": "src/contrib/GeneRegionScan_1.30.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GeneRegionScan_1.30.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GeneRegionScan_1.30.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GeneRegionScan_1.30.0.tgz", "vignettes": [ "vignettes/GeneRegionScan/inst/doc/GeneRegionScan.pdf" ], "vignetteTitles": [ "GeneRegionScan" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GeneRegionScan/inst/doc/GeneRegionScan.R" ] }, "geneRxCluster": { "Package": "geneRxCluster", "Version": "1.10.0", "Depends": [ "GenomicRanges", "IRanges" ], "Suggests": [ "RUnit", "BiocGenerics" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "2acd25338bf9efacfdb2098f23026480", "NeedsCompilation": "yes", "Title": "gRx Differential Clustering", "Description": "Detect Differential Clustering of Genomic Sites such as gene therapy integrations. The package provides some functions for exploring genomic insertion sites originating from two different sources. Possibly, the two sources are two different gene therapy vectors. Vectors are preferred that target sensitive regions less frequently, motivating the search for localized clusters of insertions and comparison of the clusters formed by integration of different vectors. Scan statistics allow the discovery of spatial differences in clustering and calculation of False Discovery Rates (FDRs) providing statistical methods for comparing retroviral vectors. A scan statistic for comparing two vectors using multiple window widths to detect clustering differentials and compute FDRs is implemented here.", "biocViews": [ "Clustering", "Genetics", "Sequencing", "Software" ], "Author": "Charles Berry", "Maintainer": "Charles Berry ", "source.ver": "src/contrib/geneRxCluster_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/geneRxCluster_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/geneRxCluster_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/geneRxCluster_1.10.0.tgz", "vignettes": [ "vignettes/geneRxCluster/inst/doc/tutorial.pdf" ], "vignetteTitles": [ "Using geneRxCluster" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/geneRxCluster/inst/doc/tutorial.R" ] }, "GeneSelectMMD": { "Package": "GeneSelectMMD", "Version": "2.18.0", "Depends": [ "R (>= 2.13.2)", "Biobase" ], "Imports": [ "Biobase", "MASS", "graphics", "stats", "survival", "limma" ], "Suggests": [ "ALL" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "3c11e0a539e9d0d0c158fea49fa3ae53", "NeedsCompilation": "yes", "Title": "Gene selection based on the marginal distributions of gene profiles that characterized by a mixture of three-component multivariate distributions", "Description": "Gene selection based on a mixture of marginal distributions", "biocViews": [ "DifferentialExpression", "Software" ], "Author": "Jarrett Morrow , Weiliang Qiu , Wenqing He , Xiaogang Wang , Ross Lazarus .", "Maintainer": "Weiliang Qiu ", "source.ver": "src/contrib/GeneSelectMMD_2.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GeneSelectMMD_2.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GeneSelectMMD_2.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GeneSelectMMD_2.18.0.tgz", "vignettes": [ "vignettes/GeneSelectMMD/inst/doc/gsMMD.pdf" ], "vignetteTitles": [ "Gene Selection based on a mixture of marginal distributions" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GeneSelectMMD/inst/doc/gsMMD.R" ], "importsMe": [ "iCheck" ] }, "GeneSelector": { "Package": "GeneSelector", "Version": "2.24.0", "Depends": [ "R (>= 2.5.1)", "methods", "stats", "Biobase" ], "Imports": [ "multtest", "siggenes", "samr", "limma" ], "Suggests": [ "multtest", "siggenes", "samr", "limma" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "ea9e1a0c2485dc4b682e53f43ff4710f", "NeedsCompilation": "yes", "Title": "Stability and Aggregation of ranked gene lists", "Description": "The term 'GeneSelector' refers to a filter selecting those genes which are consistently identified as differentially expressed using various statistical procedures. 'Selected' genes are those present at the top of the list in various ranking methods (currently 14). In addition, the stability of the findings can be taken into account in the final ranking by examining perturbed versions of the original data set, e.g. by leaving samples, swapping class labels, generating bootstrap replicates or adding noise. Given multiple ranked lists, one can use aggregation methods in order to find a synthesis.", "biocViews": [ "DifferentialExpression", "Software", "StatisticalMethod" ], "Author": "Martin Slawski , Anne-Laure Boulesteix .", "Maintainer": "Martin Slawski ", "source.ver": "src/contrib/GeneSelector_2.24.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GeneSelector_2.24.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GeneSelector_2.24.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GeneSelector_2.24.0.tgz", "vignettes": [ "vignettes/GeneSelector/inst/doc/GeneSelector.pdf" ], "vignetteTitles": [ "GeneSelector.pdf" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GeneSelector/inst/doc/GeneSelector.R" ] }, "GENESIS": { "Package": "GENESIS", "Version": "2.4.0", "Imports": [ "GWASTools", "SeqArray", "SeqVarTools", "Biobase", "gdsfmt", "graph", "grDevices", "graphics", "stats", "utils" ], "Suggests": [ "SNPRelate", "logistf", "survey", "CompQuadForm", "RUnit", "BiocGenerics", "knitr" ], "License": "GPL-3", "MD5sum": "ebb93ea22487353f9470ce5c99f9a843", "NeedsCompilation": "no", "Title": "GENetic EStimation and Inference in Structured samples (GENESIS): Statistical methods for analyzing genetic data from samples with population structure and/or relatedness", "Description": "The GENESIS package provides methodology for estimating, inferring, and accounting for population and pedigree structure in genetic analyses. The current implementation provides functions to perform PC-AiR (Conomos et al., 2015, Gen Epi) and PC-Relate (Conomos et al., 2016, AJHG). PC-AiR performs a Principal Components Analysis on genome-wide SNP data for the detection of population structure in a sample that may contain known or cryptic relatedness. Unlike standard PCA, PC-AiR accounts for relatedness in the sample to provide accurate ancestry inference that is not confounded by family structure. PC-Relate uses ancestry representative principal components to adjust for population structure/ancestry and accurately estimate measures of recent genetic relatedness such as kinship coefficients, IBD sharing probabilities, and inbreeding coefficients. Additionally, functions are provided to perform efficient variance component estimation and mixed model association testing for both quantitative and binary phenotypes.", "biocViews": [ "BiocViews", "DimensionReduction", "GeneticVariability", "Genetics", "GenomeWideAssociation", "PrincipalComponent", "QualityControl", "SNP", "Software", "StatisticalMethod" ], "Author": "Matthew P. Conomos and Timothy Thornton", "Maintainer": "Matthew P. Conomos ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/GENESIS_2.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GENESIS_2.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GENESIS_2.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GENESIS_2.4.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GENESIS/inst/doc/assoc_test.R", "vignettes/GENESIS/inst/doc/pcair.R" ], "htmlDocs": [ "vignettes/GENESIS/inst/doc/assoc_test.html", "vignettes/GENESIS/inst/doc/pcair.html" ], "htmlTitles": [ "Genetic Association Testing using the GENESIS Package", "Population Structure and Relatedness Inference using the GENESIS Package" ] }, "geNetClassifier": { "Package": "geNetClassifier", "Version": "1.14.0", "Depends": [ "R (>= 2.10.1)", "Biobase (>= 2.5.5)", "EBarrays", "minet", "methods" ], "Imports": [ "e1071", "graphics" ], "Suggests": [ "leukemiasEset", "RUnit", "BiocGenerics" ], "Enhances": [ "RColorBrewer", "igraph", "infotheo" ], "License": "GPL (>= 2)", "MD5sum": "b51eae76057668b5903b89ace6d20e3e", "NeedsCompilation": "no", "Title": "Classify diseases and build associated gene networks using gene expression profiles", "Description": "Comprehensive package to automatically train and validate a multi-class SVM classifier based on gene expression data. Provides transparent selection of gene markers, their coexpression networks, and an interface to query the classifier.", "biocViews": [ "Classification", "DifferentialExpression", "Microarray", "Software" ], "Author": "Sara Aibar, Celia Fontanillo and Javier De Las Rivas. Bioinformatics and Functional Genomics Group. Cancer Research Center (CiC-IBMCC, CSIC/USAL). Salamanca. Spain.", "Maintainer": "Sara Aibar ", "URL": "http://www.cicancer.org", "source.ver": "src/contrib/geNetClassifier_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/geNetClassifier_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/geNetClassifier_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/geNetClassifier_1.14.0.tgz", "vignettes": [ "vignettes/geNetClassifier/inst/doc/geNetClassifier-vignette.pdf" ], "vignetteTitles": [ "geNetClassifier-vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/geNetClassifier/inst/doc/geNetClassifier-vignette.R" ], "importsMe": [ "bioCancer", "canceR" ] }, "GeneticsDesign": { "Package": "GeneticsDesign", "Version": "1.42.0", "Imports": [ "gmodels", "graphics", "gtools (>= 2.4.0)", "mvtnorm", "stats" ], "License": "GPL-2", "MD5sum": "daf518f823a525929b7455e034bfa94a", "NeedsCompilation": "no", "Title": "Functions for designing genetics studies", "Description": "This package contains functions useful for designing genetics studies, including power and sample-size calculations.", "biocViews": [ "Genetics", "Software" ], "Author": "Gregory Warnes David Duffy , Michael Man Weiliang Qiu Ross Lazarus ", "Maintainer": "The R Genetics Project ", "source.ver": "src/contrib/GeneticsDesign_1.42.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GeneticsDesign_1.42.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GeneticsDesign_1.42.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GeneticsDesign_1.42.0.tgz", "vignettes": [ "vignettes/GeneticsDesign/inst/doc/GPC.pdf" ], "vignetteTitles": [ "Power Calculation for Testing If Disease is Associated a Marker in a Case-Control Study Using the \\Rpackage{GeneticsDesign} Package" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GeneticsDesign/inst/doc/GPC.R" ] }, "GeneticsPed": { "Package": "GeneticsPed", "Version": "1.36.0", "Depends": [ "R (>= 2.4.0)", "MASS" ], "Imports": [ "gdata", "genetics" ], "Suggests": [ "RUnit", "gtools" ], "License": "LGPL (>= 2.1) | file LICENSE", "Archs": "i386, x64", "MD5sum": "f62998bb6a3a4c890727e60d223ab683", "NeedsCompilation": "yes", "Title": "Pedigree and genetic relationship functions", "Description": "Classes and methods for handling pedigree data. It also includes functions to calculate genetic relationship measures as relationship and inbreeding coefficients and other utilities. Note that package is not yet stable. Use it with care!", "biocViews": [ "Genetics", "Software" ], "Author": "Gregor Gorjanc and David A. Henderson , with code contributions by Brian Kinghorn and Andrew Percy (see file COPYING)", "Maintainer": "David Henderson ", "URL": "http://rgenetics.org", "source.ver": "src/contrib/GeneticsPed_1.36.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GeneticsPed_1.36.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GeneticsPed_1.36.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GeneticsPed_1.36.0.tgz", "vignettes": [ "vignettes/GeneticsPed/inst/doc/geneticRelatedness.pdf", "vignettes/GeneticsPed/inst/doc/pedigreeHandling.pdf", "vignettes/GeneticsPed/inst/doc/quanGenAnimalModel.pdf" ], "vignetteTitles": [ "Calculation of genetic relatedness/relationship between individuals in the pedigree", "Pedigree handling", "Quantitative genetic (animal) model example in R" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/GeneticsPed/inst/doc/geneticRelatedness.R", "vignettes/GeneticsPed/inst/doc/pedigreeHandling.R", "vignettes/GeneticsPed/inst/doc/quanGenAnimalModel.R" ] }, "geneXtendeR": { "Package": "geneXtendeR", "Version": "1.0.0", "Depends": [ "rtracklayer", "R (>= 3.3.1)" ], "Imports": [ "data.table", "dplyr", "graphics", "utils" ], "Suggests": [ "BiocStyle", "knitr", "rmarkdown" ], "License": "GPL (>= 3)", "Archs": "i386, x64", "MD5sum": "6e50a4302bdfec86597a67a2feb95182", "NeedsCompilation": "yes", "Title": "Optimal Gene Extensions From Histone Modification ChIP-seq Data", "Description": "geneXtendeR is designed to optimally annotate a histone modification ChIP-seq peak input file with functionally important genomic features (e.g., genes associated with peaks) based on optimization calculations. geneXtendeR optimally extends the boundaries of every gene in a genome by some genomic distance (in DNA base pairs) for the purpose of flexibly incorporating cis-regulatory elements (CREs), such as enhancers and promoters, as well as downstream elements that are important to the function of the gene relative to an epigenetic histone modification ChIP-seq dataset. geneXtender computes optimal gene extensions tailored to the broadness of the specific epigenetic mark (e.g., H3K9me1, H3K27me3), as determined by a user-supplied ChIP-seq peak input file. As such, geneXtender maximizes the signal-to-noise ratio of locating genes closest to and directly under peaks. By performing a computational expansion of this nature, ChIP-seq reads that would initially not map strictly to a specific gene can now be optimally mapped to the regulatory regions of the gene, thereby implicating the gene as a potential candidate, and thereby making the ChIP-seq experiment more successful. Such an approach becomes particularly important when working with epigenetic histone modifications that have inherently broad peaks.", "biocViews": [ "Annotation", "ChIPSeq", "ChipOnChip", "Coverage", "DataImport", "DifferentialPeakCalling", "Genetics", "GenomeAnnotation", "HistoneModification", "PeakDetection", "Software" ], "Author": "Bohdan Khomtchouk [aut, cre]", "Maintainer": "Bohdan Khomtchouk ", "URL": "https://github.com/Bohdan-Khomtchouk/geneXtendeR", "VignetteBuilder": "knitr", "BugReports": "https://github.com/Bohdan-Khomtchouk/geneXtendeR/issues", "source.ver": "src/contrib/geneXtendeR_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/geneXtendeR_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/geneXtendeR_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/geneXtendeR_1.0.0.tgz", "vignettes": [ "vignettes/geneXtendeR/inst/doc/geneXtendeR.pdf" ], "vignetteTitles": [ "geneXtendeR Vignette" ], "hasREADME": true, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/geneXtendeR/inst/doc/geneXtendeR.R" ] }, "genoCN": { "Package": "genoCN", "Version": "1.26.0", "Imports": [ "graphics", "stats", "utils" ], "License": "GPL (>=2)", "Archs": "i386, x64", "MD5sum": "d32c8dbe85e93e334c1b537a585f00db", "NeedsCompilation": "yes", "Title": "genotyping and copy number study tools", "Description": "Simultaneous identification of copy number states and genotype calls for regions of either copy number variations or copy number aberrations", "biocViews": [ "Genetics", "Microarray", "Software" ], "Author": "Wei Sun and ZhengZheng Tang", "Maintainer": "Wei Sun ", "source.ver": "src/contrib/genoCN_1.26.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/genoCN_1.26.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/genoCN_1.26.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/genoCN_1.26.0.tgz", "vignettes": [ "vignettes/genoCN/inst/doc/genoCN.pdf" ], "vignetteTitles": [ "add stuff" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/genoCN/inst/doc/genoCN.R" ] }, "GenoGAM": { "Package": "GenoGAM", "Version": "1.2.1", "Depends": [ "R (>= 3.3)", "Rsamtools (>= 1.18.2)", "SummarizedExperiment (>= 1.1.19)", "GenomicRanges (>= 1.23.16)", "methods" ], "Imports": [ "BiocParallel (>= 1.5.17)", "data.table (>= 1.9.4)", "DESeq2 (>= 1.11.23)", "futile.logger (>= 1.4.1)", "GenomeInfoDb (>= 1.7.6)", "GenomicAlignments (>= 1.7.17)", "IRanges (>= 2.5.30)", "mgcv (>= 1.8)", "reshape2 (>= 1.4.1)", "S4Vectors (>= 0.9.34)", "Biostrings (>= 2.39.14)" ], "Suggests": [ "BiocStyle", "chipseq (>= 1.21.2)", "LSD (>= 3.0.0)", "genefilter (>= 1.54.2)", "ggplot2 (>= 2.1.0)", "testthat", "knitr" ], "License": "GPL-2", "MD5sum": "fb22833fa452c241050e5eb78692ed36", "NeedsCompilation": "no", "Title": "A GAM based framework for analysis of ChIP-Seq data", "Description": "This package allows statistical analysis of genome-wide data with smooth functions using generalized additive models based on the implementation from the R-package 'mgcv'. It provides methods for the statistical analysis of ChIP-Seq data including inference of protein occupancy, and pointwise and region-wise differential analysis. Estimation of dispersion and smoothing parameters is performed by cross-validation. Scaling of generalized additive model fitting to whole chromosomes is achieved by parallelization over overlapping genomic intervals.", "biocViews": [ "ChIPSeq", "DifferentialExpression", "DifferentialPeakCalling", "Epigenetics", "Genetics", "Regression", "Software" ], "Author": "Georg Stricker [aut, cre], Alexander Engelhardt [aut], Julien Gagneur [aut]", "Maintainer": "Georg Stricker ", "URL": "https://github.com/gstricker/GenoGAM", "VignetteBuilder": "knitr", "BugReports": "https://github.com/gstricker/GenoGAM/issues", "source.ver": "src/contrib/GenoGAM_1.2.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GenoGAM_1.2.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GenoGAM_1.2.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GenoGAM_1.2.1.tgz", "vignettes": [ "vignettes/GenoGAM/inst/doc/GenoGAM.pdf" ], "vignetteTitles": [ "GenoGAM: Genome-wide generalized additive models" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GenoGAM/inst/doc/GenoGAM.R" ] }, "genomation": { "Package": "genomation", "Version": "1.6.0", "Depends": [ "R (>= 3.0.0)", "grid" ], "Imports": [ "Biostrings", "BSgenome", "data.table", "GenomeInfoDb", "GenomicRanges (>= 1.23.26)", "GenomicAlignments", "S4Vectors (>= 0.9.25)", "ggplot2", "gridBase", "impute", "IRanges", "matrixStats", "methods", "parallel", "plotrix", "plyr", "readr", "reshape2", "Rsamtools", "seqPattern", "rtracklayer", "Rcpp", "RUnit" ], "LinkingTo": [ "Rcpp", "Rhtslib" ], "Suggests": [ "BiocGenerics", "genomationData", "knitr", "knitrBootstrap", "RColorBrewer", "rmarkdown" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "ceb645ad51f99c5b9ef09491c942d06a", "NeedsCompilation": "yes", "Title": "Summary, annotation and visualization of genomic data", "Description": "A package for summary and annotation of genomic intervals. Users can visualize and quantify genomic intervals over pre-defined functional regions, such as promoters, exons, introns, etc. The genomic intervals represent regions with a defined chromosome position, which may be associated with a score, such as aligned reads from HT-seq experiments, TF binding sites, methylation scores, etc. The package can use any tabular genomic feature data as long as it has minimal information on the locations of genomic intervals. In addition, It can use BAM or BigWig files as input.", "biocViews": [ "Annotation", "CpGIsland", "Sequencing", "Software", "Visualization" ], "Author": "Altuna Akalin [aut, cre], Vedran Franke [aut, cre], Katarzyna Wreczycka [aut], Alexander Gosdschan [ctb], Liz Ing-Simmons [ctb]", "Maintainer": "Altuna Akalin , Vedran Franke ", "URL": "http://bioinformatics.mdc-berlin.de/genomation/", "VignetteBuilder": "knitr", "BugReports": "https://github.com/BIMSBbioinfo/genomation/issues", "source.ver": "src/contrib/genomation_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/genomation_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/genomation_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/genomation_1.6.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/genomation/inst/doc/GenomationManual.R" ], "htmlDocs": [ "vignettes/genomation/inst/doc/GenomationManual.html" ], "htmlTitles": [ "genomation" ], "importsMe": [ "CexoR", "fCCAC", "RCAS" ], "suggestsMe": [ "methylKit" ] }, "GenomeGraphs": { "Package": "GenomeGraphs", "Version": "1.34.0", "Depends": [ "R (>= 2.10)", "methods", "biomaRt", "grid" ], "License": "Artistic-2.0", "MD5sum": "630ed529e9d3d2159a21db50352cb233", "NeedsCompilation": "no", "Title": "Plotting genomic information from Ensembl", "Description": "Genomic data analyses requires integrated visualization of known genomic information and new experimental data. GenomeGraphs uses the biomaRt package to perform live annotation queries to Ensembl and translates this to e.g. gene/transcript structures in viewports of the grid graphics package. This results in genomic information plotted together with your data. Another strength of GenomeGraphs is to plot different data types such as array CGH, gene expression, sequencing and other data, together in one plot using the same genome coordinate system.", "biocViews": [ "Microarray", "Software", "Visualization" ], "Author": "Steffen Durinck , James Bullard ", "Maintainer": "Steffen Durinck ", "source.ver": "src/contrib/GenomeGraphs_1.34.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GenomeGraphs_1.34.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GenomeGraphs_1.34.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GenomeGraphs_1.34.0.tgz", "vignettes": [ "vignettes/GenomeGraphs/inst/doc/GenomeGraphs.pdf" ], "vignetteTitles": [ "The GenomeGraphs users guide" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GenomeGraphs/inst/doc/GenomeGraphs.R" ], "dependsOnMe": [ "Genominator", "waveTiling" ], "suggestsMe": [ "leeBamViews", "oligo", "oligo", "oneChannelGUI", "rMAT", "triplex" ] }, "GenomeInfoDb": { "Package": "GenomeInfoDb", "Version": "1.10.3", "Depends": [ "R (>= 3.1)", "methods", "BiocGenerics (>= 0.13.8)", "S4Vectors (>= 0.9.25)", "IRanges (>= 1.99.26)" ], "Imports": [ "stats", "stats4", "utils", "RCurl" ], "Suggests": [ "GenomicRanges", "Rsamtools", "GenomicAlignments", "BSgenome", "GenomicFeatures", "BSgenome.Scerevisiae.UCSC.sacCer2", "BSgenome.Celegans.UCSC.ce2", "BSgenome.Hsapiens.NCBI.GRCh38", "TxDb.Dmelanogaster.UCSC.dm3.ensGene", "RUnit", "BiocStyle", "knitr" ], "License": "Artistic-2.0", "MD5sum": "88376d3b96da905887491c9b6ef28339", "NeedsCompilation": "no", "Title": "Utilities for manipulating chromosome and other 'seqname' identifiers", "Description": "Contains data and functions that define and allow translation between different chromosome sequence naming conventions (e.g., \"chr1\" versus \"1\"), including a function that attempts to place sequence names in their natural, rather than lexicographic, order.", "biocViews": [ "Annotation", "DataRepresentation", "Genetics", "GenomeAnnotation", "Software" ], "Author": "Sonali Arora, Martin Morgan, Marc Carlson, H. Pagès", "Maintainer": "Bioconductor Package Maintainer ", "VignetteBuilder": "knitr", "Video": "http://youtu.be/wdEjCYSXa7w", "source.ver": "src/contrib/GenomeInfoDb_1.10.3.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GenomeInfoDb_1.10.3.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GenomeInfoDb_1.10.3.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GenomeInfoDb_1.10.3.tgz", "vignettes": [ "vignettes/GenomeInfoDb/inst/doc/Accept-organism-for-GenomeInfoDb.pdf", "vignettes/GenomeInfoDb/inst/doc/GenomeInfoDb.pdf" ], "vignetteTitles": [ "GenomeInfoDb: Submitting your organism to GenomeInfoDb", "GenomeInfoDb: Introduction to GenomeInfoDb" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GenomeInfoDb/inst/doc/Accept-organism-for-GenomeInfoDb.R", "vignettes/GenomeInfoDb/inst/doc/GenomeInfoDb.R" ], "dependsOnMe": [ "BSgenome", "bumphunter", "ChIPComp", "CODEX", "CSAR", "GenomicAlignments", "GenomicFeatures", "GenomicRanges", "GenomicTuples", "gmapR", "groHMM", "HelloRanges", "htSeqTools", "IdeoViz", "methyAnalysis", "Rsamtools", "SNPlocs.Hsapiens.dbSNP142.GRCh37", "TitanCNA", "VariantAnnotation", "XtraSNPlocs.Hsapiens.dbSNP141.GRCh38" ], "importsMe": [ "AllelicImbalance", "alpine", "AneuFinder", "AnnotationHubData", "annotatr", "BaalChIP", "ballgown", "BasicSTARRseq", "biovizBase", "BiSeq", "BSgenome", "bsseq", "casper", "CexoR", "chipenrich", "ChIPpeakAnno", "ChIPseeker", "chromstaR", "CINdex", "cn.mops", "CNEr", "CNPBayes", "compEpiTools", "consensusSeekeR", "conumee", "CopywriteR", "CrispRVariants", "csaw", "customProDB", "DeepBlueR", "derfinder", "derfinderPlot", "diffHic", "diffloop", "easyRNASeq", "ELMER", "ensembldb", "ensemblVEP", "epigenomix", "epivizrData", "epivizrStandalone", "exomeCopy", "FunChIP", "genbankr", "geneAttribution", "GenoGAM", "genomation", "genomeIntervals", "GenomicFiles", "GenomicInteractions", "genoset", "genotypeeval", "ggbio", "GGtools", "GoogleGenomics", "gQTLstats", "grasp2db", "GreyListChIP", "GUIDEseq", "Gviz", "gwascat", "h5vc", "HiTC", "HTSeqGenie", "InPAS", "InteractionSet", "IVAS", "MADSEQ", "metagene", "methylKit", "methylPipe", "methylumi", "minfi", "MinimumDistance", "mosaics", "motifbreakR", "MutationalPatterns", "myvariant", "NarrowPeaks", "normr", "Pi", "podkat", "prebs", "ProteomicsAnnotationHubData", "PureCN", "qpgraph", "qsea", "QuasR", "R3CPET", "r3Cseq", "RareVariantVis", "Rariant", "Rcade", "RCAS", "rCGH", "recount", "regioneR", "regionReport", "Repitools", "RiboProfiling", "riboSeqR", "roar", "rtracklayer", "segmentSeq", "SeqArray", "seqplots", "SGSeq", "ShortRead", "SNPchip", "SNPhood", "SNPlocs.Hsapiens.dbSNP142.GRCh37", "SNPlocs.Hsapiens.dbSNP144.GRCh37", "SNPlocs.Hsapiens.dbSNP144.GRCh38", "soGGi", "SomaticSignatures", "SplicingGraphs", "SPLINTER", "STAN", "SummarizedExperiment", "TarSeqQC", "TFBSTools", "transcriptR", "TVTB", "VanillaICE", "VariantFiltering", "VariantTools", "XtraSNPlocs.Hsapiens.dbSNP141.GRCh38", "XtraSNPlocs.Hsapiens.dbSNP144.GRCh37", "XtraSNPlocs.Hsapiens.dbSNP144.GRCh38", "YAPSA" ], "suggestsMe": [ "AnnotationForge", "AnnotationHub", "ExperimentHubData", "gQTLBase", "QDNAseq", "recoup" ] }, "genomeIntervals": { "Package": "genomeIntervals", "Version": "1.30.1", "Depends": [ "R (>= 2.15.0)", "methods", "intervals (>= 0.14.0)", "BiocGenerics (>= 0.15.2)" ], "Imports": [ "GenomeInfoDb (>= 1.5.8)", "GenomicRanges (>= 1.21.16)", "IRanges(>= 2.3.14)", "S4Vectors (>= 0.7.10)" ], "License": "Artistic-2.0", "MD5sum": "8f8b3c02b89d243d34128d5cab4b3795", "NeedsCompilation": "no", "Title": "Operations on genomic intervals", "Description": "This package defines classes for representing genomic intervals and provides functions and methods for working with these. Note: The package provides the basic infrastructure for and is enhanced by the package 'girafe'.", "biocViews": [ "DataImport", "Genetics", "Infrastructure", "Software" ], "Author": "Julien Gagneur , Joern Toedling, Richard Bourgon, Nicolas Delhomme", "Maintainer": "Julien Gagneur ", "source.ver": "src/contrib/genomeIntervals_1.30.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/genomeIntervals_1.30.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/genomeIntervals_1.30.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/genomeIntervals_1.30.1.tgz", "vignettes": [ "vignettes/genomeIntervals/inst/doc/genomeIntervals.pdf" ], "vignetteTitles": [ "Overview of the genomeIntervals package." ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/genomeIntervals/inst/doc/genomeIntervals.R" ], "dependsOnMe": [ "girafe" ], "importsMe": [ "easyRNASeq" ], "suggestsMe": [ "RnaSeqTutorial" ] }, "genomes": { "Package": "genomes", "Version": "3.4.0", "Depends": [ "readr", "curl" ], "License": "GPL-3", "MD5sum": "16a7ab73705d538e885c756258b750c7", "NeedsCompilation": "no", "Title": "Genome sequencing project metadata", "Description": "Download genome and assembly reports from NCBI", "biocViews": [ "Annotation", "Genetics", "Software" ], "Author": "Chris Stubben", "Maintainer": "Chris Stubben ", "source.ver": "src/contrib/genomes_3.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/genomes_3.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/genomes_3.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/genomes_3.4.0.tgz", "vignettes": [ "vignettes/genomes/inst/doc/genomes.pdf" ], "vignetteTitles": [ "Genome metadata" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/genomes/inst/doc/genomes.R" ] }, "GenomicAlignments": { "Package": "GenomicAlignments", "Version": "1.10.1", "Depends": [ "R (>= 2.10)", "methods", "BiocGenerics (>= 0.15.3)", "S4Vectors (>= 0.9.40)", "IRanges (>= 2.5.36)", "GenomeInfoDb (>= 1.1.20)", "GenomicRanges (>= 1.25.6)", "SummarizedExperiment (>= 0.3.1)", "Biostrings (>= 2.37.1)", "Rsamtools (>= 1.21.4)" ], "Imports": [ "methods", "utils", "stats", "BiocGenerics", "S4Vectors", "IRanges", "GenomicRanges", "Biostrings", "Rsamtools", "BiocParallel" ], "LinkingTo": [ "S4Vectors", "IRanges" ], "Suggests": [ "ShortRead", "rtracklayer", "BSgenome", "GenomicFeatures", "RNAseqData.HNRNPC.bam.chr14", "pasillaBamSubset", "TxDb.Hsapiens.UCSC.hg19.knownGene", "TxDb.Dmelanogaster.UCSC.dm3.ensGene", "BSgenome.Dmelanogaster.UCSC.dm3", "BSgenome.Hsapiens.UCSC.hg19", "DESeq2", "edgeR", "RUnit", "BiocStyle" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "a05adb11949aa2b15fbac07597bd35ec", "NeedsCompilation": "yes", "Title": "Representation and manipulation of short genomic alignments", "Description": "Provides efficient containers for storing and manipulating short genomic alignments (typically obtained by aligning short reads to a reference genome). This includes read counting, computing the coverage, junction detection, and working with the nucleotide content of the alignments.", "biocViews": [ "Alignment", "Coverage", "DataImport", "Genetics", "Infrastructure", "RNASeq", "SNP", "Sequencing", "Software" ], "Author": "Hervé Pagès, Valerie Obenchain, Martin Morgan", "Maintainer": "Bioconductor Package Maintainer ", "Video": "https://www.youtube.com/watch?v=2KqBSbkfhRo , https://www.youtube.com/watch?v=3PK_jx44QTs", "source.ver": "src/contrib/GenomicAlignments_1.10.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GenomicAlignments_1.10.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GenomicAlignments_1.10.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GenomicAlignments_1.10.1.tgz", "vignettes": [ "vignettes/GenomicAlignments/inst/doc/GenomicAlignmentsIntroduction.pdf", "vignettes/GenomicAlignments/inst/doc/OverlapEncodings.pdf", "vignettes/GenomicAlignments/inst/doc/summarizeOverlaps.pdf", "vignettes/GenomicAlignments/inst/doc/WorkingWithAlignedNucleotides.pdf" ], "vignetteTitles": [ "An Introduction to the GenomicAlignments Package", "Overlap encodings", "Counting reads with summarizeOverlaps", "Working with aligned nucleotides" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GenomicAlignments/inst/doc/GenomicAlignmentsIntroduction.R", "vignettes/GenomicAlignments/inst/doc/OverlapEncodings.R", "vignettes/GenomicAlignments/inst/doc/summarizeOverlaps.R", "vignettes/GenomicAlignments/inst/doc/WorkingWithAlignedNucleotides.R" ], "dependsOnMe": [ "AllelicImbalance", "ASpli", "Basic4Cseq", "BasicSTARRseq", "chimera", "exomePeak", "GoogleGenomics", "groHMM", "Guitar", "HelloRanges", "hiReadsProcessor", "prebs", "recoup", "RIPSeeker", "rnaSeqMap", "ShortRead", "SplicingGraphs" ], "importsMe": [ "alpine", "AneuFinder", "BaalChIP", "biovizBase", "ChIPpeakAnno", "ChIPQC", "chromstaR", "CNEr", "contiBAIT", "CopywriteR", "CoverageView", "CrispRVariants", "customProDB", "derfinder", "DiffBind", "easyRNASeq", "FourCSeq", "FunChIP", "GenoGAM", "genomation", "GenomicFiles", "ggbio", "gmapR", "GreyListChIP", "GUIDEseq", "Gviz", "HTSeqGenie", "INSPEcT", "leeBamViews", "MADSEQ", "metagene", "methylPipe", "mosaics", "PICS", "QuasR", "Rcade", "Repitools", "RiboProfiling", "RNAprobR", "roar", "Rqc", "rtracklayer", "SGSeq", "similaRpeak", "soGGi", "SplicingGraphs", "SPLINTER", "TarSeqQC", "trackViewer", "transcriptR" ], "suggestsMe": [ "alpineData", "BiocParallel", "gage", "GenomeInfoDb", "GenomicFeatures", "GenomicRanges", "IRanges", "oneChannelGUI", "parathyroidSE", "RNAseqData.HNRNPC.bam.chr14", "RnaSeqTutorial", "Rsamtools", "Streamer" ] }, "GenomicFeatures": { "Package": "GenomicFeatures", "Version": "1.26.4", "Depends": [ "BiocGenerics (>= 0.1.0)", "S4Vectors (>= 0.9.47)", "IRanges (>= 2.3.21)", "GenomeInfoDb (>= 1.5.16)", "GenomicRanges (>= 1.21.32)", "AnnotationDbi (>= 1.33.15)" ], "Imports": [ "methods", "utils", "stats", "tools", "DBI", "RSQLite", "RCurl", "XVector", "Biostrings (>= 2.23.3)", "rtracklayer (>= 1.29.24)", "biomaRt (>= 2.17.1)", "Biobase (>= 2.15.1)" ], "Suggests": [ "org.Mm.eg.db", "org.Hs.eg.db", "BSgenome", "BSgenome.Hsapiens.UCSC.hg19 (>= 1.3.17)", "BSgenome.Celegans.UCSC.ce2", "BSgenome.Dmelanogaster.UCSC.dm3 (>= 1.3.17)", "mirbase.db", "FDb.UCSC.tRNAs", "TxDb.Hsapiens.UCSC.hg19.knownGene", "TxDb.Dmelanogaster.UCSC.dm3.ensGene (>= 2.7.1)", "TxDb.Mmusculus.UCSC.mm10.knownGene", "TxDb.Hsapiens.UCSC.hg19.lincRNAsTranscripts", "TxDb.Hsapiens.UCSC.hg38.knownGene", "SNPlocs.Hsapiens.dbSNP141.GRCh38", "Rsamtools", "pasillaBamSubset (>= 0.0.5)", "GenomicAlignments", "RUnit", "BiocStyle", "knitr" ], "License": "Artistic-2.0", "MD5sum": "275a00ad50b7a5ec5ca5389b136491ca", "NeedsCompilation": "no", "Title": "Tools for making and manipulating transcript centric annotations", "Description": "A set of tools and methods for making and manipulating transcript centric annotations. With these tools the user can easily download the genomic locations of the transcripts, exons and cds of a given organism, from either the UCSC Genome Browser or a BioMart database (more sources will be supported in the future). This information is then stored in a local database that keeps track of the relationship between transcripts, exons, cds and genes. Flexible methods are provided for extracting the desired features in a convenient format.", "biocViews": [ "Annotation", "Genetics", "GenomeAnnotation", "Infrastructure", "Sequencing", "Software" ], "Author": "M. Carlson, H. Pagès, P. Aboyoun, S. Falcon, M. Morgan, D. Sarkar, M. Lawrence", "Maintainer": "Bioconductor Package Maintainer ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/GenomicFeatures_1.26.4.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GenomicFeatures_1.26.4.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GenomicFeatures_1.26.4.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GenomicFeatures_1.26.4.tgz", "vignettes": [ "vignettes/GenomicFeatures/inst/doc/GenomicFeatures.pdf" ], "vignetteTitles": [ "Making and Utilizing TxDb Objects" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GenomicFeatures/inst/doc/GenomicFeatures.R" ], "dependsOnMe": [ "ASpli", "cpvSNP", "ensembldb", "exomePeak", "FDb.FANTOM4.promoters.hg19", "FDb.InfiniumMethylation.hg18", "FDb.InfiniumMethylation.hg19", "FDb.UCSC.snp135common.hg19", "FDb.UCSC.snp137common.hg19", "FDb.UCSC.tRNAs", "Guitar", "HelloRanges", "Homo.sapiens", "InPAS", "IVAS", "Mus.musculus", "mygene", "OrganismDbi", "Rattus.norvegicus", "RNAprobR", "SplicingGraphs", "TxDb.Athaliana.BioMart.plantsmart22", "TxDb.Athaliana.BioMart.plantsmart25", "TxDb.Athaliana.BioMart.plantsmart28", "TxDb.Btaurus.UCSC.bosTau8.refGene", "TxDb.Celegans.UCSC.ce11.refGene", "TxDb.Celegans.UCSC.ce6.ensGene", "TxDb.Cfamiliaris.UCSC.canFam3.refGene", "TxDb.Dmelanogaster.UCSC.dm3.ensGene", "TxDb.Dmelanogaster.UCSC.dm6.ensGene", "TxDb.Drerio.UCSC.danRer10.refGene", "TxDb.Ggallus.UCSC.galGal4.refGene", "TxDb.Hsapiens.BioMart.igis", "TxDb.Hsapiens.UCSC.hg18.knownGene", "TxDb.Hsapiens.UCSC.hg19.knownGene", "TxDb.Hsapiens.UCSC.hg19.lincRNAsTranscripts", "TxDb.Hsapiens.UCSC.hg38.knownGene", "TxDb.Mmulatta.UCSC.rheMac3.refGene", "TxDb.Mmulatta.UCSC.rheMac8.refGene", "TxDb.Mmusculus.UCSC.mm10.ensGene", "TxDb.Mmusculus.UCSC.mm10.knownGene", "TxDb.Mmusculus.UCSC.mm9.knownGene", "TxDb.Ptroglodytes.UCSC.panTro4.refGene", "TxDb.Rnorvegicus.BioMart.igis", "TxDb.Rnorvegicus.UCSC.rn4.ensGene", "TxDb.Rnorvegicus.UCSC.rn5.refGene", "TxDb.Rnorvegicus.UCSC.rn6.refGene", "TxDb.Scerevisiae.UCSC.sacCer2.sgdGene", "TxDb.Scerevisiae.UCSC.sacCer3.sgdGene", "TxDb.Sscrofa.UCSC.susScr3.refGene" ], "importsMe": [ "AllelicImbalance", "alpine", "AnnotationHubData", "annotatr", "biovizBase", "bumphunter", "casper", "ChIPpeakAnno", "ChIPQC", "ChIPseeker", "compEpiTools", "CompGO", "crisprseekplus", "csaw", "customProDB", "derfinder", "derfinderPlot", "EDASeq", "ELMER", "epivizrData", "epivizrStandalone", "FDb.FANTOM4.promoters.hg19", "FDb.InfiniumMethylation.hg18", "FDb.InfiniumMethylation.hg19", "FDb.UCSC.snp135common.hg19", "FDb.UCSC.snp137common.hg19", "FDb.UCSC.tRNAs", "genbankr", "geneAttribution", "geneLenDataBase", "GenVisR", "ggbio", "gmapR", "gQTLstats", "Gviz", "gwascat", "Homo.sapiens", "HTSeqGenie", "INSPEcT", "lumi", "metagene", "methyAnalysis", "Mus.musculus", "PGA", "proBAMr", "qpgraph", "QuasR", "Rattus.norvegicus", "RCAS", "rCGH", "RiboProfiling", "SGSeq", "SplicingGraphs", "SPLINTER", "systemPipeR", "trackViewer", "transcriptR", "TxDb.Athaliana.BioMart.plantsmart22", "TxDb.Athaliana.BioMart.plantsmart25", "TxDb.Hsapiens.BioMart.igis", "TxDb.Rnorvegicus.BioMart.igis", "VariantAnnotation", "VariantFiltering", "VariantTools", "wavClusteR" ], "suggestsMe": [ "AnnotationHub", "biomvRCNS", "Biostrings", "BSgenome.Btaurus.UCSC.bosTau3", "BSgenome.Btaurus.UCSC.bosTau4", "BSgenome.Btaurus.UCSC.bosTau6", "BSgenome.Btaurus.UCSC.bosTau8", "BSgenome.Celegans.UCSC.ce10", "BSgenome.Celegans.UCSC.ce11", "BSgenome.Celegans.UCSC.ce2", "BSgenome.Cfamiliaris.UCSC.canFam2", "BSgenome.Cfamiliaris.UCSC.canFam3", "BSgenome.Dmelanogaster.UCSC.dm2", "BSgenome.Dmelanogaster.UCSC.dm6", "BSgenome.Drerio.UCSC.danRer10", "BSgenome.Drerio.UCSC.danRer5", "BSgenome.Drerio.UCSC.danRer6", "BSgenome.Drerio.UCSC.danRer7", "BSgenome.Gaculeatus.UCSC.gasAcu1", "BSgenome.Ggallus.UCSC.galGal3", "BSgenome.Ggallus.UCSC.galGal4", "BSgenome.Hsapiens.UCSC.hg17", "BSgenome.Mmulatta.UCSC.rheMac2", "BSgenome.Mmulatta.UCSC.rheMac3", "BSgenome.Mmusculus.UCSC.mm8", "BSgenome.Ptroglodytes.UCSC.panTro2", "BSgenome.Ptroglodytes.UCSC.panTro3", "BSgenome.Rnorvegicus.UCSC.rn6", "chipseq", "chromPlot", "CrispRVariants", "cummeRbund", "DEXSeq", "easyRNASeq", "flipflop", "GenomeInfoDb", "GenomicAlignments", "GenomicRanges", "groHMM", "IRanges", "MiRaGE", "parathyroidSE", "recount", "RIPSeeker", "Rsamtools", "ShortRead", "Single.mTEC.Transcriptomes", "SummarizedExperiment" ] }, "GenomicFiles": { "Package": "GenomicFiles", "Version": "1.10.3", "Depends": [ "R (>= 3.1.0)", "methods", "BiocGenerics (>= 0.11.2)", "GenomicRanges (>= 1.23.21)", "SummarizedExperiment", "BiocParallel (>= 1.1.0)", "Rsamtools (>= 1.17.29)", "rtracklayer (>= 1.25.3)" ], "Imports": [ "GenomicAlignments (>= 1.7.7)", "IRanges", "S4Vectors (>= 0.9.25)", "VariantAnnotation", "GenomeInfoDb" ], "Suggests": [ "BiocStyle", "RUnit", "genefilter", "deepSNV", "RNAseqData.HNRNPC.bam.chr14", "Biostrings", "Homo.sapiens" ], "License": "Artistic-2.0", "MD5sum": "a39b2cdb90b498eb102ed5bf100bd7d0", "NeedsCompilation": "no", "Title": "Distributed computing by file or by range", "Description": "This package provides infrastructure for parallel computations distributed 'by file' or 'by range'. User defined MAPPER and REDUCER functions provide added flexibility for data combination and manipulation.", "biocViews": [ "Coverage", "DataImport", "Genetics", "Infrastructure", "Sequencing", "Software" ], "Author": "Bioconductor Package Maintainer [aut, cre], Valerie Obenchain [aut], Michael Love [aut], Lori Shepherd [aut], Martin Morgan [aut]", "Maintainer": "Bioconductor Package Maintainer ", "Video": "https://www.youtube.com/watch?v=3PK_jx44QTs", "source.ver": "src/contrib/GenomicFiles_1.10.3.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GenomicFiles_1.10.3.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GenomicFiles_1.10.3.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GenomicFiles_1.10.3.tgz", "vignettes": [ "vignettes/GenomicFiles/inst/doc/GenomicFiles.pdf" ], "vignetteTitles": [ "Introduction to GenomicFiles" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GenomicFiles/inst/doc/GenomicFiles.R" ], "importsMe": [ "contiBAIT", "derfinder", "erma", "gQTLBase", "gQTLstats", "QuasR", "Rqc" ], "suggestsMe": [ "MultiAssayExperiment" ] }, "GenomicInteractions": { "Package": "GenomicInteractions", "Version": "1.8.1", "Depends": [ "R (>= 3.3)", "InteractionSet" ], "Imports": [ "Rsamtools", "rtracklayer", "GenomicRanges", "IRanges", "BiocGenerics (>= 0.15.3)", "data.table", "stringr", "GenomeInfoDb", "ggplot2", "grid", "gridExtra", "methods", "igraph", "S4Vectors", "dplyr", "Gviz", "Biobase", "graphics", "stats", "utils" ], "Suggests": [ "knitr", "BiocStyle", "testthat" ], "License": "GPL-3", "MD5sum": "46e2691d7c57a7802bec445b1fc0a12a", "NeedsCompilation": "no", "Title": "R package for handling genomic interaction data", "Description": "R package for handling Genomic interaction data, such as ChIA-PET/Hi-C, annotating genomic features with interaction information and producing various plots / statistics.", "biocViews": [ "DataImport", "DataRepresentation", "HiC", "Infrastructure", "Software" ], "Author": "Harmston, N., Ing-Simmons, E., Perry, M., Baresic, A., Lenhard, B.", "Maintainer": "Malcolm Perry , Liz Ing-Simmons ", "URL": "https://github.com/ComputationalRegulatoryGenomicsICL/GenomicInteractions/", "VignetteBuilder": "knitr", "source.ver": "src/contrib/GenomicInteractions_1.8.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GenomicInteractions_1.8.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GenomicInteractions_1.8.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GenomicInteractions_1.8.1.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GenomicInteractions/inst/doc/chiapet_vignette.R", "vignettes/GenomicInteractions/inst/doc/hic_vignette.R" ], "htmlDocs": [ "vignettes/GenomicInteractions/inst/doc/chiapet_vignette.html", "vignettes/GenomicInteractions/inst/doc/hic_vignette.html" ], "htmlTitles": [ "chiapet_vignette.html", "GenomicInteractions-HiC" ], "suggestsMe": [ "Chicago" ] }, "GenomicRanges": { "Package": "GenomicRanges", "Version": "1.26.4", "Depends": [ "R (>= 2.10)", "methods", "stats4", "BiocGenerics (>= 0.17.5)", "S4Vectors (>= 0.9.47)", "IRanges (>= 2.7.8)", "GenomeInfoDb (>= 1.1.20)" ], "Imports": [ "utils", "stats", "XVector" ], "LinkingTo": [ "S4Vectors", "IRanges" ], "Suggests": [ "Biobase", "AnnotationDbi (>= 1.21.1)", "annotate", "Biostrings (>= 2.25.3)", "Rsamtools (>= 1.13.53)", "SummarizedExperiment (>= 0.1.5)", "Matrix", "GenomicAlignments", "rtracklayer", "BSgenome", "GenomicFeatures", "Gviz", "VariantAnnotation", "AnnotationHub", "DESeq2", "DEXSeq", "edgeR", "KEGGgraph", "BiocStyle", "digest", "RUnit", "BSgenome.Hsapiens.UCSC.hg19", "BSgenome.Scerevisiae.UCSC.sacCer2", "KEGG.db", "hgu95av2.db", "org.Hs.eg.db", "org.Mm.eg.db", "org.Sc.sgd.db", "pasilla", "pasillaBamSubset", "TxDb.Athaliana.BioMart.plantsmart22", "TxDb.Dmelanogaster.UCSC.dm3.ensGene", "TxDb.Hsapiens.UCSC.hg19.knownGene", "BSgenome.Mmusculus.UCSC.mm10", "TxDb.Mmusculus.UCSC.mm10.knownGene", "RNAseqData.HNRNPC.bam.chr14", "hgu95av2probe" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "86c7d60ee21a86abc9f48b6527877bf4", "NeedsCompilation": "yes", "Title": "Representation and manipulation of genomic intervals and variables defined along a genome", "Description": "The ability to efficiently represent and manipulate genomic annotations and alignments is playing a central role when it comes to analyzing high-throughput sequencing data (a.k.a. NGS data). The GenomicRanges package defines general purpose containers for storing and manipulating genomic intervals and variables defined along a genome. More specialized containers for representing and manipulating short alignments against a reference genome, or a matrix-like summarization of an experiment, are defined in the GenomicAlignments and SummarizedExperiment packages respectively. Both packages build on top of the GenomicRanges infrastructure.", "biocViews": [ "Annotation", "Coverage", "Genetics", "GenomeAnnotation", "Infrastructure", "Sequencing", "Software" ], "Author": "P. Aboyoun, H. Pagès, and M. Lawrence", "Maintainer": "Bioconductor Package Maintainer ", "source.ver": "src/contrib/GenomicRanges_1.26.4.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GenomicRanges_1.26.4.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GenomicRanges_1.26.4.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GenomicRanges_1.26.4.tgz", "vignettes": [ "vignettes/GenomicRanges/inst/doc/ExtendingGenomicRanges.pdf", "vignettes/GenomicRanges/inst/doc/GenomicRangesHOWTOs.pdf", "vignettes/GenomicRanges/inst/doc/GenomicRangesIntroduction.pdf", "vignettes/GenomicRanges/inst/doc/GRanges_and_GRangesList_slides.pdf", "vignettes/GenomicRanges/inst/doc/Ten_things_slides.pdf" ], "vignetteTitles": [ "Extending GenomicRanges", "GenomicRanges HOWTOs", "An Introduction to the GenomicRanges Package", "A quick introduction to GRanges and GRangesList objects (slides)", "10 Things You Didn't Know (slides from BioC 2016)" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GenomicRanges/inst/doc/ExtendingGenomicRanges.R", "vignettes/GenomicRanges/inst/doc/GenomicRangesHOWTOs.R", "vignettes/GenomicRanges/inst/doc/GenomicRangesIntroduction.R", "vignettes/GenomicRanges/inst/doc/GRanges_and_GRangesList_slides.R", "vignettes/GenomicRanges/inst/doc/Ten_things_slides.R" ], "dependsOnMe": [ "AllelicImbalance", "AneuFinder", "annmap", "AnnotationHubData", "ASpli", "BaalChIP", "Basic4Cseq", "BasicSTARRseq", "baySeq", "biomvRCNS", "BiSeq", "BPRMeth", "BSgenome", "bsseq", "BubbleTree", "bumphunter", "CAFE", "casper", "ChAMPdata", "cheung2010", "chimera", "ChIPComp", "ChIPpeakAnno", "ChIPQC", "chipseq", "chroGPS", "chromPlot", "chromstaR", "CINdex", "cleanUpdTSeq", "cn.mops", "CNPBayes", "cnvGSA", "CNVPanelizer", "compEpiTools", "consensusSeekeR", "CSAR", "csaw", "deepSNV", "DESeq2", "DEXSeq", "DiffBind", "diffHic", "DMRcaller", "DMRcatedata", "DMRforPairs", "DNAshapeR", "DOQTL", "EatonEtAlChIPseq", "EnrichedHeatmap", "ensembldb", "ensemblVEP", "epigenomix", "exomeCopy", "fastseg", "fCCAC", "FourCSeq", "FunChIP", "GeneBreak", "geneRxCluster", "GenoGAM", "GenomicAlignments", "GenomicFeatures", "GenomicFiles", "GenomicTuples", "genoset", "geuvStore2", "gmapR", "GMRP", "GOTHiC", "GreyListChIP", "groHMM", "gtrellis", "GUIDEseq", "Guitar", "Gviz", "HelloRanges", "hiAnnotator", "HilbertCurve", "HiTC", "htSeqTools", "IdeoViz", "InPAS", "intansv", "InteractionSet", "isomiRs", "MBASED", "metagene", "methyAnalysis", "methylKit", "methylPipe", "minfi", "MutationalPatterns", "OmicCircos", "PGA", "PING", "podkat", "QuasR", "r3Cseq", "Rariant", "Rcade", "recoup", "regioneR", "rfPred", "rGREAT", "riboSeqR", "RIPSeeker", "RnBeads", "RnBeads.hg19", "RnBeads.hg38", "RnBeads.mm10", "RnBeads.mm9", "RnBeads.rn5", "Rsamtools", "RSVSim", "rtracklayer", "segmentSeq", "seqbias", "SGSeq", "SICtools", "SigFuge", "SMITE", "SNPhood", "SNPlocs.Hsapiens.dbSNP.20090506", "SNPlocs.Hsapiens.dbSNP.20100427", "SNPlocs.Hsapiens.dbSNP.20101109", "SNPlocs.Hsapiens.dbSNP.20110815", "SNPlocs.Hsapiens.dbSNP.20111119", "SNPlocs.Hsapiens.dbSNP.20120608", "SNPlocs.Hsapiens.dbSNP141.GRCh38", "SNPlocs.Hsapiens.dbSNP142.GRCh37", "SomaticSignatures", "SummarizedExperiment", "TarSeqQC", "TitanCNA", "trackViewer", "TransView", "traseR", "VanillaICE", "VariantAnnotation", "VariantTools", "vtpnet", "wavClusteR", "XtraSNPlocs.Hsapiens.dbSNP141.GRCh38", "YAPSA", "yriMulti" ], "importsMe": [ "ALDEx2", "alpine", "annotatr", "ArrayExpressHTS", "BadRegionFinder", "ballgown", "bamsignals", "BBCAnalyzer", "beadarray", "BEAT", "biovizBase", "BiSeq", "BSgenome", "CAGEr", "CexoR", "cgdv17", "ChAMP", "chipenrich", "chipenrich.data", "ChIPseeker", "chipseq", "ChIPseqR", "chromDraw", "ChromHeatMap", "CNEr", "CNPBayes", "coMET", "contiBAIT", "conumee", "copynumber", "CopywriteR", "COSMIC.67", "CoverageView", "crisprseekplus", "CrispRVariants", "customProDB", "DChIPRep", "debrowser", "DeepBlueR", "DEFormats", "derfinder", "derfinderPlot", "diffloop", "DMRcate", "DRIMSeq", "easyRNASeq", "EDASeq", "ELMER", "ELMER.data", "epivizr", "epivizrData", "erma", "fitCons.UCSC.hg19", "flipflop", "FourCSeq", "FunciSNP", "genbankr", "geneAttribution", "GeneGeneInteR", "genomation", "genomeIntervals", "GenomicAlignments", "GenomicInteractions", "genotypeeval", "GenVisR", "GGBase", "ggbio", "GGtools", "GoogleGenomics", "gQTLBase", "gQTLstats", "gwascat", "h5vc", "hiReadsProcessor", "HTSeqGenie", "INSPEcT", "IVAS", "JunctionSeq", "leeBamViews", "LOLA", "lumi", "M3D", "MADSEQ", "MafDb.1Kgenomes.phase1.hs37d5", "MafDb.1Kgenomes.phase3.hs37d5", "MafDb.ESP6500SI.V2.SSA137", "MafDb.ESP6500SI.V2.SSA137.GRCh38", "MafDb.ESP6500SI.V2.SSA137.hs37d5", "MafDb.ExAC.r0.3.1.nonTCGA.snvs.hs37d5", "MafDb.ExAC.r0.3.1.snvs.hs37d5", "MEAL", "MEDIPS", "methyAnalysis", "MethylSeekR", "methylumi", "MinimumDistance", "MMDiff2", "mosaics", "motifbreakR", "MultiAssayExperiment", "MultiDataSet", "NarrowPeaks", "normr", "nucleR", "oligoClasses", "OrganismDbi", "Pbase", "pcaExplorer", "pepDat", "pepStat", "phastCons100way.UCSC.hg19", "phastCons100way.UCSC.hg38", "phastCons7way.UCSC.hg38", "Pi", "PICS", "pqsfinder", "prebs", "proBAMr", "PureCN", "Pviz", "pwOmics", "QDNAseq", "qpgraph", "qsea", "R3CPET", "R453Plus1Toolbox", "RareVariantVis", "RCAS", "rCGH", "recount", "regioneR", "regionReport", "Repitools", "RiboProfiling", "RNAprobR", "rnaSeqMap", "roar", "seq2pathway", "SeqArray", "seqPattern", "seqplots", "SeqVarTools", "ShortRead", "signeR", "simulatorZ", "SNPchip", "SNPlocs.Hsapiens.dbSNP.20090506", "SNPlocs.Hsapiens.dbSNP.20100427", "SNPlocs.Hsapiens.dbSNP.20101109", "SNPlocs.Hsapiens.dbSNP.20110815", "SNPlocs.Hsapiens.dbSNP.20111119", "SNPlocs.Hsapiens.dbSNP.20120608", "SNPlocs.Hsapiens.dbSNP141.GRCh38", "SNPlocs.Hsapiens.dbSNP142.GRCh37", "SNPlocs.Hsapiens.dbSNP144.GRCh37", "SNPlocs.Hsapiens.dbSNP144.GRCh38", "soGGi", "SomaticCancerAlterations", "spliceR", "SplicingGraphs", "SPLINTER", "STAN", "SVM2CRM", "systemPipeR", "TCGAbiolinks", "TFBSTools", "tracktables", "transcriptR", "triplex", "TVTB", "VariantFiltering", "waveTiling", "XtraSNPlocs.Hsapiens.dbSNP141.GRCh38", "XtraSNPlocs.Hsapiens.dbSNP144.GRCh37", "XtraSNPlocs.Hsapiens.dbSNP144.GRCh38" ], "suggestsMe": [ "alternativeSplicingEvents.hg19", "AnnotationHub", "BeadArrayUseCases", "biobroom", "BiocGenerics", "BiocParallel", "Chicago", "cummeRbund", "GenomeInfoDb", "GeuvadisTranscriptExpr", "HDF5Array", "interactiveDisplay", "IRanges", "metaseqR", "MiRaGE", "NarrowPeaks", "NGScopy", "RTCGA", "S4Vectors", "SeqGSEA", "Single.mTEC.Transcriptomes" ] }, "GenomicTuples": { "Package": "GenomicTuples", "Version": "1.8.3", "Depends": [ "R (>= 3.3.0)", "GenomicRanges (>= 1.23.15)", "GenomeInfoDb (>= 1.7.2)", "S4Vectors (>= 0.9.38)" ], "Imports": [ "methods", "BiocGenerics (>= 0.17.0)", "Rcpp (>= 0.11.2)", "IRanges (>= 2.5.26)", "data.table" ], "LinkingTo": [ "Rcpp" ], "Suggests": [ "testthat", "knitr", "BiocStyle", "rmarkdown" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "b247a7c67d4da07148a012640ff4ad24", "NeedsCompilation": "yes", "Title": "Representation and Manipulation of Genomic Tuples", "Description": "GenomicTuples defines general purpose containers for storing genomic tuples. It aims to provide functionality for tuples of genomic co-ordinates that are analogous to those available for genomic ranges in the GenomicRanges Bioconductor package.", "biocViews": [ "DataRepresentation", "Infrastructure", "Sequencing", "Software" ], "Author": "Peter Hickey , with contributions from Marcin Cieslik and Herve Pages.", "Maintainer": "Peter Hickey ", "URL": "www.github.com/PeteHaitch/GenomicTuples", "VignetteBuilder": "knitr", "BugReports": "https://github.com/PeteHaitch/GenomicTuples/issues", "source.ver": "src/contrib/GenomicTuples_1.8.3.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GenomicTuples_1.8.3.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GenomicTuples_1.8.3.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GenomicTuples_1.8.3.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GenomicTuples/inst/doc/GenomicTuplesIntroduction.R" ], "htmlDocs": [ "vignettes/GenomicTuples/inst/doc/GenomicTuplesIntroduction.html" ], "htmlTitles": [ "GenomicTuplesIntroduction" ] }, "Genominator": { "Package": "Genominator", "Version": "1.28.0", "Depends": [ "R (>= 2.10)", "methods", "RSQLite", "DBI (>= 0.2-5)", "BiocGenerics (>= 0.1.0)", "IRanges (>= 2.5.27)", "GenomeGraphs" ], "Imports": [ "graphics", "stats", "utils" ], "Suggests": [ "biomaRt", "ShortRead", "yeastRNASeq" ], "License": "Artistic-2.0", "MD5sum": "a826b9c64b3b012afaacd7ebc0992bd9", "NeedsCompilation": "no", "Title": "Analyze, manage and store genomic data", "Description": "Tools for storing, accessing, analyzing and visualizing genomic data.", "biocViews": [ "Infrastructure", "Software" ], "Author": "James Bullard, Kasper Daniel Hansen", "Maintainer": "James Bullard ", "source.ver": "src/contrib/Genominator_1.28.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Genominator_1.28.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Genominator_1.28.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Genominator_1.28.0.tgz", "vignettes": [ "vignettes/Genominator/inst/doc/Genominator.pdf", "vignettes/Genominator/inst/doc/plotting.pdf", "vignettes/Genominator/inst/doc/withShortRead.pdf" ], "vignetteTitles": [ "The Genominator User Guide", "Plotting with Genominator", "Working with the ShortRead Package" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Genominator/inst/doc/Genominator.R", "vignettes/Genominator/inst/doc/plotting.R", "vignettes/Genominator/inst/doc/withShortRead.R" ], "suggestsMe": [ "oneChannelGUI" ] }, "genoset": { "Package": "genoset", "Version": "1.30.0", "Depends": [ "R (>= 2.10)", "BiocGenerics (>= 0.11.3)", "GenomicRanges (>= 1.17.19)", "SummarizedExperiment (>= 1.1.6)" ], "Imports": [ "S4Vectors (>= 0.9.25)", "GenomeInfoDb (>= 1.1.3)", "IRanges (>= 2.5.12)", "methods", "graphics" ], "Suggests": [ "RUnit", "knitr", "BiocStyle", "rmarkdown", "DNAcopy", "stats", "BSgenome", "Biostrings" ], "Enhances": [ "parallel" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "b0a5cf43df0dec2be600bd743b22010c", "NeedsCompilation": "yes", "Title": "A RangedSummarizedExperiment with methods for copy number analysis", "Description": "GenoSet provides an extension of the RangedSummarizedExperiment class with additional API features. This class provides convenient and fast methods for working with segmented genomic data. Additionally, GenoSet provides the class RleDataFrame which stores runs of data along the genome for multiple samples and provides very fast summaries of arbitrary row sets (regions of the genome).", "biocViews": [ "CopyNumberVariation", "DataRepresentation", "Infrastructure", "Microarray", "SNP", "Software" ], "Author": "Peter M. Haverty", "Maintainer": "Peter M. Haverty ", "URL": "https://github.com/phaverty/genoset", "VignetteBuilder": "knitr", "source.ver": "src/contrib/genoset_1.30.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/genoset_1.30.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/genoset_1.30.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/genoset_1.30.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/genoset/inst/doc/genoset.R" ], "htmlDocs": [ "vignettes/genoset/inst/doc/genoset.html" ], "htmlTitles": [ "genoset" ], "importsMe": [ "methyAnalysis", "VegaMC" ] }, "genotypeeval": { "Package": "genotypeeval", "Version": "1.4.0", "Depends": [ "R (>= 3.2.0)", "VariantAnnotation" ], "Imports": [ "ggplot2", "rtracklayer", "BiocGenerics", "GenomicRanges", "GenomeInfoDb", "IRanges", "methods", "BiocParallel" ], "Suggests": [ "knitr", "testthat", "SNPlocs.Hsapiens.dbSNP141.GRCh38", "TxDb.Hsapiens.UCSC.hg38.knownGene" ], "License": "file LICENSE", "MD5sum": "76f2436d4b20d65b26768e7b37cb4c36", "NeedsCompilation": "no", "Title": "QA/QC of a gVCF or VCF file", "Description": "Takes in a gVCF or VCF and reports metrics to assess quality of calls.", "biocViews": [ "BatchEffect", "DataImport", "Genetics", "SNP", "Sequencing", "Software", "VariantAnnotation" ], "Author": "Jennifer Tom [aut, cre]", "Maintainer": "Jennifer Tom ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/genotypeeval_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/genotypeeval_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/genotypeeval_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/genotypeeval_1.4.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/genotypeeval/inst/doc/genotypeeval_vignette.R" ], "htmlDocs": [ "vignettes/genotypeeval/inst/doc/genotypeeval_vignette.html" ], "htmlTitles": [ "genotypeeval_vignette" ] }, "genphen": { "Package": "genphen", "Version": "1.2.0", "Depends": [ "R(>= 3.3)", "randomForest", "e1071", "ggplot2", "effsize", "Biostrings", "rjags" ], "License": "GPL (>= 2)", "MD5sum": "678696ea4f386b7c12e05b789ef53ef9", "NeedsCompilation": "no", "Title": "A tool for quantification of associations between genotypes and phenotypes with statistical learning techniques such as random forests and support vector machines as well as with Bayesian inference using hierarchical models", "Description": "Genetic association studies have become an essential tool for studying the relationship between genotypes and phenotypes. They are necessary for the discovery of disease-causing genetic variants. Here we provide a tool for conducting genetic association studies, which uses statistical learning techniques such as random forests and support vector machines, as well as using Bayesian inference with Bayesian hierarchical models. These techniques are superior to the commonly used (frequentist) statistical approaches, alleviating the multiple hypothesis problems and the need for P value corrections, which often lead to massive numbers of false negatives. Thus, with genphen we provide a framework to compare the results obtained using frequentist methods with those obtained using the more sophisticated methods provided by this tool. The tool also provides a few visualization functions which enable the user to inspect the results of such genetic association study and conveniently select the genotypes which have the highest strength of association with the phenotype.", "biocViews": [ "Bayesian", "Classification", "FeatureExtraction", "Genetics", "GenomeWideAssociation", "Regression", "SequenceMatching", "Sequencing", "Software", "SupportVectorMachine" ], "Author": "Simo Kitanovski", "Maintainer": "Simo Kitanovski ", "source.ver": "src/contrib/genphen_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/genphen_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/genphen_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/genphen_1.2.0.tgz", "vignettes": [ "vignettes/genphen/inst/doc/genphenManual.pdf" ], "vignetteTitles": [ "genphen overview" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/genphen/inst/doc/genphenManual.R" ] }, "GenRank": { "Package": "GenRank", "Version": "1.2.0", "Depends": [ "R (>= 3.2.3)" ], "Imports": [ "matrixStats", "reshape2", "survcomp" ], "Suggests": [ "knitr", "rmarkdown", "testthat" ], "License": "Artistic-2.0", "MD5sum": "8d7b8dd6547e31d15cf47b30ab5f4795", "NeedsCompilation": "no", "Title": "Candidate gene prioritization based on convergent evidence", "Description": "Methods for ranking genes based on convergent evidence obtained from multiple independent evidence layers. This package adapts three methods that are popular for meta-analysis.", "biocViews": [ "CopyNumberVariation", "GeneExpression", "Genetics", "Microarray", "SNP", "Sequencing", "Software" ], "Author": "Chakravarthi Kanduri", "Maintainer": "Chakravarthi Kanduri ", "URL": "https://github.com/chakri9/GenRank", "VignetteBuilder": "knitr", "BugReports": "https://github.com/chakri9/GenRank/issues", "source.ver": "src/contrib/GenRank_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GenRank_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GenRank_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GenRank_1.2.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GenRank/inst/doc/GenRank_Vignette.R" ], "htmlDocs": [ "vignettes/GenRank/inst/doc/GenRank_Vignette.html" ], "htmlTitles": [ "Introduction to GenRank Package" ] }, "GenVisR": { "Package": "GenVisR", "Version": "1.4.1", "Depends": [ "R (>= 3.3.0)" ], "Imports": [ "AnnotationDbi", "biomaRt", "BiocGenerics", "Biostrings", "DBI", "FField", "GenomicFeatures", "GenomicRanges", "ggplot2 (>= 2.1.0)", "grid", "gridExtra", "gtable", "gtools", "IRanges", "plyr (>= 1.8.3)", "reshape2", "Rsamtools", "scales", "stats", "utils", "viridis" ], "Suggests": [ "BiocStyle", "BSgenome.Hsapiens.UCSC.hg19", "knitr", "RMySQL", "roxygen2", "testthat", "TxDb.Hsapiens.UCSC.hg19.knownGene", "rmarkdown" ], "License": "GPL-3 + file LICENSE", "MD5sum": "dfdee7d5758b6a1bee7cb2d437f2f23c", "NeedsCompilation": "no", "Title": "Genomic Visualizations in R", "Description": "Produce highly customizable publication quality graphics for genomic data primarily at the cohort level.", "biocViews": [ "Classification", "DNASeq", "DataRepresentation", "Infrastructure", "Software" ], "Author": "Zachary Skidmore [aut, cre], Alex Wagner [aut], Robert Lesurf [aut], Katie Campbell [aut], Jason Kunisaki [aut], Obi Griffith [aut], Malachi Griffith [aut]", "Maintainer": "Zachary Skidmore ", "VignetteBuilder": "knitr", "BugReports": "https://github.com/griffithlab/GenVisR/issues", "source.ver": "src/contrib/GenVisR_1.4.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GenVisR_1.4.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GenVisR_1.4.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GenVisR_1.4.1.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/GenVisR/inst/doc/GenVisR_intro.R", "vignettes/GenVisR/inst/doc/waterfall_introduction.R" ], "htmlDocs": [ "vignettes/GenVisR/inst/doc/GenVisR_intro.html", "vignettes/GenVisR/inst/doc/waterfall_introduction.html" ], "htmlTitles": [ "GenVisR: An introduction", "waterfall: function introduction" ] }, "GEOmetadb": { "Package": "GEOmetadb", "Version": "1.34.0", "Depends": [ "GEOquery", "RSQLite" ], "Suggests": [ "knitr", "rmarkdown", "dplyr", "tm", "wordcloud" ], "License": "Artistic-2.0", "MD5sum": "bc80206762269b6761eaf30e9e618324", "NeedsCompilation": "no", "Title": "A compilation of metadata from NCBI GEO", "Description": "The NCBI Gene Expression Omnibus (GEO) represents the largest public repository of microarray data. However, finding data of interest can be challenging using current tools. GEOmetadb is an attempt to make access to the metadata associated with samples, platforms, and datasets much more feasible. This is accomplished by parsing all the NCBI GEO metadata into a SQLite database that can be stored and queried locally. GEOmetadb is simply a thin wrapper around the SQLite database along with associated documentation. Finally, the SQLite database is updated regularly as new data is added to GEO and can be downloaded at will for the most up-to-date metadata. GEOmetadb paper: http://bioinformatics.oxfordjournals.org/cgi/content/short/24/23/2798 .", "biocViews": [ "Infrastructure", "Software" ], "Author": "Jack Zhu and Sean Davis", "Maintainer": "Jack Zhu ", "URL": "http://gbnci.abcc.ncifcrf.gov/geo/", "VignetteBuilder": "knitr", "source.ver": "src/contrib/GEOmetadb_1.34.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GEOmetadb_1.34.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GEOmetadb_1.34.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GEOmetadb_1.34.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GEOmetadb/inst/doc/GEOmetadb.R" ], "htmlDocs": [ "vignettes/GEOmetadb/inst/doc/GEOmetadb.html" ], "htmlTitles": [ "GEOmetadb" ], "suggestsMe": [ "antiProfilesData" ] }, "GEOquery": { "Package": "GEOquery", "Version": "2.40.0", "Depends": [ "methods", "Biobase" ], "Imports": [ "XML", "RCurl", "httr" ], "Suggests": [ "limma", "knitr", "rmarkdown", "RUnit", "BiocGenerics" ], "License": "GPL-2", "MD5sum": "5eeafa5f4ce40f37e208b1d2f026bd98", "NeedsCompilation": "no", "Title": "Get data from NCBI Gene Expression Omnibus (GEO)", "Description": "The NCBI Gene Expression Omnibus (GEO) is a public repository of microarray data. Given the rich and varied nature of this resource, it is only natural to want to apply BioConductor tools to these data. GEOquery is the bridge between GEO and BioConductor.", "biocViews": [ "DataImport", "Microarray", "OneChannel", "SAGE", "Software", "TwoChannel" ], "Author": "Sean Davis ", "Maintainer": "Sean Davis ", "URL": "https://github.com/seandavi/GEOquery", "VignetteBuilder": "knitr", "BugReports": "https://github.com/seandavi/GEOquery/issues/new", "source.ver": "src/contrib/GEOquery_2.40.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GEOquery_2.40.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GEOquery_2.40.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GEOquery_2.40.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GEOquery/inst/doc/GEOquery.R" ], "htmlDocs": [ "vignettes/GEOquery/inst/doc/GEOquery.html" ], "htmlTitles": [ "Using GEOquery" ], "dependsOnMe": [ "DrugVsDisease", "dyebiasexamples", "GEOmetadb", "GSE62944", "SCAN.UPC" ], "importsMe": [ "AnnotationHubData", "BeadArrayUseCases", "ChIPXpress", "crossmeta", "EGAD", "minfi", "MoonlightR", "recount", "SRAdb" ], "suggestsMe": [ "airway", "antiProfilesData", "ctsGE", "dyebias", "ELBOW", "GeneExpressionSignature", "multiClust", "MultiDataSet", "parathyroidSE", "PGSEA", "prostateCancerCamcap", "prostateCancerGrasso", "prostateCancerStockholm", "prostateCancerTaylor", "prostateCancerVarambally", "RGSEA", "RnBeads", "Rnits", "skewr", "TargetScore" ] }, "GEOsearch": { "Package": "GEOsearch", "Version": "1.0.0", "Depends": [ "R(>= 3.2)" ], "Imports": [ "RCurl", "org.Hs.eg.db", "org.Mm.eg.db" ], "Suggests": [ "knitr", "shiny", "DT", "org.Ag.eg.db", "org.At.tair.db", "org.Bt.eg.db", "org.Ce.eg.db", "org.Cf.eg.db", "org.Dm.eg.db", "org.Dr.eg.db", "org.EcK12.eg.db", "org.EcSakai.eg.db", "org.Gg.eg.db", "org.Mmu.eg.db", "org.Pf.plasmo.db", "org.Pt.eg.db", "org.Rn.eg.db", "org.Sc.sgd.db", "org.Ss.eg.db", "org.Xl.eg.db" ], "License": "GPL(>=2)", "MD5sum": "fb1e7fc4fc9f1ec74bd29d2e66223247", "NeedsCompilation": "no", "Title": "GEOsearch", "Description": "GEOsearch is an extendable search engine for NCBI GEO (Gene Expression Omnibus). Instead of directly searching the term, GEOsearch can find all the gene names contained in the search term and search all the alias of the gene names simultaneously in GEO database. GEOsearch also provides other functions such as summarizing common biology keywords in the search results.", "biocViews": [ "GUI", "Software" ], "Author": "Zhicheng Ji, Hongkai Ji", "Maintainer": "Zhicheng Ji ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/GEOsearch_1.0.0.tar.gz", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GEOsearch_1.0.0.tgz", "vignettes": [ "vignettes/GEOsearch/inst/doc/GEOsearch.pdf" ], "vignetteTitles": [ "GEOsearch: Extendable Search Engine for Gene Expression Omnibus" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GEOsearch/inst/doc/GEOsearch.R" ] }, "GEOsubmission": { "Package": "GEOsubmission", "Version": "1.26.1", "Imports": [ "affy", "Biobase", "utils" ], "License": "GPL (>= 2)", "MD5sum": "ec504c8092c836d337cf6994e9416941", "NeedsCompilation": "no", "Title": "Prepares microarray data for submission to GEO", "Description": "Helps to easily submit a microarray dataset and the associated sample information to GEO by preparing a single file for upload (direct deposit).", "biocViews": [ "Microarray", "Software" ], "Author": "Alexandre Kuhn ", "Maintainer": "Alexandre Kuhn ", "source.ver": "src/contrib/GEOsubmission_1.26.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GEOsubmission_1.26.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GEOsubmission_1.26.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GEOsubmission_1.26.1.tgz", "vignettes": [ "vignettes/GEOsubmission/inst/doc/GEOsubmission.pdf" ], "vignetteTitles": [ "GEOsubmission Overview" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GEOsubmission/inst/doc/GEOsubmission.R" ] }, "gespeR": { "Package": "gespeR", "Version": "1.6.1", "Depends": [ "methods", "graphics", "ggplot2", "R(>= 2.10)" ], "Imports": [ "Matrix", "glmnet", "cellHTS2", "Biobase", "biomaRt", "doParallel", "parallel", "foreach", "reshape2", "dplyr" ], "Suggests": [ "knitr" ], "License": "GPL-3", "MD5sum": "e2b06649ed00a8e41511299339757004", "NeedsCompilation": "no", "Title": "Gene-Specific Phenotype EstimatoR", "Description": "Estimates gene-specific phenotypes from off-target confounded RNAi screens. The phenotype of each siRNA is modeled based on on-targeted and off-targeted genes, using a regularized linear regression model.", "biocViews": [ "CellBasedAssays", "GeneTarget", "Preprocessing", "Regression", "Software", "Visualization" ], "Author": "Fabian Schmich", "Maintainer": "Fabian Schmich ", "URL": "http://www.cbg.ethz.ch/software/gespeR", "VignetteBuilder": "knitr", "source.ver": "src/contrib/gespeR_1.6.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/gespeR_1.6.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/gespeR_1.6.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/gespeR_1.6.1.tgz", "vignettes": [ "vignettes/gespeR/inst/doc/gespeR.pdf" ], "vignetteTitles": [ "An R package for deconvoluting off-target confounded RNAi screens" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/gespeR/inst/doc/gespeR.R" ] }, "GEWIST": { "Package": "GEWIST", "Version": "1.18.0", "Depends": [ "R (>= 2.10)", "car" ], "License": "GPL-2", "MD5sum": "289edebfc239869679fd4231d61a81ab", "NeedsCompilation": "no", "Title": "Gene Environment Wide Interaction Search Threshold", "Description": "This 'GEWIST' package provides statistical tools to efficiently optimize SNP prioritization for gene-gene and gene-environment interactions.", "biocViews": [ "Genetics", "MultipleComparison", "Software" ], "Author": "Wei Q. Deng, Guillaume Pare", "Maintainer": "Wei Q. Deng ", "source.ver": "src/contrib/GEWIST_1.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GEWIST_1.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GEWIST_1.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GEWIST_1.18.0.tgz", "vignettes": [ "vignettes/GEWIST/inst/doc/GEWIST.pdf" ], "vignetteTitles": [ "GEWIST.pdf" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GEWIST/inst/doc/GEWIST.R" ] }, "GGBase": { "Package": "GGBase", "Version": "3.36.0", "Depends": [ "R (>= 2.14)", "methods", "snpStats" ], "Imports": [ "limma", "genefilter", "Biobase", "BiocGenerics", "S4Vectors", "IRanges", "Matrix", "AnnotationDbi", "digest", "GenomicRanges", "SummarizedExperiment" ], "Suggests": [ "GGtools", "illuminaHumanv1.db" ], "License": "Artistic-2.0", "MD5sum": "4721ca464e13048412abfbc6413f1075", "NeedsCompilation": "no", "Title": "GGBase infrastructure for genetics of gene expression package GGtools", "Description": "infrastructure", "biocViews": [ "Genetics", "Infrastructure", "Software" ], "Author": "VJ Carey ", "Maintainer": "VJ Carey ", "source.ver": "src/contrib/GGBase_3.36.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GGBase_3.36.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GGBase_3.36.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GGBase_3.36.0.tgz", "vignettes": [ "vignettes/GGBase/inst/doc/ggbase.pdf" ], "vignetteTitles": [ "GGBase -- infrastructure for GGtools, genetics of gene expression" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GGBase/inst/doc/ggbase.R" ], "dependsOnMe": [ "ceu1kg", "ceu1kgv", "ceuhm3", "dsQTL", "GGdata", "GGtools", "hmyriB36", "yri1kgv" ] }, "ggbio": { "Package": "ggbio", "Version": "1.22.4", "Depends": [ "methods", "BiocGenerics", "ggplot2 (>= 1.0.0)" ], "Imports": [ "grid", "grDevices", "graphics", "stats", "utils", "gridExtra", "scales", "reshape2", "gtable", "Hmisc", "biovizBase (>= 1.19.1)", "Biobase", "S4Vectors (>= 0.9.25)", "IRanges", "GenomeInfoDb (>= 1.1.3)", "GenomicRanges (>= 1.21.10)", "SummarizedExperiment", "Biostrings", "Rsamtools (>= 1.17.28)", "GenomicAlignments (>= 1.1.16)", "BSgenome", "VariantAnnotation (>= 1.11.4)", "rtracklayer (>= 1.25.16)", "GenomicFeatures (>= 1.17.13)", "OrganismDbi", "GGally", "ensembldb (>= 1.3.8)", "AnnotationDbi" ], "Suggests": [ "vsn", "BSgenome.Hsapiens.UCSC.hg19", "Homo.sapiens", "TxDb.Hsapiens.UCSC.hg19.knownGene", "chipseq", "TxDb.Mmusculus.UCSC.mm9.knownGene", "knitr", "BiocStyle", "testthat", "EnsDb.Hsapiens.v75" ], "License": "Artistic-2.0", "MD5sum": "d09a2ba6e92a5c8676cf4edc5133bfe8", "NeedsCompilation": "no", "Title": "Visualization tools for genomic data.", "Description": "The ggbio package extends and specializes the grammar of graphics for biological data. The graphics are designed to answer common scientific questions, in particular those often asked of high throughput genomics data. All core Bioconductor data structures are supported, where appropriate. The package supports detailed views of particular genomic regions, as well as genome-wide overviews. Supported overviews include ideograms and grand linear views. High-level plots include sequence fragment length, edge-linked interval to data view, mismatch pileup, and several splicing summaries.", "biocViews": [ "Infrastructure", "Software", "Visualization" ], "Author": "Tengfei Yin [aut], Michael Lawrence [aut, ths, cre], Dianne Cook [aut, ths], Johannes Rainer [ctb]", "Maintainer": "Michael Lawrence ", "URL": "http://tengfei.github.com/ggbio/", "VignetteBuilder": "knitr", "BugReports": "https://github.com/tengfei/ggbio/issues", "source.ver": "src/contrib/ggbio_1.22.4.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ggbio_1.22.4.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ggbio_1.22.4.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ggbio_1.22.4.tgz", "vignettes": [ "vignettes/ggbio/inst/doc/ggbio.pdf" ], "vignetteTitles": [ "Part 0: Introduction and quick start" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "dependsOnMe": [ "CAFE", "coMET", "intansv" ], "importsMe": [ "derfinderPlot", "FourCSeq", "gwascat", "Pi", "R3CPET", "Rariant", "ReportingTools", "RiboProfiling", "SomaticSignatures" ], "suggestsMe": [ "beadarray", "chromstaR", "GoogleGenomics", "gQTLstats", "interactiveDisplay", "regionReport", "RnBeads", "Single.mTEC.Transcriptomes", "SomaticCancerAlterations" ] }, "ggcyto": { "Package": "ggcyto", "Version": "1.2.3", "Depends": [ "methods", "ggplot2(>= 2.0.0)", "flowCore", "ncdfFlow(>= 2.17.1)", "flowWorkspace(>= 3.17.24)" ], "Imports": [ "plyr", "scales", "data.table", "RColorBrewer", "gridExtra" ], "Suggests": [ "testthat", "flowWorkspaceData", "knitr", "rmarkdown", "flowStats", "openCyto", "flowViz" ], "License": "Artistic-2.0", "MD5sum": "830310cab9e42d2ecdb921d31115cce8", "NeedsCompilation": "no", "Title": "Visualize Cytometry data with ggplot", "Description": "With the dedicated fority method implemented for flowSet, ncdfFlowSet and GatingSet classes, both raw and gated flow cytometry data can be plotted directly with ggplot. ggcyto wrapper and some customed layers also make it easy to add gates and population statistics to the plot.", "biocViews": [ "CellBasedAssays", "FlowCytometry", "Infrastructure", "Software", "Visualization" ], "Author": "Mike Jiang", "Maintainer": "Mike Jiang ", "URL": "https://github.com/RGLab/ggcyto/issues", "VignetteBuilder": "knitr", "source.ver": "src/contrib/ggcyto_1.2.3.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ggcyto_1.2.3.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ggcyto_1.2.3.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ggcyto_1.2.3.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ggcyto/inst/doc/autoplot.R", "vignettes/ggcyto/inst/doc/ggcyto.flowSet.R", "vignettes/ggcyto/inst/doc/ggcyto.GatingSet.R", "vignettes/ggcyto/inst/doc/Top_features_of_ggcyto.R" ], "htmlDocs": [ "vignettes/ggcyto/inst/doc/autoplot.html", "vignettes/ggcyto/inst/doc/ggcyto.flowSet.html", "vignettes/ggcyto/inst/doc/ggcyto.GatingSet.html", "vignettes/ggcyto/inst/doc/Top_features_of_ggcyto.html" ], "htmlTitles": [ "Quick plot for cytometry data", "Visualize flowSet with ggcyto", "Visualize GatingSet with ggcyto", "Feature summary of ggcyto" ], "suggestsMe": [ "CytoML", "flowCore", "flowWorkspace" ] }, "GGtools": { "Package": "GGtools", "Version": "5.10.1", "Depends": [ "R (>= 2.14)", "GGBase (>= 3.19.7)", "data.table", "parallel", "Homo.sapiens" ], "Imports": [ "methods", "utils", "stats", "BiocGenerics", "snpStats", "ff", "Rsamtools", "AnnotationDbi", "Biobase", "bit", "VariantAnnotation", "hexbin", "rtracklayer", "Gviz", "stats4", "S4Vectors (>= 0.9.25)", "IRanges", "GenomeInfoDb", "GenomicRanges", "iterators", "Biostrings", "ROCR", "biglm", "ggplot2", "reshape2" ], "Suggests": [ "GGdata", "illuminaHumanv1.db", "SNPlocs.Hsapiens.dbSNP144.GRCh37", "multtest", "aod", "rmeta" ], "Enhances": [ "MatrixEQTL", "foreach", "doParallel", "gwascat" ], "License": "Artistic-2.0", "MD5sum": "738e902ea03a36f6b7ace070ab502ebb", "NeedsCompilation": "no", "Title": "software and data for analyses in genetics of gene expression", "Description": "software and data for analyses in genetics of gene expression and/or DNA methylation", "biocViews": [ "GeneExpression", "GeneticVariability", "Genetics", "SNP", "Software" ], "Author": "VJ Carey ", "Maintainer": "VJ Carey ", "source.ver": "src/contrib/GGtools_5.10.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GGtools_5.10.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GGtools_5.10.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GGtools_5.10.1.tgz", "vignettes": [ "vignettes/GGtools/inst/doc/GGtools.pdf" ], "vignetteTitles": [ "GGtools: software for eQTL identification" ], "hasREADME": true, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GGtools/inst/doc/GGtools.R" ], "importsMe": [ "ceuhm3", "GeneGeneInteR" ], "suggestsMe": [ "cgdv17", "dsQTL", "GGBase", "gQTLBase", "gwascat", "hmyriB36" ], "dependsOnMe": [ "ceu1kg", "cheung2010" ] }, "ggtree": { "Package": "ggtree", "Version": "1.6.11", "Depends": [ "R (>= 3.3.1)", "ggplot2 (>= 2.2.0)" ], "Imports": [ "ape", "grDevices", "grid", "jsonlite", "magrittr", "methods", "stats4", "tidyr", "utils" ], "Suggests": [ "Biostrings", "colorspace", "EBImage", "emojifont", "knitr", "rmarkdown", "scales", "testthat" ], "License": "Artistic-2.0", "MD5sum": "cd28978bdef28a35035a38952835438d", "NeedsCompilation": "no", "Title": "an R package for visualization and annotation of phylogenetic trees with their covariates and other associated data", "Description": "'ggtree' extends the 'ggplot2' plotting system which implemented the grammar of graphics. 'ggtree' is designed for visualization and annotation of phylogenetic trees with their covariates and other associated data.", "biocViews": [ "Alignment", "Annotation", "Clustering", "DataImport", "MultipleSequenceAlignment", "ReproducibleResearch", "Software", "Visualization" ], "Author": "Guangchuang Yu and Tommy Tsan-Yuk Lam", "Maintainer": "Guangchuang Yu ", "URL": "https://guangchuangyu.github.io/ggtree", "VignetteBuilder": "knitr", "BugReports": "https://github.com/GuangchuangYu/ggtree/issues", "source.ver": "src/contrib/ggtree_1.6.11.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ggtree_1.6.11.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ggtree_1.6.11.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ggtree_1.6.11.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ggtree/inst/doc/advanceTreeAnnotation.R", "vignettes/ggtree/inst/doc/ggtree.R", "vignettes/ggtree/inst/doc/ggtreeUtilities.R", "vignettes/ggtree/inst/doc/treeAnnotation.R", "vignettes/ggtree/inst/doc/treeImport.R", "vignettes/ggtree/inst/doc/treeManipulation.R", "vignettes/ggtree/inst/doc/treeVisualization.R" ], "htmlDocs": [ "vignettes/ggtree/inst/doc/advanceTreeAnnotation.html", "vignettes/ggtree/inst/doc/ggtree.html", "vignettes/ggtree/inst/doc/ggtreeUtilities.html", "vignettes/ggtree/inst/doc/treeAnnotation.html", "vignettes/ggtree/inst/doc/treeImport.html", "vignettes/ggtree/inst/doc/treeManipulation.html", "vignettes/ggtree/inst/doc/treeVisualization.html" ], "htmlTitles": [ "05 Advance Tree Annotation", "00 ggtree introduction", "06 ggtree utilities", "04 Tree Annotation", "01 Tree Data Import", "03 Tree Manipulation", "02 Tree Visualization" ], "importsMe": [ "LINC", "philr" ] }, "girafe": { "Package": "girafe", "Version": "1.26.0", "Depends": [ "R (>= 2.10.0)", "methods", "BiocGenerics (>= 0.13.8)", "S4Vectors (>= 0.7.21)", "Rsamtools", "intervals (>= 0.13.1)", "ShortRead (>= 1.3.21)", "genomeIntervals (>= 1.25.1)", "grid" ], "Imports": [ "methods", "Biobase", "Biostrings", "graphics", "grDevices", "stats", "utils", "IRanges (>= 2.3.23)" ], "Suggests": [ "MASS", "org.Mm.eg.db", "RColorBrewer" ], "Enhances": [ "genomeIntervals" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "0a08248c25d610277f077b57f1d75a3a", "NeedsCompilation": "yes", "Title": "Genome Intervals and Read Alignments for Functional Exploration", "Description": "The package 'girafe' deals with the genome-level representation of aligned reads from next-generation sequencing data. It contains an object class for enabling a detailed description of genome intervals with aligned reads and functions for comparing, visualising, exporting and working with such intervals and the aligned reads. As such, the package interacts with and provides a link between the packages ShortRead, IRanges and genomeIntervals.", "biocViews": [ "Sequencing", "Software" ], "Author": "Joern Toedling, with contributions from Constance Ciaudo, Olivier Voinnet, Edith Heard, Emmanuel Barillot, and Wolfgang Huber", "Maintainer": "J. Toedling ", "source.ver": "src/contrib/girafe_1.26.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/girafe_1.26.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/girafe_1.26.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/girafe_1.26.0.tgz", "vignettes": [ "vignettes/girafe/inst/doc/girafe.pdf" ], "vignetteTitles": [ "Genome intervals and read alignments for functional exploration" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/girafe/inst/doc/girafe.R" ] }, "GLAD": { "Package": "GLAD", "Version": "2.38.0", "Depends": [ "R (>= 2.10)" ], "Suggests": [ "aws", "tcltk" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "4ea9e2c27e13e1cf5e4a9cd9d9e8a5f3", "NeedsCompilation": "yes", "Title": "Gain and Loss Analysis of DNA", "Description": "Analysis of array CGH data : detection of breakpoints in genomic profiles and assignment of a status (gain, normal or loss) to each chromosomal regions identified.", "biocViews": [ "CopyNumberVariation", "Microarray", "Software" ], "Author": "Philippe Hupe", "Maintainer": "Philippe Hupe ", "URL": "http://bioinfo.curie.fr", "SystemRequirements": "gsl. Note: users should have GSL installed. Windows users: 'consult the README file available in the inst directory of the source distribution for necessary configuration instructions'.", "source.ver": "src/contrib/GLAD_2.38.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GLAD_2.38.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GLAD_2.38.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GLAD_2.38.0.tgz", "vignettes": [ "vignettes/GLAD/inst/doc/GLAD.pdf" ], "vignetteTitles": [ "GLAD" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GLAD/inst/doc/GLAD.R" ], "dependsOnMe": [ "ADaCGH2", "ITALICS", "MANOR", "seqCNA" ], "importsMe": [ "ITALICS", "MANOR", "snapCGH" ] }, "Glimma": { "Package": "Glimma", "Version": "1.2.1", "Depends": [ "R (>= 3.3.0)" ], "Imports": [ "DESeq2", "edgeR", "grDevices", "methods", "stats", "utils" ], "Suggests": [ "BiocStyle", "limma" ], "License": "GPL-3 | file LICENSE", "MD5sum": "806b341f8255e00cfce5061745ac1e09", "NeedsCompilation": "no", "Title": "Interactive HTML graphics", "Description": "This package generates interactive visualisations for analysis of RNA-sequencing data using output from limma, edgeR or DESeq2 packages in an HTML page. The interactions are built on top of the popular static representations of analysis results in order to provide additional information.", "biocViews": [ "DifferentialExpression", "RNASeq", "ReportWriting", "Software", "Visualization" ], "Author": "Shian Su, Matt Ritchie, Charity Law", "Maintainer": "Shian Su ", "URL": "https://github.com/Shians/Glimma", "BugReports": "https://github.com/Shians/Glimma/issues", "source.ver": "src/contrib/Glimma_1.2.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Glimma_1.2.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Glimma_1.2.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Glimma_1.2.1.tgz", "vignettes": [ "vignettes/Glimma/inst/doc/Glimma.pdf" ], "vignetteTitles": [ "Glimma Vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/Glimma/inst/doc/Glimma.R" ] }, "GlobalAncova": { "Package": "GlobalAncova", "Version": "3.42.0", "Depends": [ "methods", "corpcor", "globaltest" ], "Imports": [ "annotate", "AnnotationDbi" ], "Suggests": [ "Biobase", "annotate", "GO.db", "KEGG.db", "golubEsets", "hu6800.db", "vsn", "GSEABase", "Rgraphviz" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "8277af66056416236f46e1422f8aec97", "NeedsCompilation": "yes", "Title": "Calculates a global test for differential gene expression between groups", "Description": "We give the following arguments in support of the GlobalAncova approach: After appropriate normalisation, gene-expression-data appear rather symmetrical and outliers are no real problem, so least squares should be rather robust. ANCOVA with interaction yields saturated data modelling e.g. different means per group and gene. Covariate adjustment can help to correct for possible selection bias. Variance homogeneity and uncorrelated residuals cannot be expected. Application of ordinary least squares gives unbiased, but no longer optimal estimates (Gauss-Markov-Aitken). Therefore, using the classical F-test is inappropriate, due to correlation. The test statistic however mirrors deviations from the null hypothesis. In combination with a permutation approach, empirical significance levels can be approximated. Alternatively, an approximation yields asymptotic p-values. This work was supported by the NGFN grant 01 GR 0459, BMBF, Germany.", "biocViews": [ "DifferentialExpression", "Microarray", "OneChannel", "Pathways", "Software" ], "Author": "U. Mansmann, R. Meister, M. Hummel, R. Scheufele, with contributions from S. Knueppel", "Maintainer": "Manuela Hummel ", "source.ver": "src/contrib/GlobalAncova_3.42.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GlobalAncova_3.42.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GlobalAncova_3.42.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GlobalAncova_3.42.0.tgz", "vignettes": [ "vignettes/GlobalAncova/inst/doc/GlobalAncova.pdf", "vignettes/GlobalAncova/inst/doc/GlobalAncovaDecomp.pdf" ], "vignetteTitles": [ "GlobalAncova.pdf", "GlobalAncovaDecomp.pdf" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GlobalAncova/inst/doc/GlobalAncova.R", "vignettes/GlobalAncova/inst/doc/GlobalAncovaDecomp.R" ] }, "globalSeq": { "Package": "globalSeq", "Version": "1.2.0", "Depends": [ "R(>= 3.3.0)" ], "Suggests": [ "knitr", "testthat", "SummarizedExperiment" ], "License": "GPL-3", "MD5sum": "f79ecdfeccd122c023141c9d7bc19e01", "NeedsCompilation": "no", "Title": "Testing for association between RNA-Seq and high-dimensional data", "Description": "The method may be conceptualised as a test of overall significance in regression analysis, where the response variable is overdispersed and the number of explanatory variables exceeds the sample size.", "biocViews": [ "DifferentialExpression", "DimensionReduction", "ExomeSeq", "ExonArray", "GeneExpression", "GenomeWideAssociation", "MultipleComparison", "RNASeq", "Regression", "Sequencing", "Software", "Transcriptomics", "WholeGenome", "miRNA" ], "Author": "Armin Rauschenberger", "Maintainer": "Armin Rauschenberger ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/globalSeq_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/globalSeq_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/globalSeq_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/globalSeq_1.2.0.tgz", "vignettes": [ "vignettes/globalSeq/inst/doc/globalSeq.pdf" ], "vignetteTitles": [ "globalSeq" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/globalSeq/inst/doc/globalSeq.R" ] }, "globaltest": { "Package": "globaltest", "Version": "5.28.0", "Depends": [ "methods", "survival" ], "Imports": [ "Biobase", "AnnotationDbi", "annotate", "graphics" ], "Suggests": [ "vsn", "golubEsets", "KEGG.db", "hu6800.db", "Rgraphviz", "GO.db", "lungExpression", "org.Hs.eg.db", "GSEABase", "penalized", "gss", "MASS", "boot", "rpart" ], "License": "GPL (>= 2)", "MD5sum": "aa33575d25d437d991c602f7ceefc37e", "NeedsCompilation": "no", "Title": "Testing Groups of Covariates/Features for Association with a Response Variable, with Applications to Gene Set Testing", "Description": "The global test tests groups of covariates (or features) for association with a response variable. This package implements the test with diagnostic plots and multiple testing utilities, along with several functions to facilitate the use of this test for gene set testing of GO and KEGG terms.", "biocViews": [ "Bioinformatics", "DifferentialExpression", "GO", "Microarray", "OneChannel", "Pathways", "Software" ], "Author": "Jelle Goeman and Jan Oosting, with contributions by Livio Finos and Aldo Solari", "Maintainer": "Jelle Goeman ", "source.ver": "src/contrib/globaltest_5.28.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/globaltest_5.28.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/globaltest_5.28.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/globaltest_5.28.0.tgz", "vignettes": [ "vignettes/globaltest/inst/doc/GlobalTest.pdf" ], "vignetteTitles": [ "Global Test" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/globaltest/inst/doc/GlobalTest.R" ], "dependsOnMe": [ "GlobalAncova" ], "importsMe": [ "BiSeq", "EGSEA", "SIM" ], "suggestsMe": [ "topGO" ] }, "gmapR": { "Package": "gmapR", "Version": "1.16.0", "Depends": [ "R (>= 2.15.0)", "methods", "GenomeInfoDb (>= 1.1.3)", "GenomicRanges (>= 1.17.12)", "Rsamtools (>= 1.17.8)" ], "Imports": [ "S4Vectors (>= 0.9.25)", "IRanges", "rtracklayer (>= 1.31.2)", "GenomicFeatures (>= 1.17.13)", "Biostrings", "VariantAnnotation (>= 1.11.4)", "tools", "Biobase", "BSgenome", "GenomicAlignments (>= 1.1.9)", "BiocParallel" ], "Suggests": [ "RUnit", "BSgenome.Dmelanogaster.UCSC.dm3", "BSgenome.Scerevisiae.UCSC.sacCer3", "org.Hs.eg.db", "TxDb.Hsapiens.UCSC.hg19.knownGene", "BSgenome.Hsapiens.UCSC.hg19", "LungCancerLines" ], "License": "Artistic-2.0", "MD5sum": "29669b353d07892536e0c3d1767acb02", "NeedsCompilation": "yes", "Title": "An R interface to the GMAP/GSNAP/GSTRUCT suite", "Description": "GSNAP and GMAP are a pair of tools to align short-read data written by Tom Wu. This package provides convenience methods to work with GMAP and GSNAP from within R. In addition, it provides methods to tally alignment results on a per-nucleotide basis using the bam_tally tool.", "biocViews": [ "Alignment", "Software" ], "Author": "Cory Barr, Thomas Wu, Michael Lawrence", "Maintainer": "Michael Lawrence ", "source.ver": "src/contrib/gmapR_1.16.0.tar.gz", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/gmapR_1.16.0.tgz", "vignettes": [ "vignettes/gmapR/inst/doc/gmapR.pdf" ], "vignetteTitles": [ "gmapR" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/gmapR/inst/doc/gmapR.R" ], "dependsOnMe": [ "HTSeqGenie" ], "importsMe": [ "VariantTools" ] }, "GMRP": { "Package": "GMRP", "Version": "1.2.0", "Depends": [ "R(>= 3.3.0)", "stats", "utils", "graphics", "grDevices", "diagram", "plotrix", "base", "GenomicRanges" ], "Suggests": [ "BiocStyle", "BiocGenerics", "VariantAnnotation" ], "License": "GPL (>= 2)", "MD5sum": "fb47ec3eb0b11e8fb6c07d3748d70d24", "NeedsCompilation": "no", "Title": "GWAS-based Mendelian Randomization and Path Analyses", "Description": "Perform Mendelian randomization analysis of multiple SNPs to determine risk factors causing disease of study and to exclude confounding variabels and perform path analysis to construct path of risk factors to the disease.", "biocViews": [ "Regression", "SNP", "Sequencing", "Software" ], "Author": "Yuan-De Tan and Dajiang Liu", "Maintainer": "Yuan-De Tan ", "source.ver": "src/contrib/GMRP_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GMRP_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GMRP_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GMRP_1.2.0.tgz", "vignettes": [ "vignettes/GMRP/inst/doc/GMRP.pdf" ], "vignetteTitles": [ "Causal Effect Analysis of Risk Factors for Disease with the \"GMRP\" package" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GMRP/inst/doc/GMRP.R" ] }, "GOexpress": { "Package": "GOexpress", "Version": "1.8.1", "Depends": [ "R (>= 3.0.2)", "grid", "stats", "graphics", "Biobase (>= 2.22.0)" ], "Imports": [ "biomaRt (>= 2.18.0)", "stringr (>= 0.6.2)", "ggplot2 (>= 0.9.0)", "RColorBrewer (>= 1.0)", "gplots (>= 2.13.0)", "randomForest (>= 4.6)", "VennDiagram (>= 1.6.5)", "RCurl (>= 1.95)" ], "Suggests": [ "BiocStyle" ], "License": "GPL (>= 3)", "MD5sum": "92a64baa2d22da131b7a60ba8b39e255", "NeedsCompilation": "no", "Title": "Visualise microarray and RNAseq data using gene ontology annotations", "Description": "The package contains methods to visualise the expression profile of genes from a microarray or RNA-seq experiment, and offers a supervised clustering approach to identify GO terms containing genes with expression levels that best classify two or more predefined groups of samples. Annotations for the genes present in the expression dataset may be obtained from Ensembl through the biomaRt package, if not provided by the user. The default random forest framework is used to evaluate the capacity of each gene to cluster samples according to the factor of interest. Finally, GO terms are scored by averaging the rank (alternatively, score) of their respective gene sets to cluster the samples. P-values may be computed to assess the significance of GO term ranking. Visualisation function include gene expression profile, gene ontology-based heatmaps, and hierarchical clustering of experimental samples using gene expression data.", "biocViews": [ "Annotation", "Clustering", "DataRepresentation", "DifferentialExpression", "GO", "GeneExpression", "GeneSetEnrichment", "Microarray", "MultipleComparison", "Pathways", "RNASeq", "Sequencing", "Software", "TimeCourse", "Transcription", "Visualization" ], "Author": "Kevin Rue-Albrecht [aut, cre], Tharvesh M.L. Ali [ctb], Paul A. McGettigan [ctb], Belinda Hernandez [ctb], David A. Magee [ctb], Nicolas C. Nalpas [ctb], Andrew Parnell [ctb], Stephen V. Gordon [ths], David E. MacHugh [ths]", "Maintainer": "Kevin Rue-Albrecht ", "URL": "https://github.com/kevinrue/GOexpress", "source.ver": "src/contrib/GOexpress_1.8.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GOexpress_1.8.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GOexpress_1.8.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GOexpress_1.8.1.tgz", "vignettes": [ "vignettes/GOexpress/inst/doc/GOexpress-UsersGuide.pdf" ], "vignetteTitles": [ "UsersGuide" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GOexpress/inst/doc/GOexpress-UsersGuide.R" ] }, "GOFunction": { "Package": "GOFunction", "Version": "1.22.0", "Depends": [ "R (>= 2.11.0)", "methods", "Biobase (>= 2.8.0)", "graph (>= 1.26.0)", "Rgraphviz (>= 1.26.0)", "GO.db (>= 2.4.1)", "AnnotationDbi (>= 1.10.2)", "SparseM (>= 0.85)" ], "Imports": [ "methods", "Biobase", "graph", "Rgraphviz", "GO.db", "AnnotationDbi", "DBI", "SparseM" ], "License": "GPL (>= 2)", "MD5sum": "b1f9011104c7d78cfd15bf79e1e6f73b", "NeedsCompilation": "no", "Title": "GO-function: deriving biologcially relevant functions from statistically significant functions", "Description": "The GO-function package provides a tool to address the redundancy that result from the GO structure or multiple annotation genes and derive biologically relevant functions from the statistically significant functions based on some intuitive assumption and statistical testing.", "biocViews": [ "GO", "GeneSetEnrichment", "Microarray", "Pathways", "Software" ], "Author": "Jing Wang ", "Maintainer": "Jing Wang ", "source.ver": "src/contrib/GOFunction_1.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GOFunction_1.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GOFunction_1.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GOFunction_1.22.0.tgz", "vignettes": [ "vignettes/GOFunction/inst/doc/GOFunction.pdf" ], "vignetteTitles": [ "GO-function" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GOFunction/inst/doc/GOFunction.R" ] }, "GoogleGenomics": { "Package": "GoogleGenomics", "Version": "1.6.0", "Depends": [ "R (>= 3.1.0)", "GenomicAlignments (>= 1.0.1)", "VariantAnnotation" ], "Imports": [ "Biostrings", "GenomeInfoDb", "GenomicRanges", "IRanges", "httr", "rjson", "Rsamtools", "S4Vectors (>= 0.9.25)" ], "Suggests": [ "BiocStyle", "httpuv", "knitr", "rmarkdown", "testthat", "ggbio", "ggplot2", "BSgenome.Hsapiens.UCSC.hg19", "org.Hs.eg.db", "TxDb.Hsapiens.UCSC.hg19.knownGene" ], "License": "Apache License (== 2.0) | file LICENSE", "MD5sum": "d5286fc47ed324eb83aeaea675835cea", "NeedsCompilation": "no", "Title": "R Client for Google Genomics API", "Description": "Provides an R package to interact with the Google Genomics API.", "biocViews": [ "DataImport", "Software", "ThirdPartyClient" ], "Author": "Cassie Doll [aut], Nicole Deflaux [aut], Siddhartha Bagaria [aut, cre]", "Maintainer": "Siddhartha Bagaria ", "URL": "https://cloud.google.com/genomics/", "VignetteBuilder": "knitr", "BugReports": "https://github.com/Bioconductor/GoogleGenomics/issues", "source.ver": "src/contrib/GoogleGenomics_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GoogleGenomics_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GoogleGenomics_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GoogleGenomics_1.6.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/GoogleGenomics/inst/doc/AnnotatingVariants.R", "vignettes/GoogleGenomics/inst/doc/PlottingAlignments.R", "vignettes/GoogleGenomics/inst/doc/VariantAnnotation-comparison-test.R" ], "htmlDocs": [ "vignettes/GoogleGenomics/inst/doc/AnnotatingVariants.html", "vignettes/GoogleGenomics/inst/doc/PlottingAlignments.html", "vignettes/GoogleGenomics/inst/doc/VariantAnnotation-comparison-test.html" ], "htmlTitles": [ "Annotating Variants", "Plotting Alignments", "Reproducing Variant Annotation Results" ] }, "GOpro": { "Package": "GOpro", "Version": "1.0.0", "Depends": [ "R (>= 3.3)" ], "Imports": [ "AnnotationDbi", "dendextend", "doParallel", "foreach", "parallel", "org.Hs.eg.db", "GO.db", "Rcpp", "stats", "graphics", "MultiAssayExperiment", "IRanges", "S4Vectors" ], "LinkingTo": [ "Rcpp", "BH" ], "Suggests": [ "knitr", "rmarkdown", "RTCGA.PANCAN12", "BiocStyle", "testthat" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "5e34a8c22244f66c3d82a31ae36a737f", "NeedsCompilation": "yes", "Title": "Find the most characteristic gene ontology terms for groups of human genes", "Description": "Find the most characteristic gene ontology terms for groups of human genes. This package was created as a part of the thesis which was developed under the auspices of MI^2 Group (http://mi2.mini.pw.edu.pl/, https://github.com/geneticsMiNIng).", "biocViews": [ "Annotation", "Clustering", "GO", "GeneExpression", "GeneSetEnrichment", "MultipleComparison", "Software" ], "Author": "Lidia Chrabaszcz", "Maintainer": "Lidia Chrabaszcz ", "URL": "https://github.com/mi2-warsaw/GOpro", "VignetteBuilder": "knitr", "BugReports": "https://github.com/mi2-warsaw/GOpro/issues", "source.ver": "src/contrib/GOpro_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GOpro_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GOpro_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GOpro_1.0.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GOpro/inst/doc/GOpro_vignette.R" ], "htmlDocs": [ "vignettes/GOpro/inst/doc/GOpro_vignette.html" ], "htmlTitles": [ "GOpro: Determine groups of genes and find their characteristic GO term" ] }, "goProfiles": { "Package": "goProfiles", "Version": "1.36.0", "Depends": [ "Biobase", "AnnotationDbi", "GO.db" ], "Suggests": [ "org.Hs.eg.db" ], "License": "GPL-2", "MD5sum": "c4527712d8440b349bdf7aef10075e1b", "NeedsCompilation": "no", "Title": "goProfiles: an R package for the statistical analysis of functional profiles", "Description": "The package implements methods to compare lists of genes based on comparing the corresponding 'functional profiles'.", "biocViews": [ "Annotation", "GO", "GeneExpression", "GeneSetEnrichment", "GraphAndNetwork", "Microarray", "MultipleComparison", "Pathways", "Software" ], "Author": "Alex Sanchez, Jordi Ocana and Miquel Salicru", "Maintainer": "Alex Sanchez ", "source.ver": "src/contrib/goProfiles_1.36.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/goProfiles_1.36.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/goProfiles_1.36.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/goProfiles_1.36.0.tgz", "vignettes": [ "vignettes/goProfiles/inst/doc/goProfiles.pdf" ], "vignetteTitles": [ "goProfiles Vignette" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/goProfiles/inst/doc/goProfiles.R" ] }, "GOSemSim": { "Package": "GOSemSim", "Version": "2.0.4", "Depends": [ "R (>= 3.3.0)" ], "Imports": [ "AnnotationDbi", "GO.db", "methods", "utils" ], "LinkingTo": [ "Rcpp" ], "Suggests": [ "AnnotationHub", "BiocInstaller", "BiocStyle", "clusterProfiler", "DOSE", "knitr", "org.Hs.eg.db", "testthat" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "141cefa151503670e62bfdf3a8353a4b", "NeedsCompilation": "yes", "Title": "GO-terms Semantic Similarity Measures", "Description": "The semantic comparisons of Gene Ontology (GO) annotations provide quantitative ways to compute similarities between genes and gene groups, and have became important basis for many bioinformatics analysis approaches. GOSemSim is an R package for semantic similarity computation among GO terms, sets of GO terms, gene products and gene clusters. GOSemSim implemented five methods proposed by Resnik, Schlicker, Jiang, Lin and Wang respectively.", "biocViews": [ "Annotation", "Clustering", "GO", "Network", "Pathways", "Software" ], "Author": "Guangchuang Yu with contributions from Alexey Stukalov and Chuanle Xiao.", "Maintainer": "Guangchuang Yu ", "URL": "https://guangchuangyu.github.io/GOSemSim", "VignetteBuilder": "knitr", "BugReports": "https://github.com/GuangchuangYu/GOSemSim/issues", "source.ver": "src/contrib/GOSemSim_2.0.4.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GOSemSim_2.0.4.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GOSemSim_2.0.4.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GOSemSim_2.0.4.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GOSemSim/inst/doc/GOSemSim.R" ], "htmlDocs": [ "vignettes/GOSemSim/inst/doc/GOSemSim.html" ], "htmlTitles": [ "An introduction to GOSemSim" ], "dependsOnMe": [ "tRanslatome" ], "importsMe": [ "clusterProfiler", "DOSE", "meshes", "Rcpi" ], "suggestsMe": [ "SemDist" ] }, "goseq": { "Package": "goseq", "Version": "1.26.0", "Depends": [ "R (>= 2.11.0)", "BiasedUrn", "geneLenDataBase (>= 1.9.2)" ], "Imports": [ "mgcv", "graphics", "stats", "utils", "AnnotationDbi", "GO.db", "BiocGenerics" ], "Suggests": [ "edgeR", "org.Hs.eg.db", "rtracklayer" ], "License": "LGPL (>= 2)", "MD5sum": "da46e940cc1cf1f624a06c908f07f910", "NeedsCompilation": "no", "Title": "Gene Ontology analyser for RNA-seq and other length biased data", "Description": "Detects Gene Ontology and/or other user defined categories which are over/under represented in RNA-seq data", "biocViews": [ "GO", "GeneExpression", "RNASeq", "Sequencing", "Software", "Transcription" ], "Author": "Matthew Young", "Maintainer": "Nadia Davidson , Anthony Hawkins ", "source.ver": "src/contrib/goseq_1.26.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/goseq_1.26.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/goseq_1.26.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/goseq_1.26.0.tgz", "vignettes": [ "vignettes/goseq/inst/doc/goseq.pdf" ], "vignetteTitles": [ "goseq User's Guide" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/goseq/inst/doc/goseq.R" ], "dependsOnMe": [ "rgsepd" ], "importsMe": [ "ChAMP", "SMITE" ], "suggestsMe": [ "oneChannelGUI" ] }, "GOSim": { "Package": "GOSim", "Version": "1.12.0", "Depends": [ "GO.db", "annotate" ], "Imports": [ "org.Hs.eg.db", "AnnotationDbi", "topGO", "cluster", "flexmix", "RBGL", "graph", "Matrix", "corpcor", "Rcpp" ], "LinkingTo": [ "Rcpp" ], "Enhances": [ "igraph" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "3e935c538ec173ca4827f44e1e6699ef", "NeedsCompilation": "yes", "Title": "Computation of functional similarities between GO terms and gene products; GO enrichment analysis", "Description": "This package implements several functions useful for computing similarities between GO terms and gene products based on their GO annotation. Moreover it allows for computing a GO enrichment analysis", "biocViews": [ "Clustering", "GO", "Pathways", "Software" ], "Author": "Holger Froehlich ", "Maintainer": "Holger Froehlich ", "source.ver": "src/contrib/GOSim_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GOSim_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GOSim_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GOSim_1.12.0.tgz", "vignettes": [ "vignettes/GOSim/inst/doc/GOSim.pdf" ], "vignetteTitles": [ "GOsim" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GOSim/inst/doc/GOSim.R" ] }, "GOstats": { "Package": "GOstats", "Version": "2.40.0", "Depends": [ "R (>= 2.10)", "Biobase (>= 1.15.29)", "Category (>= 2.3.26)", "graph" ], "Imports": [ "methods", "stats", "stats4", "AnnotationDbi (>= 0.0.89)", "Biobase (>= 1.15.29)", "Category (>= 2.3.26)", "GO.db (>= 1.13.0)", "RBGL", "annotate (>= 1.13.2)", "graph (>= 1.15.15)", "AnnotationForge" ], "Suggests": [ "hgu95av2.db (>= 1.13.0)", "ALL", "GO.db (>= 1.13.0)", "annotate", "multtest", "genefilter", "RColorBrewer", "Rgraphviz", "xtable", "SparseM", "GSEABase", "geneplotter", "org.Hs.eg.db", "RUnit", "BiocGenerics" ], "License": "Artistic-2.0", "MD5sum": "c9f869cf6389715d51a9918250d226f5", "NeedsCompilation": "no", "Title": "Tools for manipulating GO and microarrays.", "Description": "A set of tools for interacting with GO and microarray data. A variety of basic manipulation tools for graphs, hypothesis testing and other simple calculations.", "biocViews": [ "Annotation", "GO", "GeneExpression", "GeneSetEnrichment", "GraphAndNetwork", "Microarray", "MultipleComparison", "Pathways", "Software" ], "Author": "R. Gentleman and S. Falcon", "Maintainer": "Bioconductor Package Maintainer ", "source.ver": "src/contrib/GOstats_2.40.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GOstats_2.40.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GOstats_2.40.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GOstats_2.40.0.tgz", "vignettes": [ "vignettes/GOstats/inst/doc/GOstatsForUnsupportedOrganisms.pdf", "vignettes/GOstats/inst/doc/GOstatsHyperG.pdf", "vignettes/GOstats/inst/doc/GOvis.pdf" ], "vignetteTitles": [ "Hypergeometric tests for less common model organisms", "Hypergeometric Tests Using GOstats", "Visualizing Data Using GOstats" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GOstats/inst/doc/GOstatsForUnsupportedOrganisms.R", "vignettes/GOstats/inst/doc/GOstatsHyperG.R", "vignettes/GOstats/inst/doc/GOvis.R" ], "dependsOnMe": [ "MineICA", "RDAVIDWebService" ], "importsMe": [ "affycoretools", "attract", "categoryCompare", "facopy", "mvGST", "pcaExplorer", "ProCoNA", "ReportingTools", "systemPipeR" ], "suggestsMe": [ "BiocCaseStudies", "Category", "eisa", "fastLiquidAssociation", "GSEAlm", "HTSanalyzeR", "interactiveDisplay", "MineICA", "miRLAB", "MLP", "MmPalateMiRNA", "oneChannelGUI", "phenoDist", "qpgraph", "RnBeads", "safe" ] }, "GOsummaries": { "Package": "GOsummaries", "Version": "2.8.0", "Depends": [ "R (>= 2.15)", "Rcpp" ], "Imports": [ "plyr", "grid", "gProfileR", "reshape2", "limma", "ggplot2", "gtable" ], "LinkingTo": [ "Rcpp" ], "Suggests": [ "vegan" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "72d456c9ba0c8e1f1c4d5cec104b05e4", "NeedsCompilation": "yes", "Title": "Word cloud summaries of GO enrichment analysis", "Description": "A package to visualise Gene Ontology (GO) enrichment analysis results on gene lists arising from different analyses such clustering or PCA. The significant GO categories are visualised as word clouds that can be combined with different plots summarising the underlying data.", "biocViews": [ "Clustering", "GO", "GeneExpression", "Software", "Visualization" ], "Author": "Raivo Kolde ", "Maintainer": "Raivo Kolde ", "URL": "https://github.com/raivokolde/GOsummaries", "source.ver": "src/contrib/GOsummaries_2.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GOsummaries_2.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GOsummaries_2.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GOsummaries_2.8.0.tgz", "vignettes": [ "vignettes/GOsummaries/inst/doc/GOsummaries-basics.pdf" ], "vignetteTitles": [ "GOsummaries basics" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GOsummaries/inst/doc/GOsummaries-basics.R" ] }, "GOTHiC": { "Package": "GOTHiC", "Version": "1.10.0", "Depends": [ "R (>= 2.15.1)", "methods", "utils", "GenomicRanges", "Biostrings", "BSgenome", "data.table" ], "Imports": [ "BiocGenerics", "S4Vectors (>= 0.9.38)", "IRanges", "Rsamtools", "ShortRead", "rtracklayer", "ggplot2" ], "Suggests": [ "HiCDataLymphoblast" ], "Enhances": [ "parallel" ], "License": "GPL-3", "MD5sum": "869e35d51d80e3fd407a67971be42c10", "NeedsCompilation": "no", "Title": "Binomial test for Hi-C data analysis", "Description": "This is a Hi-C analysis package using a cumulative binomial test to detect interactions between distal genomic loci that have significantly more reads than expected by chance in Hi-C experiments. It takes mapped paired NGS reads as input and gives back the list of significant interactions for a given bin size in the genome.", "biocViews": [ "Epigenetics", "HiC", "Preprocessing", "Sequencing", "Software" ], "Author": "Borbala Mifsud and Robert Sugar", "Maintainer": "Borbala Mifsud ", "source.ver": "src/contrib/GOTHiC_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GOTHiC_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GOTHiC_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GOTHiC_1.10.0.tgz", "vignettes": [ "vignettes/GOTHiC/inst/doc/package_vignettes.pdf" ], "vignetteTitles": [ "package_vignettes.pdf" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GOTHiC/inst/doc/package_vignettes.R" ], "suggestsMe": [ "HiCDataLymphoblast" ] }, "goTools": { "Package": "goTools", "Version": "1.48.0", "Depends": [ "GO.db" ], "Imports": [ "AnnotationDbi", "GO.db", "graphics", "grDevices" ], "Suggests": [ "hgu133a.db" ], "License": "GPL-2", "MD5sum": "ea446de381d743a87c7c79590c26854e", "NeedsCompilation": "no", "Title": "Functions for Gene Ontology database", "Description": "Wraper functions for description/comparison of oligo ID list using Gene Ontology database", "biocViews": [ "GO", "Microarray", "Software", "Visualization" ], "Author": "Yee Hwa (Jean) Yang , Agnes Paquet ", "Maintainer": "Agnes Paquet ", "source.ver": "src/contrib/goTools_1.48.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/goTools_1.48.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/goTools_1.48.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/goTools_1.48.0.tgz", "vignettes": [ "vignettes/goTools/inst/doc/goTools.pdf" ], "vignetteTitles": [ "goTools overview" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/goTools/inst/doc/goTools.R" ] }, "gpls": { "Package": "gpls", "Version": "1.46.0", "Imports": [ "stats" ], "Suggests": [ "MASS" ], "License": "Artistic-2.0", "MD5sum": "6e7dab804c99bc5ba50a34aa869f39a4", "NeedsCompilation": "no", "Title": "Classification using generalized partial least squares", "Description": "Classification using generalized partial least squares for two-group and multi-group (more than 2 group) classification.", "biocViews": [ "Classification", "Microarray", "Regression", "Software" ], "Author": "Beiying Ding", "Maintainer": "Bioconductor Package Maintainer ", "source.ver": "src/contrib/gpls_1.46.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/gpls_1.46.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/gpls_1.46.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/gpls_1.46.0.tgz", "vignettes": [ "vignettes/gpls/inst/doc/gpls.pdf" ], "vignetteTitles": [ "gpls Tutorial" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/gpls/inst/doc/gpls.R" ], "suggestsMe": [ "MCRestimate", "MLInterfaces" ] }, "gprege": { "Package": "gprege", "Version": "1.18.0", "Depends": [ "R (>= 2.10)", "gptk" ], "Suggests": [ "spam" ], "License": "AGPL-3", "MD5sum": "6774b553a69b0a2fe23b24e350196c50", "NeedsCompilation": "no", "Title": "Gaussian Process Ranking and Estimation of Gene Expression time-series", "Description": "The gprege package implements the methodology described in Kalaitzis & Lawrence (2011) \"A simple approach to ranking differentially expressed gene expression time-courses through Gaussian process regression\". The software fits two GPs with the an RBF (+ noise diagonal) kernel on each profile. One GP kernel is initialised wih a short lengthscale hyperparameter, signal variance as the observed variance and a zero noise variance. It is optimised via scaled conjugate gradients (netlab). A second GP has fixed hyperparameters: zero inverse-width, zero signal variance and noise variance as the observed variance. The log-ratio of marginal likelihoods of the two hypotheses acts as a score of differential expression for the profile. Comparison via ROC curves is performed against BATS (Angelini et.al, 2007). A detailed discussion of the ranking approach and dataset used can be found in the paper (http://www.biomedcentral.com/1471-2105/12/180).", "biocViews": [ "Bioinformatics", "DifferentialExpression", "Microarray", "Preprocessing", "Software", "TimeCourse" ], "Author": "Alfredo Kalaitzis ", "Maintainer": "Alfredo Kalaitzis ", "BugReports": "alkalait@gmail.com", "source.ver": "src/contrib/gprege_1.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/gprege_1.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/gprege_1.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/gprege_1.18.0.tgz", "vignettes": [ "vignettes/gprege/inst/doc/gprege_quick.pdf" ], "vignetteTitles": [ "gprege Quick Guide" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/gprege/inst/doc/gprege_quick.R" ] }, "gQTLBase": { "Package": "gQTLBase", "Version": "1.6.0", "Imports": [ "GenomicRanges", "methods", "BatchJobs", "BBmisc", "S4Vectors", "BiocGenerics", "foreach", "doParallel", "bit", "ff", "rtracklayer", "ffbase", "GenomicFiles", "SummarizedExperiment" ], "Suggests": [ "geuvStore2", "knitr", "rmarkdown", "BiocStyle", "RUnit", "GGtools", "Homo.sapiens", "IRanges", "erma", "GenomeInfoDb", "gwascat", "geuvPack" ], "License": "Artistic-2.0", "MD5sum": "3a4fb5ce044ead87367a07b23eb5e5a9", "NeedsCompilation": "no", "Title": "gQTLBase: infrastructure for eQTL, mQTL and similar studies", "Description": "Infrastructure for eQTL, mQTL and similar studies.", "Author": "VJ Carey ", "Maintainer": "VJ Carey ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/gQTLBase_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/gQTLBase_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/gQTLBase_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/gQTLBase_1.6.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/gQTLBase/inst/doc/gQTLBase.R" ], "htmlDocs": [ "vignettes/gQTLBase/inst/doc/gQTLBase.html" ], "htmlTitles": [ "gQTLBase infrastructure for eQTL archives" ], "importsMe": [ "geuvStore2", "gQTLstats" ], "biocViews": [ "Software" ], "dependsOnMe": [ "yriMulti" ] }, "gQTLstats": { "Package": "gQTLstats", "Version": "1.6.0", "Depends": [ "R (>= 3.1.0)" ], "Imports": [ "methods", "snpStats", "BiocGenerics", "S4Vectors (>= 0.9.25)", "IRanges", "GenomeInfoDb", "GenomicFiles", "GenomicRanges", "SummarizedExperiment", "VariantAnnotation", "Biobase", "BatchJobs", "gQTLBase", "limma", "mgcv", "dplyr", "AnnotationDbi", "GenomicFeatures", "ggplot2", "reshape2", "doParallel", "foreach", "ffbase", "BBmisc", "beeswarm" ], "Suggests": [ "geuvPack", "geuvStore2", "Rsamtools", "knitr", "rmarkdown", "ggbio", "BiocStyle", "Homo.sapiens", "RUnit", "multtest" ], "License": "Artistic-2.0", "MD5sum": "44166e79333f176ad5dee09c14dd8375", "NeedsCompilation": "no", "Title": "gQTLstats: computationally efficient analysis for eQTL and allied studies", "Description": "computationally efficient analysis of eQTL, mQTL, dsQTL, etc.", "Author": "VJ Carey ", "Maintainer": "VJ Carey ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/gQTLstats_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/gQTLstats_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/gQTLstats_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/gQTLstats_1.6.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/gQTLstats/inst/doc/gQTLstats.R" ], "htmlDocs": [ "vignettes/gQTLstats/inst/doc/gQTLstats.html" ], "htmlTitles": [ "gQTLstats: statistics for genetics of genomic features" ], "importsMe": [ "gwascat" ], "biocViews": [ "Software" ] }, "graph": { "Package": "graph", "Version": "1.52.0", "Depends": [ "R (>= 2.10)", "methods", "BiocGenerics (>= 0.13.11)" ], "Imports": [ "stats", "stats4", "utils" ], "Suggests": [ "SparseM (>= 0.36)", "XML", "RBGL", "RUnit", "cluster" ], "Enhances": [ "Rgraphviz" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "a2f2cf1b4b83208e9746770bd2f5b925", "NeedsCompilation": "yes", "Title": "graph: A package to handle graph data structures", "Description": "A package that implements some simple graph handling capabilities.", "biocViews": [ "GraphAndNetwork", "Software" ], "Author": "R. Gentleman, Elizabeth Whalen, W. Huber, S. Falcon", "Maintainer": "Bioconductor Package Maintainer ", "source.ver": "src/contrib/graph_1.52.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/graph_1.52.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/graph_1.52.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/graph_1.52.0.tgz", "vignettes": [ "vignettes/graph/inst/doc/clusterGraph.pdf", "vignettes/graph/inst/doc/graph.pdf", "vignettes/graph/inst/doc/graphAttributes.pdf", "vignettes/graph/inst/doc/GraphClass.pdf", "vignettes/graph/inst/doc/MultiGraphClass.pdf" ], "vignetteTitles": [ "clusterGraph and distGraph", "Graph", "Attributes for Graph Objects", "Graph Design", "graphBAM and MultiGraph classes" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/graph/inst/doc/clusterGraph.R", "vignettes/graph/inst/doc/graph.R", "vignettes/graph/inst/doc/graphAttributes.R", "vignettes/graph/inst/doc/GraphClass.R", "vignettes/graph/inst/doc/MultiGraphClass.R" ], "dependsOnMe": [ "apComplex", "biocGraph", "BioMVCClass", "BioNet", "CellNOptR", "clipper", "CNORfeeder", "ddgraph", "FEM", "flowMerge", "gaggle", "gaucho", "GOFunction", "GOstats", "GraphAT", "GSEABase", "hypergraph", "keggorthology", "maigesPack", "MineICA", "NCIgraph", "NetSAM", "pathRender", "Pigengene", "pkgDepTools", "ppiData", "RbcBook1", "RBGL", "RBioinf", "RCy3", "RCyjs", "RCytoscape", "RDAVIDWebService", "Rgraphviz", "ROntoTools", "RpsiXML", "SNAData", "SRAdb", "ToPASeq", "topGO", "vtpnet", "yeastExpData" ], "importsMe": [ "alpine", "AnalysisPageServer", "BgeeDB", "BiocCheck", "biocGraph", "biocViews", "CAMERA", "Category", "categoryCompare", "ChIPpeakAnno", "CHRONOS", "CytoML", "DEGraph", "DEsubs", "EnrichmentBrowser", "FEM", "flowCL", "flowClust", "flowCore", "flowUtils", "flowWorkspace", "gage", "GeneNetworkBuilder", "GENESIS", "GOFunction", "GOSim", "GOstats", "GraphAT", "graphite", "gwascat", "HTSanalyzeR", "hyperdraw", "KEGGgraph", "keggorthology", "keggorthology", "mirIntegrator", "mvGST", "NCIgraph", "nem", "netresponse", "OncoSimulR", "openCyto", "OrganismDbi", "pathview", "PCpheno", "pkgDepTools", "ppiStats", "qpgraph", "RamiGO", "RchyOptimyx", "RGraph2js", "rsbml", "Rtreemix", "SplicingGraphs", "Streamer", "VariantFiltering" ], "suggestsMe": [ "AnnotationDbi", "BiocCaseStudies", "DEGraph", "EBcoexpress", "ecolitk", "GeneAnswers", "KEGGlincs", "mmnet", "MmPalateMiRNA", "netbenchmark", "NetPathMiner", "rBiopaxParser", "rTRM", "S4Vectors", "SPIA", "VariantTools" ] }, "GraphAlignment": { "Package": "GraphAlignment", "Version": "1.38.0", "License": "file LICENSE", "License_restricts_use": "yes", "Archs": "i386, x64", "MD5sum": "67111cf057ef90d879092c030247a170", "NeedsCompilation": "yes", "Title": "GraphAlignment", "Description": "Graph alignment is an extension package for the R programming environment which provides functions for finding an alignment between two networks based on link and node similarity scores. (J. Berg and M. Laessig, \"Cross-species analysis of biological networks by Bayesian alignment\", PNAS 103 (29), 10967-10972 (2006))", "biocViews": [ "GraphAndNetwork", "Network", "Software" ], "Author": "Joern P. Meier , Michal Kolar, Ville Mustonen, Michael Laessig, and Johannes Berg.", "Maintainer": "Joern P. Meier ", "URL": "http://www.thp.uni-koeln.de/~berg/GraphAlignment/", "source.ver": "src/contrib/GraphAlignment_1.38.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GraphAlignment_1.38.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GraphAlignment_1.38.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GraphAlignment_1.38.0.tgz", "vignettes": [ "vignettes/GraphAlignment/inst/doc/GraphAlignment.pdf" ], "vignetteTitles": [ "GraphAlignment" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/GraphAlignment/inst/doc/GraphAlignment.R" ] }, "GraphAT": { "Package": "GraphAT", "Version": "1.46.0", "Depends": [ "R (>= 2.10)", "graph", "methods" ], "Imports": [ "graph", "MCMCpack", "methods", "stats" ], "License": "LGPL", "MD5sum": "d1aef590af9bcce1c647737a27d93c11", "NeedsCompilation": "no", "Title": "Graph Theoretic Association Tests", "Description": "Functions and data used in Balasubramanian, et al. (2004)", "biocViews": [ "GraphAndNetwork", "Network", "Software" ], "Author": "R. Balasubramanian, T. LaFramboise, D. Scholtens", "Maintainer": "Thomas LaFramboise ", "source.ver": "src/contrib/GraphAT_1.46.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GraphAT_1.46.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GraphAT_1.46.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GraphAT_1.46.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false }, "graphite": { "Package": "graphite", "Version": "1.20.1", "Depends": [ "R (>= 2.10)", "methods" ], "Imports": [ "AnnotationDbi", "graph", "stats", "utils", "rappdirs" ], "Suggests": [ "BiocStyle", "hgu133plus2.db", "org.Hs.eg.db", "SPIA (>= 2.2)", "topologyGSA (>= 1.4.0)", "clipper", "ALL", "testthat" ], "Enhances": [ "DEGraph", "RCytoscape", "RCy3" ], "License": "AGPL-3", "MD5sum": "e4b11c02b3a48deb27010df060bad612", "NeedsCompilation": "no", "Title": "GRAPH Interaction from pathway Topological Environment", "Description": "Graph objects from pathway topology derived from Biocarta, HumanCyc, KEGG, NCI, Panther, Reactome and SPIKE databases.", "biocViews": [ "BioCarta", "GraphAndNetwork", "KEGG", "Network", "Pathways", "Reactome", "Software", "ThirdPartyClient" ], "Author": "Gabriele Sales , Enrica Calura , Chiara Romualdi ", "Maintainer": "Gabriele Sales ", "source.ver": "src/contrib/graphite_1.20.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/graphite_1.20.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/graphite_1.20.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/graphite_1.20.1.tgz", "vignettes": [ "vignettes/graphite/inst/doc/graphite.pdf" ], "vignetteTitles": [ "GRAPH Interaction from pathway Topological Environment" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/graphite/inst/doc/graphite.R" ], "dependsOnMe": [ "ToPASeq" ], "importsMe": [ "facopy", "mogsa", "ReactomePA" ], "suggestsMe": [ "clipper" ] }, "GraphPAC": { "Package": "GraphPAC", "Version": "1.16.0", "Depends": [ "R(>= 2.15)", "iPAC", "igraph", "TSP", "RMallow" ], "Suggests": [ "RUnit", "BiocGenerics" ], "License": "GPL-2", "MD5sum": "49bba41d38362739facbe258f3d42b7a", "NeedsCompilation": "no", "Title": "Identification of Mutational Clusters in Proteins via a Graph Theoretical Approach.", "Description": "Identifies mutational clusters of amino acids in a protein while utilizing the proteins tertiary structure via a graph theoretical model.", "biocViews": [ "Clustering", "Proteomics", "Software" ], "Author": "Gregory Ryslik, Hongyu Zhao", "Maintainer": "Gregory Ryslik ", "source.ver": "src/contrib/GraphPAC_1.16.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GraphPAC_1.16.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GraphPAC_1.16.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GraphPAC_1.16.0.tgz", "vignettes": [ "vignettes/GraphPAC/inst/doc/GraphPAC.pdf" ], "vignetteTitles": [ "iPAC: identification of Protein Amino acid Mutations" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GraphPAC/inst/doc/GraphPAC.R" ], "dependsOnMe": [ "QuartPAC" ] }, "GRENITS": { "Package": "GRENITS", "Version": "1.26.0", "Depends": [ "R (>= 2.12.0)", "Rcpp (>= 0.8.6)", "RcppArmadillo (>= 0.2.8)", "ggplot2 (>= 0.9.0)" ], "Imports": [ "graphics", "grDevices", "reshape2", "stats", "utils" ], "LinkingTo": [ "Rcpp", "RcppArmadillo" ], "Suggests": [ "network" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "0b7ce1ee89c32fb37eef16ea576c920f", "NeedsCompilation": "yes", "Title": "Gene Regulatory Network Inference Using Time Series", "Description": "The package offers four network inference statistical models using Dynamic Bayesian Networks and Gibbs Variable Selection: a linear interaction model, two linear interaction models with added experimental noise (Gaussian and Student distributed) for the case where replicates are available and a non-linear interaction model.", "biocViews": [ "Bayesian", "GeneExpression", "GeneRegulation", "GraphAndNetwork", "Network", "NetworkInference", "Software", "TimeCourse" ], "Author": "Edward Morrissey", "Maintainer": "Edward Morrissey ", "source.ver": "src/contrib/GRENITS_1.26.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GRENITS_1.26.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GRENITS_1.26.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GRENITS_1.26.0.tgz", "vignettes": [ "vignettes/GRENITS/inst/doc/GRENITS_package.pdf" ], "vignetteTitles": [ "GRENITS" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GRENITS/inst/doc/GRENITS_package.R" ] }, "GreyListChIP": { "Package": "GreyListChIP", "Version": "1.6.0", "Depends": [ "R (>= 3.1)", "methods", "GenomicRanges" ], "Imports": [ "GenomicAlignments", "BSgenome", "Rsamtools", "rtracklayer", "MASS", "parallel", "GenomeInfoDb", "SummarizedExperiment" ], "Suggests": [ "BiocStyle", "BiocGenerics", "RUnit" ], "Enhances": [ "BSgenome.Hsapiens.UCSC.hg19" ], "License": "Artistic-2.0", "MD5sum": "64341fba467a524d659cd37bc0408888", "NeedsCompilation": "no", "Title": "Grey Lists -- Mask Artefact Regions Based on ChIP Inputs", "Description": "Identify regions of ChIP experiments with high signal in the input, that lead to spurious peaks during peak calling. Remove reads aligning to these regions prior to peak calling, for cleaner ChIP analysis.", "biocViews": [ "Alignment", "ChIPSeq", "Coverage", "DifferentialPeakCalling", "GenomeAnnotation", "Preprocessing", "Sequencing", "Software" ], "Author": "Gord Brown ", "Maintainer": "Gordon Brown ", "source.ver": "src/contrib/GreyListChIP_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GreyListChIP_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GreyListChIP_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GreyListChIP_1.6.0.tgz", "vignettes": [ "vignettes/GreyListChIP/inst/doc/GreyList-demo.pdf" ], "vignetteTitles": [ "Generating Grey Lists from Input Libraries" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GreyListChIP/inst/doc/GreyList-demo.R" ] }, "GRmetrics": { "Package": "GRmetrics", "Version": "1.0.0", "Depends": [ "R (>= 3.3)", "SummarizedExperiment" ], "Imports": [ "drc", "plotly", "ggplot2", "S4Vectors" ], "Suggests": [ "knitr", "rmarkdown", "BiocStyle" ], "License": "GPL-3", "MD5sum": "86b0296bc0a36825ddc5c3c728c58e69", "NeedsCompilation": "no", "Title": "Calculate growth-rate inhibition (GR) metrics", "Description": "Functions for calculating and visualizing growth-rate inhibition (GR) metrics.", "biocViews": [ "CellBasedAssays", "CellBiology", "Software", "TimeCourse", "Visualization" ], "Author": "Nicholas Clark", "Maintainer": "Nicholas Clark ", "URL": "https://github.com/uc-bd2k/GRmetrics", "VignetteBuilder": "knitr", "BugReports": "https://github.com/uc-bd2k/GRmetrics/issues", "source.ver": "src/contrib/GRmetrics_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GRmetrics_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GRmetrics_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GRmetrics_1.0.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GRmetrics/inst/doc/GRmetrics-vignette.R" ], "htmlDocs": [ "vignettes/GRmetrics/inst/doc/GRmetrics-vignette.html" ], "htmlTitles": [ "GRmetrics: an R package for calculation and visualization of Growth Rate Metrics" ] }, "groHMM": { "Package": "groHMM", "Version": "1.8.0", "Depends": [ "R (>= 3.0.2)", "MASS", "parallel", "S4Vectors (>= 0.9.25)", "IRanges (>= 2.5.27)", "GenomeInfoDb", "GenomicRanges (>= 1.23.16)", "GenomicAlignments", "rtracklayer" ], "Suggests": [ "BiocStyle", "GenomicFeatures", "edgeR", "org.Hs.eg.db", "TxDb.Hsapiens.UCSC.hg19.knownGene" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "6837136b45f0b8fed4d0c0f2b4388929", "NeedsCompilation": "yes", "Title": "GRO-seq Analysis Pipeline", "Description": "A pipeline for the analysis of GRO-seq data.", "biocViews": [ "Sequencing", "Software" ], "Author": "Charles G. Danko, Minho Chae, Andre Martins, W. Lee Kraus", "Maintainer": "Anusha Nagari , Venkat Malladi , Tulip Nandu , W. Lee Kraus ", "URL": "https://github.com/Kraus-Lab/groHMM", "BugReports": "https://github.com/Kraus-Lab/groHMM/issues", "source.ver": "src/contrib/groHMM_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/groHMM_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/groHMM_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/groHMM_1.8.0.tgz", "vignettes": [ "vignettes/groHMM/inst/doc/groHMM.pdf" ], "vignetteTitles": [ "groHMM tutorial" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/groHMM/inst/doc/groHMM.R" ] }, "GSALightning": { "Package": "GSALightning", "Version": "1.2.0", "Depends": [ "R (>= 3.3.0)" ], "Imports": [ "Matrix", "data.table", "stats" ], "Suggests": [ "knitr", "rmarkdown" ], "License": "GPL (>=2)", "MD5sum": "ebbcd6587fa1d37ee13ce2a5916514a4", "NeedsCompilation": "no", "Title": "Fast Permutation-based Gene Set Analysis", "Description": "GSALightning provides a fast implementation of permutation-based gene set analysis for two-sample problem. This package is particularly useful when testing simultaneously a large number of gene sets, or when a large number of permutations is necessary for more accurate p-values estimation.", "biocViews": [ "BiologicalQuestion", "DifferentialExpression", "GeneExpression", "GeneSetEnrichment", "Software", "Transcription" ], "Author": "Billy Heung Wing Chang", "Maintainer": "Billy Heung Wing Chang ", "URL": "https://github.com/billyhw/GSALightning", "VignetteBuilder": "knitr", "BugReports": "https://github.com/billyhw/GSALightning/issues", "source.ver": "src/contrib/GSALightning_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GSALightning_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GSALightning_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GSALightning_1.2.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/GSALightning/inst/doc/vignette.R" ], "htmlDocs": [ "vignettes/GSALightning/inst/doc/vignette.html" ], "htmlTitles": [ "Vignette Title" ] }, "GSAR": { "Package": "GSAR", "Version": "1.8.0", "Depends": [ "R (>= 3.0.1)", "igraph (>= 0.7.1)" ], "Imports": [ "stats", "graphics" ], "Suggests": [ "MASS", "GSVAdata", "ALL", "tweeDEseqCountData", "GSEABase", "annotate", "org.Hs.eg.db", "Biobase", "genefilter", "hgu95av2.db", "edgeR", "BiocStyle" ], "License": "GPL (>=2)", "MD5sum": "36ed86c5072a25cc452e83e3aeae400c", "NeedsCompilation": "no", "Title": "Gene Set Analysis in R", "Description": "Gene set analysis using specific alternative hypotheses. Tests for differential expression, scale and net correlation structure.", "biocViews": [ "DifferentialExpression", "Software", "StatisticalMethod" ], "Author": "Yasir Rahmatallah , Galina Glazko ", "Maintainer": "Yasir Rahmatallah , Galina Glazko ", "source.ver": "src/contrib/GSAR_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GSAR_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GSAR_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GSAR_1.8.0.tgz", "vignettes": [ "vignettes/GSAR/inst/doc/GSAR.pdf" ], "vignetteTitles": [ "Gene Set Analysis in R -- the GSAR Package" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GSAR/inst/doc/GSAR.R" ] }, "GSCA": { "Package": "GSCA", "Version": "2.4.0", "Depends": [ "shiny", "sp", "gplots", "ggplot2", "reshape2", "RColorBrewer", "rhdf5", "R(>= 2.10.0)" ], "Imports": [ "graphics" ], "Suggests": [ "Affyhgu133aExpr", "Affymoe4302Expr", "Affyhgu133A2Expr", "Affyhgu133Plus2Expr" ], "License": "GPL(>=2)", "MD5sum": "21731e41436c02df1da418a9df132042", "NeedsCompilation": "no", "Title": "GSCA: Gene Set Context Analysis", "Description": "GSCA takes as input several lists of activated and repressed genes. GSCA then searches through a compendium of publicly available gene expression profiles for biological contexts that are enriched with a specified pattern of gene expression. GSCA provides both traditional R functions and interactive, user-friendly user interface.", "biocViews": [ "GUI", "GeneExpression", "Software", "Visualization" ], "Author": "Zhicheng Ji, Hongkai Ji", "Maintainer": "Zhicheng Ji ", "source.ver": "src/contrib/GSCA_2.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GSCA_2.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GSCA_2.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GSCA_2.4.0.tgz", "vignettes": [ "vignettes/GSCA/inst/doc/GSCA.pdf" ], "vignetteTitles": [ "GSCA" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GSCA/inst/doc/GSCA.R" ] }, "GSEABase": { "Package": "GSEABase", "Version": "1.36.0", "Depends": [ "R (>= 2.6.0)", "BiocGenerics (>= 0.13.8)", "Biobase (>= 2.17.8)", "annotate (>= 1.45.3)", "methods", "graph (>= 1.37.2)" ], "Imports": [ "AnnotationDbi", "XML" ], "Suggests": [ "hgu95av2.db", "GO.db", "org.Hs.eg.db", "Rgraphviz", "ReportingTools" ], "License": "Artistic-2.0", "MD5sum": "03945b4d71555e5429e2c6db1ee90e2d", "NeedsCompilation": "no", "Title": "Gene set enrichment data structures and methods", "Description": "This package provides classes and methods to support Gene Set Enrichment Analysis (GSEA).", "biocViews": [ "GO", "GeneExpression", "GeneSetEnrichment", "GraphAndNetwork", "KEGG", "Software" ], "Author": "Martin Morgan, Seth Falcon, Robert Gentleman", "Maintainer": "Bioconductor Package Maintainer ", "source.ver": "src/contrib/GSEABase_1.36.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GSEABase_1.36.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GSEABase_1.36.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GSEABase_1.36.0.tgz", "vignettes": [ "vignettes/GSEABase/inst/doc/GSEABase.pdf" ], "vignetteTitles": [ "An introduction to GSEABase" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GSEABase/inst/doc/GSEABase.R" ], "dependsOnMe": [ "AGDEX", "BicARE", "CCPROMISE", "cpvSNP", "EnrichmentBrowser", "gCMAP", "GSVAdata", "npGSEA", "PROMISE", "splineTimeR" ], "importsMe": [ "canceR", "Category", "categoryCompare", "cellHTS2", "gCMAPWeb", "GSRI", "GSVA", "HTSanalyzeR", "mogsa", "oppar", "PCpheno", "phenoTest", "PROMISE", "ReportingTools" ], "suggestsMe": [ "BiocCaseStudies", "clusterProfiler", "gage", "GlobalAncova", "globaltest", "GOstats", "GSAR", "GSEAlm", "MAST", "PGSEA", "phenoTest" ] }, "GSEAlm": { "Package": "GSEAlm", "Version": "1.34.0", "Depends": [ "Biobase" ], "Suggests": [ "GSEABase", "Category", "multtest", "ALL", "annotate", "hgu95av2.db", "genefilter", "GOstats", "RColorBrewer" ], "License": "Artistic-2.0", "MD5sum": "d4685402971c72caaf2358d87d9cd557", "NeedsCompilation": "no", "Title": "Linear Model Toolset for Gene Set Enrichment Analysis", "Description": "Models and methods for fitting linear models to gene expression data, together with tools for computing and using various regression diagnostics.", "biocViews": [ "Microarray", "Software" ], "Author": "Assaf Oron, Robert Gentleman (with contributions from S. Falcon and Z. Jiang)", "Maintainer": "Assaf Oron ", "source.ver": "src/contrib/GSEAlm_1.34.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GSEAlm_1.34.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GSEAlm_1.34.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GSEAlm_1.34.0.tgz", "vignettes": [ "vignettes/GSEAlm/inst/doc/GSEAlm.pdf" ], "vignetteTitles": [ "Linear models in GSEA" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GSEAlm/inst/doc/GSEAlm.R" ], "importsMe": [ "canceR", "gCMAP" ] }, "GSReg": { "Package": "GSReg", "Version": "1.8.0", "Depends": [ "R (>= 2.13.1)" ], "Suggests": [ "GSBenchMark" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "b611fa56229887e67da759ffbc4c9301", "NeedsCompilation": "yes", "Title": "Gene Set Regulation (GS-Reg)", "Description": "A package for gene set analysis based on the variability of expressions. It implements DIfferential RAnk Conservation (DIRAC) and gene set Expression Variation Analysis (EVA) methods.", "biocViews": [ "GeneExpression", "GeneRegulation", "GeneSetEnrichment", "GeneticVariability", "Pathways", "Software" ], "Author": "Bahman Afsari , Elana J. Fertig ", "Maintainer": "Bahman Afsari ", "source.ver": "src/contrib/GSReg_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GSReg_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GSReg_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GSReg_1.8.0.tgz", "vignettes": [ "vignettes/GSReg/inst/doc/GSReg.pdf" ], "vignetteTitles": [ "Working with the GSReg package" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GSReg/inst/doc/GSReg.R" ] }, "GSRI": { "Package": "GSRI", "Version": "2.22.0", "Depends": [ "R (>= 2.14.2)", "fdrtool" ], "Imports": [ "methods", "graphics", "stats", "utils", "genefilter", "Biobase", "GSEABase", "les (>= 1.1.6)" ], "Suggests": [ "limma", "hgu95av2.db" ], "Enhances": [ "parallel" ], "License": "GPL-3", "MD5sum": "688bdb18d93a451b94d84be3ae9b6e8c", "NeedsCompilation": "no", "Title": "Gene Set Regulation Index", "Description": "The GSRI package estimates the number of differentially expressed genes in gene sets, utilizing the concept of the Gene Set Regulation Index (GSRI).", "biocViews": [ "DifferentialExpression", "GeneRegulation", "GeneSetEnrichment", "Microarray", "Software", "Transcription" ], "Author": "Julian Gehring, Kilian Bartholome, Clemens Kreutz, Jens Timmer", "Maintainer": "Julian Gehring ", "source.ver": "src/contrib/GSRI_2.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GSRI_2.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GSRI_2.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GSRI_2.22.0.tgz", "vignettes": [ "vignettes/GSRI/inst/doc/gsri.pdf" ], "vignetteTitles": [ "Introduction to the GSRI package: Estimating Regulatory Effects utilizing the Gene Set Regulation Index" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GSRI/inst/doc/gsri.R" ] }, "GSVA": { "Package": "GSVA", "Version": "1.22.4", "Depends": [ "R (>= 2.13.0)" ], "Imports": [ "methods", "BiocGenerics", "Biobase", "GSEABase (>= 1.17.4)" ], "Suggests": [ "limma", "RColorBrewer", "genefilter", "mclust", "edgeR", "snow", "parallel", "GSVAdata" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "a6193234fa6b2d0c809801fd230c5b07", "NeedsCompilation": "yes", "Title": "Gene Set Variation Analysis for microarray and RNA-seq data", "Description": "Gene Set Variation Analysis (GSVA) is a non-parametric, unsupervised method for estimating variation of gene set enrichment through the samples of a expression data set. GSVA performs a change in coordinate systems, transforming the data from a gene by sample matrix to a gene-set by sample matrix, thereby allowing the evaluation of pathway enrichment for each sample. This new matrix of GSVA enrichment scores facilitates applying standard analytical methods like functional enrichment, survival analysis, clustering, CNV-pathway analysis or cross-tissue pathway analysis, in a pathway-centric manner.", "biocViews": [ "GeneSetEnrichment", "Microarray", "Pathways", "Software" ], "Author": "Justin Guinney [aut, cre], Robert Castelo [aut]", "Maintainer": "Justin Guinney ", "URL": "http://www.sagebase.org", "source.ver": "src/contrib/GSVA_1.22.4.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GSVA_1.22.4.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GSVA_1.22.4.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GSVA_1.22.4.tgz", "vignettes": [ "vignettes/GSVA/inst/doc/GSVA.pdf" ], "vignetteTitles": [ "Gene Set Variation Analysis" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GSVA/inst/doc/GSVA.R" ], "importsMe": [ "EGSEA", "oppar" ], "dependsOnMe": [ "SISPA" ] }, "gtrellis": { "Package": "gtrellis", "Version": "1.6.0", "Depends": [ "R (>= 3.1.2)", "grid", "IRanges", "GenomicRanges" ], "Imports": [ "circlize (>= 0.3.3)", "GetoptLong" ], "Suggests": [ "testthat (>= 1.0.0)", "knitr", "RColorBrewer", "markdown", "ComplexHeatmap (>= 1.9.7)" ], "License": "GPL (>= 2)", "MD5sum": "65429167b161555d18a312d0a8e3e970", "NeedsCompilation": "no", "Title": "Genome Level Trellis Layout", "Description": "Genome level Trellis graph visualizes genomic data conditioned by genomic categories (e.g. chromosomes). For each genomic category, multiple dimensional data which are represented as tracks describe different features from different aspects. This package provides high flexibility to arrange genomic categories and to add self-defined graphics in the plot.", "biocViews": [ "Sequencing", "Software", "Visualization" ], "Author": "Zuguang Gu", "Maintainer": "Zuguang Gu ", "URL": "https://github.com/jokergoo/gtrellis", "VignetteBuilder": "knitr", "source.ver": "src/contrib/gtrellis_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/gtrellis_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/gtrellis_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/gtrellis_1.6.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/gtrellis/inst/doc/gtrellis.R" ], "htmlDocs": [ "vignettes/gtrellis/inst/doc/gtrellis.html" ], "htmlTitles": [ "Make Genome-level Trellis Graph" ], "importsMe": [ "YAPSA" ] }, "GUIDEseq": { "Package": "GUIDEseq", "Version": "1.4.1", "Depends": [ "R (>= 3.2.0)", "GenomicRanges", "BiocGenerics" ], "Imports": [ "BiocParallel", "Biostrings", "CRISPRseek", "ChIPpeakAnno", "data.table", "matrixStats", "BSgenome", "parallel", "IRanges (>= 2.5.5)", "S4Vectors (>= 0.9.6)", "GenomicAlignments (>= 1.7.3)", "GenomeInfoDb", "Rsamtools", "hash", "limma" ], "Suggests": [ "knitr", "RUnit", "BiocStyle", "BSgenome.Hsapiens.UCSC.hg19", "TxDb.Hsapiens.UCSC.hg19.knownGene", "org.Hs.eg.db" ], "License": "GPL (>= 2)", "MD5sum": "c1789bce9552edc3c4f8208609290b59", "NeedsCompilation": "no", "Title": "GUIDE-seq analysis pipeline", "Description": "The package implements GUIDE-seq analysis workflow including functions for obtaining unique insertion sites (proxy of cleavage sites), estimating the locations of the insertion sites, aka, peaks, merging estimated insertion sites from plus and minus strand, and performing off target search of the extended regions around insertion sites.", "biocViews": [ "CRISPR", "GeneRegulation", "Sequencing", "Software", "WorkflowStep" ], "Author": "Lihua Julie Zhu, Michael Lawrence, Ankit Gupta, Alper Kucukural, Manuel Garber, Scot A. Wolfe", "Maintainer": "Lihua Julie Zhu ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/GUIDEseq_1.4.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GUIDEseq_1.4.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GUIDEseq_1.4.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GUIDEseq_1.4.1.tgz", "vignettes": [ "vignettes/GUIDEseq/inst/doc/GUIDEseq.pdf" ], "vignetteTitles": [ "GUIDEseq Vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GUIDEseq/inst/doc/GUIDEseq.R" ], "importsMe": [ "crisprseekplus" ] }, "Guitar": { "Package": "Guitar", "Version": "1.12.0", "Depends": [ "Rsamtools", "GenomicFeatures", "rtracklayer", "GenomicAlignments", "GenomicRanges", "ggplot2", "grid", "IRanges" ], "License": "GPL-2", "MD5sum": "8eb26e4117ef823e8ae6fee48f2077a7", "NeedsCompilation": "no", "Title": "Guitar", "Description": "The package is designed for visualization of RNA-related genomic features with respect to the landmarks of RNA transcripts, i.e., transcription starting site, start codon, stop codon and transcription ending site.", "biocViews": [ "Alignment", "Coverage", "DataImport", "MethylSeq", "QualityControl", "RNASeq", "Sequencing", "Software", "SplicedAlignment", "Transcription" ], "Author": "Jia Meng", "Maintainer": "Jia Meng ", "source.ver": "src/contrib/Guitar_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Guitar_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Guitar_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Guitar_1.12.0.tgz", "vignettes": [ "vignettes/Guitar/inst/doc/Guitar-Overview.pdf" ], "vignetteTitles": [ "Sample Guitar workflow" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Guitar/inst/doc/Guitar-Overview.R" ] }, "Gviz": { "Package": "Gviz", "Version": "1.18.2", "Depends": [ "R (>= 2.10.0)", "methods", "S4Vectors (>= 0.9.25)", "IRanges (>= 1.99.18)", "GenomicRanges (>= 1.17.20)", "grid" ], "Imports": [ "XVector (>= 0.5.7)", "rtracklayer (>= 1.25.13)", "lattice", "RColorBrewer", "biomaRt (>= 2.11.0)", "AnnotationDbi (>= 1.27.5)", "Biobase (>= 2.15.3)", "GenomicFeatures (>= 1.17.22)", "BSgenome (>= 1.33.1)", "Biostrings (>= 2.33.11)", "biovizBase (>= 1.13.8)", "Rsamtools (>= 1.17.28)", "latticeExtra (>= 0.6-26)", "matrixStats (>= 0.8.14)", "GenomicAlignments (>= 1.1.16)", "GenomeInfoDb (>= 1.1.3)", "BiocGenerics (>= 0.11.3)", "digest(>= 0.6.8)" ], "Suggests": [ "xtable", "BSgenome.Hsapiens.UCSC.hg19", "BiocStyle" ], "License": "Artistic-2.0", "MD5sum": "2da6170d79446a59331e61ecca534366", "NeedsCompilation": "no", "Title": "Plotting data and annotation information along genomic coordinates", "Description": "Genomic data analyses requires integrated visualization of known genomic information and new experimental data. Gviz uses the biomaRt and the rtracklayer packages to perform live annotation queries to Ensembl and UCSC and translates this to e.g. gene/transcript structures in viewports of the grid graphics package. This results in genomic information plotted together with your data.", "biocViews": [ "Microarray", "Software", "Visualization" ], "Author": "Florian Hahne, Steffen Durinck, Robert Ivanek, Arne Mueller, Steve Lianoglou, Ge Tan , Lance Parsons , Shraddha Pai ", "Maintainer": "Florian Hahne ", "source.ver": "src/contrib/Gviz_1.18.2.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Gviz_1.18.2.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Gviz_1.18.2.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Gviz_1.18.2.tgz", "vignettes": [ "vignettes/Gviz/inst/doc/Gviz.pdf" ], "vignetteTitles": [ "Gviz users guide" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Gviz/inst/doc/Gviz.R" ], "dependsOnMe": [ "ASpli", "biomvRCNS", "coMET", "cummeRbund", "DMRforPairs", "Pbase", "Pviz" ], "importsMe": [ "AllelicImbalance", "DMRcate", "GenomicInteractions", "GGtools", "gwascat", "InPAS", "methyAnalysis", "methylPipe", "motifbreakR", "PING", "SPLINTER", "STAN", "trackViewer", "VariantFiltering" ], "suggestsMe": [ "annmap", "CNEr", "DeepBlueR", "ensembldb", "GenomicRanges", "interactiveDisplay", "Pi", "pqsfinder", "QuasR", "RnBeads", "Single.mTEC.Transcriptomes", "SplicingGraphs" ] }, "gwascat": { "Package": "gwascat", "Version": "2.6.0", "Depends": [ "R (>= 3.0.0)", "Homo.sapiens" ], "Imports": [ "methods", "BiocGenerics", "S4Vectors (>= 0.9.25)", "IRanges", "GenomeInfoDb", "GenomicRanges", "snpStats", "Biostrings", "Rsamtools", "rtracklayer", "gQTLstats", "Gviz", "VariantAnnotation", "AnnotationHub", "AnnotationDbi", "GenomicFeatures", "graph", "ggbio", "ggplot2", "SummarizedExperiment" ], "Suggests": [ "DO.db", "DT", "utils", "knitr", "RBGL", "RUnit", "GGtools" ], "Enhances": [ "SNPlocs.Hsapiens.dbSNP144.GRCh37" ], "License": "Artistic-2.0", "MD5sum": "943b79820156dcfac9fa437599a1dcaa", "NeedsCompilation": "no", "Title": "representing and modeling data in the EMBL-EBI GWAS catalog", "Description": "Represent and model data in the EMBL-EBI GWAS catalog.", "biocViews": [ "Genetics", "Software" ], "Author": "VJ Carey ", "Maintainer": "VJ Carey ", "VignetteBuilder": "utils, knitr", "source.ver": "src/contrib/gwascat_2.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/gwascat_2.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/gwascat_2.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/gwascat_2.6.0.tgz", "vignettes": [ "vignettes/gwascat/inst/doc/gwascat.pdf" ], "vignetteTitles": [ "gwascat -- exploring NHGRI GWAS catalog" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/gwascat/inst/doc/gwascat.R", "vignettes/gwascat/inst/doc/gwascatOnt.R" ], "htmlDocs": [ "vignettes/gwascat/inst/doc/gwascatOnt.html" ], "htmlTitles": [ "gwascat: exploring GWAS results using the experimental factor ontology" ], "dependsOnMe": [ "vtpnet" ], "suggestsMe": [ "gQTLBase", "grasp2db" ] }, "GWASTools": { "Package": "GWASTools", "Version": "1.20.0", "Depends": [ "Biobase" ], "Imports": [ "graphics", "stats", "utils", "methods", "ncdf4", "gdsfmt", "DBI", "RSQLite", "GWASExactHW", "DNAcopy", "survival", "sandwich", "lmtest", "logistf", "quantsmooth" ], "Suggests": [ "GWASdata", "BiocGenerics", "RUnit", "SNPRelate", "snpStats", "VariantAnnotation" ], "License": "Artistic-2.0", "MD5sum": "7f1f46b997bad9cc1f71cc25ec932923", "NeedsCompilation": "no", "Title": "Tools for Genome Wide Association Studies", "Description": "Classes for storing very large GWAS data sets and annotation, and functions for GWAS data cleaning and analysis.", "biocViews": [ "GeneticVariability", "Microarray", "QualityControl", "SNP", "Software" ], "Author": "Stephanie M. Gogarten, Cathy Laurie, Tushar Bhangale, Matthew P. Conomos, Cecelia Laurie, Caitlin McHugh, Ian Painter, Xiuwen Zheng, Jess Shen, Rohit Swarnkar, Adrienne Stilp, Sarah Nelson", "Maintainer": "Stephanie M. Gogarten , Adrienne Stilp ", "source.ver": "src/contrib/GWASTools_1.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/GWASTools_1.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/GWASTools_1.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/GWASTools_1.20.0.tgz", "vignettes": [ "vignettes/GWASTools/inst/doc/Affymetrix.pdf", "vignettes/GWASTools/inst/doc/DataCleaning.pdf", "vignettes/GWASTools/inst/doc/Formats.pdf" ], "vignetteTitles": [ "Preparing Affymetrix Data", "GWAS Data Cleaning", "Data formats in GWASTools" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/GWASTools/inst/doc/Affymetrix.R", "vignettes/GWASTools/inst/doc/DataCleaning.R", "vignettes/GWASTools/inst/doc/Formats.R" ], "importsMe": [ "GENESIS" ], "suggestsMe": [ "podkat" ], "dependsOnMe": [ "GWASdata" ] }, "h5vc": { "Package": "h5vc", "Version": "2.8.1", "Depends": [ "grid", "gridExtra", "ggplot2" ], "Imports": [ "rhdf5", "reshape", "S4Vectors", "IRanges", "Biostrings", "Rsamtools (>= 1.19.38)", "methods", "GenomicRanges", "abind", "BiocParallel", "BatchJobs", "h5vcData", "GenomeInfoDb" ], "LinkingTo": [ "Rsamtools" ], "Suggests": [ "knitr", "locfit", "BSgenome.Hsapiens.UCSC.hg19", "bit64", "biomaRt", "BSgenome.Hsapiens.NCBI.GRCh38", "RUnit", "BiocGenerics" ], "License": "GPL (>= 3)", "Archs": "i386, x64", "MD5sum": "1a8a09aca75c6b87b51a24ede112d17e", "NeedsCompilation": "yes", "Title": "Managing alignment tallies using a hdf5 backend", "Description": "This package contains functions to interact with tally data from NGS experiments that is stored in HDF5 files.", "Author": "Paul Theodor Pyl", "Maintainer": "Paul Theodor Pyl ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/h5vc_2.8.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/h5vc_2.8.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/h5vc_2.8.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/h5vc_2.8.1.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/h5vc/inst/doc/h5vc.simple.genome.browser.R", "vignettes/h5vc/inst/doc/h5vc.tour.R" ], "htmlDocs": [ "vignettes/h5vc/inst/doc/h5vc.simple.genome.browser.html", "vignettes/h5vc/inst/doc/h5vc.tour.html" ], "htmlTitles": [ "Building a minimal genome browser with h5vc and shiny", "h5vc -- Tour" ], "biocViews": [ "Software" ], "suggestsMe": [ "h5vcData" ] }, "hapFabia": { "Package": "hapFabia", "Version": "1.16.1", "Depends": [ "R (>= 2.12.0)", "Biobase", "fabia (>= 2.3.1)" ], "Imports": [ "methods", "graphics", "grDevices", "stats", "utils" ], "License": "LGPL (>= 2.1)", "Archs": "i386, x64", "MD5sum": "9b195c8fc08115bac0276696bd67b936", "NeedsCompilation": "yes", "Title": "hapFabia: Identification of very short segments of identity by descent (IBD) characterized by rare variants in large sequencing data", "Description": "A package to identify very short IBD segments in large sequencing data by FABIA biclustering. Two haplotypes are identical by descent (IBD) if they share a segment that both inherited from a common ancestor. Current IBD methods reliably detect long IBD segments because many minor alleles in the segment are concordant between the two haplotypes. However, many cohort studies contain unrelated individuals which share only short IBD segments. This package provides software to identify short IBD segments in sequencing data. Knowledge of short IBD segments are relevant for phasing of genotyping data, association studies, and for population genetics, where they shed light on the evolutionary history of humans. The package supports VCF formats, is based on sparse matrix operations, and provides visualization of haplotype clusters in different formats.", "biocViews": [ "Clustering", "GeneticVariability", "Genetics", "SNP", "SequenceMatching", "Sequencing", "Software", "Visualization" ], "Author": "Sepp Hochreiter ", "Maintainer": "Sepp Hochreiter ", "URL": "http://www.bioinf.jku.at/software/hapFabia/hapFabia.html", "source.ver": "src/contrib/hapFabia_1.16.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/hapFabia_1.16.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/hapFabia_1.16.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/hapFabia_1.16.1.tgz", "vignettes": [ "vignettes/hapFabia/inst/doc/hapfabia.pdf" ], "vignetteTitles": [ "hapFabia: Manual for the R package" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/hapFabia/inst/doc/hapfabia.R" ] }, "Harman": { "Package": "Harman", "Version": "1.2.0", "Depends": [ "R (>= 3.3)" ], "Imports": [ "Rcpp (>= 0.11.2)", "graphics", "stats" ], "LinkingTo": [ "Rcpp" ], "Suggests": [ "HarmanData", "BiocGenerics", "BiocStyle", "knitr", "rmarkdown", "RUnit", "RColorBrewer", "bladderbatch", "limma", "minfi", "lumi", "msmsEDA", "affydata", "minfiData", "sva" ], "License": "GPL-3 + file LICENCE", "Archs": "i386, x64", "MD5sum": "b4e4e20eae02a2608867bf24eb5a9c5a", "NeedsCompilation": "yes", "Title": "The removal of batch effects from datasets using a PCA and constrained optimisation based technique", "Description": "Harman is a PCA and constrained optimisation based technique that maximises the removal of batch effects from datasets, with the constraint that the probability of overcorrection (i.e. removing genuine biological signal along with batch noise) is kept to a fraction which is set by the end-user.", "biocViews": [ "BatchEffect", "DNAMethylation", "Microarray", "MultipleComparison", "Normalization", "Preprocessing", "PrincipalComponent", "Software", "StatisticalMethod", "Transcription" ], "Author": "Josh Bowden [aut], Jason Ross [aut, cre], Yalchin Oytam [aut]", "Maintainer": "Jason Ross ", "URL": "http://www.bioinformatics.csiro.au/harman/", "VignetteBuilder": "knitr", "BugReports": "https://github.com/JasonR055/Harman/issues", "source.ver": "src/contrib/Harman_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Harman_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Harman_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Harman_1.2.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Harman/inst/doc/IntroductionToHarman.R" ], "htmlDocs": [ "vignettes/Harman/inst/doc/IntroductionToHarman.html" ], "htmlTitles": [ "IntroductionToHarman" ] }, "Harshlight": { "Package": "Harshlight", "Version": "1.46.0", "Depends": [ "R (>= 2.10)" ], "Imports": [ "affy", "altcdfenvs", "Biobase", "stats", "utils" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "ce697e0dcc10841f23aaafcfa938f24e", "NeedsCompilation": "yes", "Title": "A \"corrective make-up\" program for microarray chips", "Description": "The package is used to detect extended, diffuse and compact blemishes on microarray chips. Harshlight automatically marks the areas in a collection of chips (affybatch objects) and a corrected AffyBatch object is returned, in which the defected areas are substituted with NAs or the median of the values of the same probe in the other chips in the collection. The new version handle the substitute value as whole matrix to solve the memory problem.", "biocViews": [ "Microarray", "OneChannel", "Preprocessing", "QualityControl", "ReportWriting", "Software" ], "Author": "Mayte Suarez-Farinas, Maurizio Pellegrino, Knut M. Wittkowski, Marcelo O. Magnasco", "Maintainer": "Maurizio Pellegrino ", "URL": "http://asterion.rockefeller.edu/Harshlight/", "source.ver": "src/contrib/Harshlight_1.46.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Harshlight_1.46.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Harshlight_1.46.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Harshlight_1.46.0.tgz", "vignettes": [ "vignettes/Harshlight/inst/doc/Harshlight.pdf" ], "vignetteTitles": [ "Harshlight" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Harshlight/inst/doc/Harshlight.R" ] }, "HCsnip": { "Package": "HCsnip", "Version": "1.14.0", "Depends": [ "R(>= 2.10.0)", "survival", "coin", "fpc", "clusterRepro", "impute", "randomForestSRC", "sm", "sigaR", "Biobase" ], "License": "GPL (>= 2)", "MD5sum": "9b42c8612245e00b32ad0e87c59195b7", "NeedsCompilation": "no", "Title": "Semi-supervised adaptive-height snipping of the Hierarchical Clustering tree", "Description": "Decompose given hierarchical clustering tree into non-overlapping clusters in a semi-supervised way by using available patients follow-up information as guidance. Contains functions for snipping HC tree, various cluster quality evaluation criteria, assigning new patients to one of the two given HC trees, testing the significance of clusters with permutation argument and clusters visualization using sample's molecular entropy.", "biocViews": [ "Clustering", "GeneExpression", "Microarray", "Software", "aCGH" ], "Author": "Askar Obulkasim", "Maintainer": "Askar Obulkasim ", "source.ver": "src/contrib/HCsnip_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/HCsnip_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/HCsnip_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/HCsnip_1.14.0.tgz", "vignettes": [ "vignettes/HCsnip/inst/doc/HCsnip.pdf" ], "vignetteTitles": [ "HCsnip" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/HCsnip/inst/doc/HCsnip.R" ] }, "HDF5Array": { "Package": "HDF5Array", "Version": "1.2.1", "Depends": [ "R (>= 3.2)", "methods", "BiocGenerics (>= 0.15.3)", "S4Vectors (>= 0.9.43)", "IRanges (>= 2.7.6)" ], "Imports": [ "stats", "rhdf5" ], "Suggests": [ "Matrix", "h5vcData", "SummarizedExperiment", "GenomicRanges", "genefilter", "BiocStyle", "knitr", "rmarkdown" ], "License": "Artistic-2.0", "MD5sum": "a67f7ad704e51911ef42008f1bc9c90b", "NeedsCompilation": "no", "Title": "An array-like container for convenient access and manipulation of HDF5 datasets", "Description": "This package implements the HDF5Array class for convenient access and manipulation of HDF5 datasets. In order to reduce memory usage and optimize performance, operations on an HDF5Array object are either delayed or executed using a block processing mechanism. The delaying and block processing mechanisms are independent of the on-disk backend and implemented via the DelayedArray class. They even work on in-memory array-like objects like DataFrame objects (typically with Rle columns), Matrix objects, or ordinary arrays or data frames, where they can improve performance.", "biocViews": [ "Annotation", "Coverage", "DataRepresentation", "GenomeAnnotation", "Infrastructure", "Sequencing", "Software" ], "Author": "Hervé Pagès", "Maintainer": "Hervé Pagès ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/HDF5Array_1.2.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/HDF5Array_1.2.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/HDF5Array_1.2.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/HDF5Array_1.2.1.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "suggestsMe": [ "MultiAssayExperiment" ] }, "HDTD": { "Package": "HDTD", "Version": "1.8.0", "Imports": [ "stats" ], "License": "GPL-3", "MD5sum": "796b3dc7d5ab557a1251fdeea6d5bb77", "NeedsCompilation": "no", "Title": "Statistical Inference about the Mean Matrix and the Covariance Matrices in High-Dimensional Transposable Data (HDTD)", "Description": "Characterization of intra-individual variability using physiologically relevant measurements provides important insights into fundamental biological questions ranging from cell type identity to tumor development. For each individual, the data measurements can be written as a matrix with the different subsamples of the individual recorded in the columns and the different phenotypic units recorded in the rows. Datasets of this type are called high-dimensional transposable data. The HDTD package provides functions for conducting statistical inference for the mean relationship between the row and column variables and for the covariance structure within and between the row and column variables.", "biocViews": [ "DifferentialExpression", "GeneExpression", "Genetics", "Microarray", "Sequencing", "Software", "StatisticalMethod" ], "Author": "Anestis Touloumis, John C. Marioni and Simon Tavare", "Maintainer": "Anestis Touloumis ", "source.ver": "src/contrib/HDTD_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/HDTD_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/HDTD_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/HDTD_1.8.0.tgz", "vignettes": [ "vignettes/HDTD/inst/doc/Manual.pdf" ], "vignetteTitles": [ "HDTD to Analyze High-Dimensional Transposable Data" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/HDTD/inst/doc/Manual.R" ] }, "Heatplus": { "Package": "Heatplus", "Version": "2.20.0", "Imports": [ "graphics", "grDevices", "stats", "RColorBrewer" ], "Suggests": [ "Biobase", "hgu95av2.db", "limma" ], "License": "GPL (>= 2)", "MD5sum": "c84e65ba23f9a2b3cf7d0f34725f658a", "NeedsCompilation": "no", "Title": "Heatmaps with row and/or column covariates and colored clusters", "Description": "Display a rectangular heatmap (intensity plot) of a data matrix. By default, both samples (columns) and features (row) of the matrix are sorted according to a hierarchical clustering, and the corresponding dendrogram is plotted. Optionally, panels with additional information about samples and features can be added to the plot.", "biocViews": [ "Microarray", "Software", "Visualization" ], "Author": "Alexander Ploner ", "Maintainer": "Alexander Ploner ", "URL": "https://github.com/alexploner/Heatplus", "BugReports": "https://github.com/alexploner/Heatplus/issues", "source.ver": "src/contrib/Heatplus_2.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Heatplus_2.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Heatplus_2.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Heatplus_2.20.0.tgz", "vignettes": [ "vignettes/Heatplus/inst/doc/annHeatmap.pdf", "vignettes/Heatplus/inst/doc/annHeatmapCommentedSource.pdf", "vignettes/Heatplus/inst/doc/oldHeatplus.pdf" ], "vignetteTitles": [ "Annotated and regular heatmaps", "Commented package source", "Old functions (deprecated)" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Heatplus/inst/doc/annHeatmap.R", "vignettes/Heatplus/inst/doc/annHeatmapCommentedSource.R", "vignettes/Heatplus/inst/doc/oldHeatplus.R" ], "dependsOnMe": [ "GeneAnswers", "phenoTest", "tRanslatome" ], "suggestsMe": [ "mtbls2", "RforProteomics" ] }, "HelloRanges": { "Package": "HelloRanges", "Version": "1.0.1", "Depends": [ "methods", "BiocGenerics", "S4Vectors (>= 0.11.6)", "IRanges (>= 2.7.11)", "GenomicRanges (>= 1.25.5)", "Biostrings (>= 2.41.3)", "BSgenome", "GenomicFeatures", "VariantAnnotation (>= 1.19.3)", "Rsamtools", "GenomicAlignments", "rtracklayer (>= 1.33.8)", "GenomeInfoDb", "SummarizedExperiment" ], "Imports": [ "docopt", "stats", "tools", "utils" ], "Suggests": [ "HelloRangesData", "BiocStyle" ], "License": "GPL (>= 2)", "MD5sum": "6689febeb821d20de4576a720aa77931", "NeedsCompilation": "no", "Title": "Introduce *Ranges to bedtools users", "Description": "Translates bedtools command-line invocations to R code calling functions from the Bioconductor *Ranges infrastructure. This is intended to educate novice Bioconductor users and to compare the syntax and semantics of the two frameworks.", "biocViews": [ "Annotation", "Coverage", "DataImport", "GenomeAnnotation", "SequenceMatching", "Sequencing", "Software", "VariantAnnotation" ], "Author": "Michael Lawrence", "Maintainer": "Michael Lawrence ", "source.ver": "src/contrib/HelloRanges_1.0.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/HelloRanges_1.0.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/HelloRanges_1.0.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/HelloRanges_1.0.1.tgz", "vignettes": [ "vignettes/HelloRanges/inst/doc/tutorial.pdf" ], "vignetteTitles": [ "HelloRanges Tutorial" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/HelloRanges/inst/doc/tutorial.R" ] }, "HELP": { "Package": "HELP", "Version": "1.32.0", "Depends": [ "R (>= 2.8.0)", "stats", "graphics", "grDevices", "Biobase", "methods" ], "License": "GPL (>= 2)", "MD5sum": "35ca16894100a0064ae8925d73d2fbd7", "NeedsCompilation": "no", "Title": "Tools for HELP data analysis", "Description": "The package contains a modular pipeline for analysis of HELP microarray data, and includes graphical and mathematical tools with more general applications.", "biocViews": [ "CpGIsland", "DNAMethylation", "DataImport", "Microarray", "Preprocessing", "QualityControl", "Software", "TwoChannel", "Visualization" ], "Author": "Reid F. Thompson , John M. Greally , with contributions from Mark Reimers ", "Maintainer": "Reid F. Thompson ", "source.ver": "src/contrib/HELP_1.32.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/HELP_1.32.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/HELP_1.32.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/HELP_1.32.0.tgz", "vignettes": [ "vignettes/HELP/inst/doc/HELP.pdf" ], "vignetteTitles": [ "1. Primer" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/HELP/inst/doc/HELP.R" ] }, "HEM": { "Package": "HEM", "Version": "1.46.0", "Depends": [ "R (>= 2.1.0)" ], "Imports": [ "Biobase", "grDevices", "stats", "utils" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "5164796080bbb9cdf4222c6d26b1056f", "NeedsCompilation": "yes", "Title": "Heterogeneous error model for identification of differentially expressed genes under multiple conditions", "Description": "This package fits heterogeneous error models for analysis of microarray data", "biocViews": [ "DifferentialExpression", "Microarray", "Software" ], "Author": "HyungJun Cho and Jae K. Lee ", "Maintainer": "HyungJun Cho ", "URL": "http://www.healthsystem.virginia.edu/internet/hes/biostat/bioinformatics/", "source.ver": "src/contrib/HEM_1.46.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/HEM_1.46.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/HEM_1.46.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/HEM_1.46.0.tgz", "vignettes": [ "vignettes/HEM/inst/doc/HEM.pdf" ], "vignetteTitles": [ "HEM Overview" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false }, "hiAnnotator": { "Package": "hiAnnotator", "Version": "1.8.0", "Depends": [ "GenomicRanges", "R (>= 2.10)" ], "Imports": [ "foreach", "iterators", "rtracklayer", "dplyr", "BSgenome", "ggplot2", "scales" ], "Suggests": [ "knitr", "doParallel", "testthat", "BiocGenerics" ], "License": "GPL (>= 2)", "MD5sum": "bd5c170f0b3b9267b251a477c1fa01fb", "NeedsCompilation": "no", "Title": "Functions for annotating GRanges objects", "Description": "hiAnnotator contains set of functions which allow users to annotate a GRanges object with custom set of annotations. The basic philosophy of this package is to take two GRanges objects (query & subject) with common set of seqnames (i.e. chromosomes) and return associated annotation per seqnames and rows from the query matching seqnames and rows from the subject (i.e. genes or cpg islands). The package comes with three types of annotation functions which calculates if a position from query is: within a feature, near a feature, or count features in defined window sizes. Moreover, each function is equipped with parallel backend to utilize the foreach package. In addition, the package is equipped with wrapper functions, which finds appropriate columns needed to make a GRanges object from a common data frame.", "biocViews": [ "Annotation", "Software" ], "Author": "Nirav V Malani ", "Maintainer": "Nirav V Malani ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/hiAnnotator_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/hiAnnotator_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/hiAnnotator_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/hiAnnotator_1.8.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/hiAnnotator/inst/doc/Intro.R" ], "htmlDocs": [ "vignettes/hiAnnotator/inst/doc/Intro.html" ], "htmlTitles": [ "Using hiAnnotator" ], "dependsOnMe": [ "hiReadsProcessor" ] }, "HIBAG": { "Package": "HIBAG", "Version": "1.10.0", "Depends": [ "R (>= 3.2.0)" ], "Imports": [ "methods" ], "Suggests": [ "parallel", "knitr", "gdsfmt (>= 1.2.2)", "SNPRelate (>= 1.1.6)" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "94b1ac500f4eeda379a484afa39b2ef3", "NeedsCompilation": "yes", "Title": "HLA Genotype Imputation with Attribute Bagging", "Description": "It is a software package for imputing HLA types using SNP data, and relies on a training set of HLA and SNP genotypes. HIBAG can be used by researchers with published parameter estimates instead of requiring access to large training sample datasets. It combines the concepts of attribute bagging, an ensemble classifier method, with haplotype inference for SNPs and HLA types. Attribute bagging is a technique which improves the accuracy and stability of classifier ensembles using bootstrap aggregating and random variable selection.", "biocViews": [ "Genetics", "Software", "StatisticalMethod" ], "Author": "Xiuwen Zheng [aut, cre, cph], Bruce Weir [ctb, ths]", "Maintainer": "Xiuwen Zheng ", "URL": "http://www.biostat.washington.edu/~bsweir/HIBAG/, http://github.com/zhengxwen/HIBAG", "VignetteBuilder": "knitr", "source.ver": "src/contrib/HIBAG_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/HIBAG_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/HIBAG_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/HIBAG_1.10.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/HIBAG/inst/doc/HIBAG_Tutorial.R" ], "htmlDocs": [ "vignettes/HIBAG/inst/doc/HIBAG_Tutorial.html" ], "htmlTitles": [ "HIBAG vignette html" ] }, "hierGWAS": { "Package": "hierGWAS", "Version": "1.4.0", "Depends": [ "R (>= 3.2.0)" ], "Imports": [ "fastcluster", "glmnet", "fmsb" ], "Suggests": [ "BiocGenerics", "RUnit", "MASS" ], "License": "GPL-3", "MD5sum": "e1593d1bdbad8f903f051a40ce86a916", "NeedsCompilation": "no", "Title": "Asessing statistical significance in predictive GWA studies", "Description": "Testing individual SNPs, as well as arbitrarily large groups of SNPs in GWA studies, using a joint model of all SNPs. The method controls the FWER, and provides an automatic, data-driven refinement of the SNP clusters to smaller groups or single markers.", "biocViews": [ "Clustering", "LinkageDisequilibrium", "SNP", "Software" ], "Author": "Laura Buzdugan", "Maintainer": "Laura Buzdugan ", "source.ver": "src/contrib/hierGWAS_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/hierGWAS_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/hierGWAS_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/hierGWAS_1.4.0.tgz", "vignettes": [ "vignettes/hierGWAS/inst/doc/hierGWAS.pdf" ], "vignetteTitles": [ "User manual for R-Package hierGWAS" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/hierGWAS/inst/doc/hierGWAS.R" ] }, "HilbertCurve": { "Package": "HilbertCurve", "Version": "1.4.0", "Depends": [ "R (>= 3.1.2)", "grid", "IRanges", "GenomicRanges" ], "Imports": [ "methods", "HilbertVis", "png", "grDevices", "circlize (>= 0.3.3)" ], "Suggests": [ "knitr", "testthat (>= 1.0.0)", "ComplexHeatmap (>= 1.7.0)", "markdown", "RColorBrewer", "RCurl", "GetoptLong" ], "License": "GPL (>= 2)", "MD5sum": "7be961f57373ae1aefc4dcca7207fc15", "NeedsCompilation": "no", "Title": "Making 2D Hilbert Curve", "Description": "Hilbert curve is a type of space-filling curves that fold one dimensional axis into a two dimensional space, but with still preserves the locality. This package aims to provide an easy and flexible way to visualize data through Hilbert curve.", "biocViews": [ "Coverage", "GenomeAnnotation", "Sequencing", "Software", "Visualization" ], "Author": "Zuguang Gu", "Maintainer": "Zuguang Gu ", "URL": "https://github.com/jokergoo/HilbertCurve", "VignetteBuilder": "knitr", "source.ver": "src/contrib/HilbertCurve_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/HilbertCurve_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/HilbertCurve_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/HilbertCurve_1.4.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/HilbertCurve/inst/doc/HilbertCurve.R" ], "htmlDocs": [ "vignettes/HilbertCurve/inst/doc/HilbertCurve.html" ], "htmlTitles": [ "Making 2D Hilbert Curve" ], "suggestsMe": [ "ComplexHeatmap" ] }, "HilbertVis": { "Package": "HilbertVis", "Version": "1.32.0", "Depends": [ "R (>= 2.6.0)", "grid", "lattice" ], "Suggests": [ "IRanges", "EBImage" ], "License": "GPL (>= 3)", "Archs": "i386, x64", "MD5sum": "803d540500055892e10c5fd6b07d6df2", "NeedsCompilation": "yes", "Title": "Hilbert curve visualization", "Description": "Functions to visualize long vectors of integer data by means of Hilbert curves", "biocViews": [ "Software", "Visualization" ], "Author": "Simon Anders ", "Maintainer": "Simon Anders ", "URL": "http://www.ebi.ac.uk/~anders/hilbert", "source.ver": "src/contrib/HilbertVis_1.32.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/HilbertVis_1.32.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/HilbertVis_1.32.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/HilbertVis_1.32.0.tgz", "vignettes": [ "vignettes/HilbertVis/inst/doc/HilbertVis.pdf" ], "vignetteTitles": [ "Visualising very long data vectors with the Hilbert curve" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/HilbertVis/inst/doc/HilbertVis.R" ], "dependsOnMe": [ "HilbertVisGUI" ], "importsMe": [ "ChIPseqR", "HilbertCurve" ] }, "HilbertVisGUI": { "Package": "HilbertVisGUI", "Version": "1.32.0", "Depends": [ "R (>= 2.6.0)", "HilbertVis (>= 1.1.6)" ], "Suggests": [ "lattice", "IRanges" ], "License": "GPL (>= 3)", "Archs": "x64", "MD5sum": "6abbc8634e045ddfd26778f875bbee3d", "NeedsCompilation": "yes", "Title": "HilbertVisGUI", "Description": "An interactive tool to visualize long vectors of integer data by means of Hilbert curves", "biocViews": [ "Software", "Visualization" ], "Author": "Simon Anders ", "Maintainer": "Simon Anders ", "URL": "http://www.ebi.ac.uk/~anders/hilbert", "SystemRequirements": "gtkmm-2.4, GNU make", "source.ver": "src/contrib/HilbertVisGUI_1.32.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/HilbertVisGUI_1.32.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/HilbertVisGUI_1.32.0.zip", "vignettes": [ "vignettes/HilbertVisGUI/inst/doc/HilbertVisGUI.pdf" ], "vignetteTitles": [ "See vignette in package HilbertVis" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": true, "hasLICENSE": false }, "hiReadsProcessor": { "Package": "hiReadsProcessor", "Version": "1.10.0", "Depends": [ "Biostrings", "GenomicAlignments", "BiocParallel", "hiAnnotator", "R (>= 3.0)" ], "Imports": [ "sonicLength", "dplyr", "BiocGenerics", "GenomicRanges", "rSFFreader", "readxl", "methods" ], "Suggests": [ "knitr", "testthat" ], "License": "GPL-3", "MD5sum": "4f725b25fe3fd0c2a5b79a68486a2f00", "NeedsCompilation": "no", "Title": "Functions to process LM-PCR reads from 454/Illumina data", "Description": "hiReadsProcessor contains set of functions which allow users to process LM-PCR products sequenced using any platform. Given an excel/txt file containing parameters for demultiplexing and sample metadata, the functions automate trimming of adaptors and identification of the genomic product. Genomic products are further processed for QC and abundance quantification.", "biocViews": [ "Preprocessing", "Sequencing", "Software" ], "Author": "Nirav V Malani ", "Maintainer": "Nirav V Malani ", "SystemRequirements": "BLAT, UCSC hg18 in 2bit format for BLAT", "VignetteBuilder": "knitr", "source.ver": "src/contrib/hiReadsProcessor_1.10.0.tar.gz", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/hiReadsProcessor_1.10.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/hiReadsProcessor/inst/doc/Tutorial.R" ], "htmlDocs": [ "vignettes/hiReadsProcessor/inst/doc/Tutorial.html" ], "htmlTitles": [ "Using hiReadsProcessor" ] }, "HiTC": { "Package": "HiTC", "Version": "1.18.1", "Depends": [ "R (>= 2.15.0)", "methods", "IRanges", "GenomicRanges" ], "Imports": [ "Biostrings", "graphics", "grDevices", "rtracklayer", "RColorBrewer", "Matrix", "parallel", "GenomeInfoDb" ], "Suggests": [ "BiocStyle", "HiCDataHumanIMR90" ], "License": "Artistic-2.0", "MD5sum": "411b0f20a6b7702d4d4d3844aa57a8ab", "NeedsCompilation": "no", "Title": "High Throughput Chromosome Conformation Capture analysis", "Description": "The HiTC package was developed to explore high-throughput 'C' data such as 5C or Hi-C. Dedicated R classes as well as standard methods for quality controls, normalization, visualization, and further analysis are also provided.", "biocViews": [ "HiC", "HighThroughputSequencing", "Sequencing", "Software" ], "Author": "Nicolas Servant", "Maintainer": "Nicolas Servant ", "source.ver": "src/contrib/HiTC_1.18.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/HiTC_1.18.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/HiTC_1.18.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/HiTC_1.18.1.tgz", "vignettes": [ "vignettes/HiTC/inst/doc/HiC_analysis.pdf", "vignettes/HiTC/inst/doc/HiTC.pdf" ], "vignetteTitles": [ "Hi-C data analysis using HiTC", "Introduction to HiTC package" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/HiTC/inst/doc/HiC_analysis.R", "vignettes/HiTC/inst/doc/HiTC.R" ], "suggestsMe": [ "HiCDataHumanIMR90" ] }, "HMMcopy": { "Package": "HMMcopy", "Version": "1.16.0", "Depends": [ "R (>= 2.10.0)", "IRanges (>= 1.4.16)", "geneplotter (>= 1.24.0)" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "cd703f3645c7103379a27a4fbd6c066f", "NeedsCompilation": "yes", "Title": "Copy number prediction with correction for GC and mappability bias for HTS data", "Description": "Corrects GC and mappability biases for readcounts (i.e. coverage) in non-overlapping windows of fixed length for single whole genome samples, yielding a rough estimate of copy number for furthur analysis. Designed for rapid correction of high coverage whole genome tumour and normal samples.", "biocViews": [ "CopyNumberVariation", "Microarray", "Preprocessing", "Sequencing", "Software", "Visualization" ], "Author": "Daniel Lai, Gavin Ha, Sohrab Shah", "Maintainer": "Daniel Lai , Sohrab Shah ", "source.ver": "src/contrib/HMMcopy_1.16.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/HMMcopy_1.16.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/HMMcopy_1.16.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/HMMcopy_1.16.0.tgz", "vignettes": [ "vignettes/HMMcopy/inst/doc/HMMcopy.pdf" ], "vignetteTitles": [ "HMMcopy" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/HMMcopy/inst/doc/HMMcopy.R" ], "importsMe": [ "qsea" ] }, "hopach": { "Package": "hopach", "Version": "2.34.0", "Depends": [ "R (>= 2.11.0)", "cluster", "Biobase", "methods" ], "Imports": [ "graphics", "grDevices", "stats", "utils", "BiocGenerics" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "a3bcd3bcedd3cd04ce3d5540f1ac09aa", "NeedsCompilation": "yes", "Title": "Hierarchical Ordered Partitioning and Collapsing Hybrid (HOPACH)", "Description": "The HOPACH clustering algorithm builds a hierarchical tree of clusters by recursively partitioning a data set, while ordering and possibly collapsing clusters at each level. The algorithm uses the Mean/Median Split Silhouette (MSS) criteria to identify the level of the tree with maximally homogeneous clusters. It also runs the tree down to produce a final ordered list of the elements. The non-parametric bootstrap allows one to estimate the probability that each element belongs to each cluster (fuzzy clustering).", "biocViews": [ "Clustering", "Software" ], "Author": "Katherine S. Pollard, with Mark J. van der Laan and Greg Wall", "Maintainer": "Katherine S. Pollard ", "URL": "http://www.stat.berkeley.edu/~laan/, http://docpollard.org/", "source.ver": "src/contrib/hopach_2.34.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/hopach_2.34.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/hopach_2.34.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/hopach_2.34.0.tgz", "vignettes": [ "vignettes/hopach/inst/doc/hopach.pdf" ], "vignetteTitles": [ "hopach" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/hopach/inst/doc/hopach.R" ], "importsMe": [ "phenoTest" ], "suggestsMe": [ "BiocCaseStudies" ] }, "hpar": { "Package": "hpar", "Version": "1.16.0", "Depends": [ "R (>= 2.15)" ], "Imports": [ "utils" ], "Suggests": [ "org.Hs.eg.db", "GO.db", "knitr", "BiocStyle", "testthat" ], "License": "Artistic-2.0", "MD5sum": "7f967a4c1fd908a6192563234f8dcb04", "NeedsCompilation": "no", "Title": "Human Protein Atlas in R", "Description": "A simple interface to and data from the Human Protein Atlas project.", "biocViews": [ "CellBiology", "Homo_sapiens", "Proteomics", "Software" ], "Author": "Laurent Gatto", "Maintainer": "Laurent Gatto ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/hpar_1.16.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/hpar_1.16.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/hpar_1.16.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/hpar_1.16.0.tgz", "vignettes": [ "vignettes/hpar/inst/doc/hpar.pdf" ], "vignetteTitles": [ "Human Protein Atlas in R" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/hpar/inst/doc/hpar.R" ], "importsMe": [ "MetaboSignal" ], "suggestsMe": [ "pRoloc", "RforProteomics" ] }, "HTqPCR": { "Package": "HTqPCR", "Version": "1.28.0", "Depends": [ "Biobase", "RColorBrewer", "limma" ], "Imports": [ "affy", "Biobase", "gplots", "graphics", "grDevices", "limma", "methods", "RColorBrewer", "stats", "stats4", "utils" ], "Suggests": [ "statmod" ], "License": "Artistic-2.0", "MD5sum": "668530254fddff06883696d3d8c0a4dd", "NeedsCompilation": "no", "Title": "Automated analysis of high-throughput qPCR data", "Description": "Analysis of Ct values from high throughput quantitative real-time PCR (qPCR) assays across multiple conditions or replicates. The input data can be from spatially-defined formats such ABI TaqMan Low Density Arrays or OpenArray; LightCycler from Roche Applied Science; the CFX plates from Bio-Rad Laboratories; conventional 96- or 384-well plates; or microfluidic devices such as the Dynamic Arrays from Fluidigm Corporation. HTqPCR handles data loading, quality assessment, normalization, visualization and parametric or non-parametric testing for statistical significance in Ct values between features (e.g. genes, microRNAs).", "biocViews": [ "DataImport", "DifferentialExpression", "GeneExpression", "MicrotitrePlateAssay", "MultipleComparison", "Preprocessing", "QualityControl", "Software", "Visualization", "qPCR" ], "Author": "Heidi Dvinge, Paul Bertone", "Maintainer": "Heidi Dvinge ", "URL": "http://www.ebi.ac.uk/bertone/software", "source.ver": "src/contrib/HTqPCR_1.28.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/HTqPCR_1.28.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/HTqPCR_1.28.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/HTqPCR_1.28.0.tgz", "vignettes": [ "vignettes/HTqPCR/inst/doc/HTqPCR.pdf" ], "vignetteTitles": [ "qPCR analysis in R" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/HTqPCR/inst/doc/HTqPCR.R" ], "importsMe": [ "nondetects", "unifiedWMWqPCR" ] }, "HTSanalyzeR": { "Package": "HTSanalyzeR", "Version": "2.26.0", "Depends": [ "R (>= 2.15)", "igraph", "methods" ], "Imports": [ "graph", "igraph", "GSEABase", "BioNet", "cellHTS2", "AnnotationDbi", "biomaRt", "RankProd" ], "Suggests": [ "KEGG.db", "GO.db", "org.Dm.eg.db", "GOstats", "org.Ce.eg.db", "org.Mm.eg.db", "org.Rn.eg.db", "org.Hs.eg.db", "snow" ], "License": "Artistic-2.0", "MD5sum": "db8c7727d8ba0df0259becf54b78013e", "NeedsCompilation": "no", "Title": "Gene set over-representation, enrichment and network analyses for high-throughput screens", "Description": "This package provides classes and methods for gene set over-representation, enrichment and network analyses on high-throughput screens. The over-representation analysis is performed based on hypergeometric tests. The enrichment analysis is based on the GSEA algorithm (Subramanian et al. PNAS 2005). The network analysis identifies enriched subnetworks based on algorithms from the BioNet package (Beisser et al., Bioinformatics 2010). A pipeline is also specifically designed for cellHTS2 object to perform integrative network analyses of high-throughput RNA interference screens. The users can build their own analysis pipeline for their own data set based on this package.", "biocViews": [ "CellBasedAssays", "MultipleComparison", "Software" ], "Author": "Xin Wang , Camille Terfve , John C. Rose , Florian Markowetz ", "Maintainer": "Xin Wang ", "source.ver": "src/contrib/HTSanalyzeR_2.26.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/HTSanalyzeR_2.26.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/HTSanalyzeR_2.26.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/HTSanalyzeR_2.26.0.tgz", "vignettes": [ "vignettes/HTSanalyzeR/inst/doc/HTSanalyzeR-Vignette.pdf" ], "vignetteTitles": [ "Main vignette:Gene set enrichment and network analysis of high-throughput RNAi screen data using HTSanalyzeR" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/HTSanalyzeR/inst/doc/HTSanalyzeR-Vignette.R" ], "importsMe": [ "Mulder2012", "phenoTest" ], "suggestsMe": [ "RTN" ] }, "HTSeqGenie": { "Package": "HTSeqGenie", "Version": "4.4.0", "Depends": [ "R (>= 3.0.0)", "gmapR (>= 1.8.0)", "ShortRead (>= 1.19.13)", "VariantAnnotation (>= 1.8.3)" ], "Imports": [ "BiocGenerics (>= 0.2.0)", "S4Vectors (>= 0.9.25)", "IRanges (>= 1.21.39)", "GenomicRanges (>= 1.23.21)", "Rsamtools (>= 1.8.5)", "Biostrings (>= 2.24.1)", "chipseq (>= 1.6.1)", "hwriter (>= 1.3.0)", "Cairo (>= 1.5.5)", "GenomicFeatures (>= 1.9.31)", "BiocParallel", "parallel", "tools", "rtracklayer (>= 1.17.19)", "GenomicAlignments", "VariantTools (>= 1.7.7)", "GenomeInfoDb", "SummarizedExperiment", "methods" ], "Suggests": [ "TxDb.Hsapiens.UCSC.hg19.knownGene", "LungCancerLines", "org.Hs.eg.db" ], "License": "Artistic-2.0", "MD5sum": "4640e411b3b0a73ee919d1f6002a8928", "NeedsCompilation": "no", "Title": "A NGS analysis pipeline.", "Description": "Libraries to perform NGS analysis.", "Author": "Gregoire Pau, Jens Reeder", "Maintainer": "Jens Reeder ", "source.ver": "src/contrib/HTSeqGenie_4.4.0.tar.gz", "vignettes": [ "vignettes/HTSeqGenie/inst/doc/HTSeqGenie.pdf" ], "vignetteTitles": [ "HTSeqGenie" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/HTSeqGenie/inst/doc/HTSeqGenie.R" ], "biocViews": [ "Software" ] }, "htSeqTools": { "Package": "htSeqTools", "Version": "1.22.0", "Depends": [ "R (>= 2.12.2)", "methods", "BiocGenerics (>= 0.1.0)", "Biobase", "S4Vectors", "IRanges", "methods", "MASS", "BSgenome", "GenomeInfoDb (>= 1.1.3)", "GenomicRanges (>= 1.17.11)" ], "Enhances": [ "parallel", "multicore" ], "License": "GPL (>=2)", "MD5sum": "bef4c86b41f22732b6b2593d7dbf1f5a", "NeedsCompilation": "no", "Title": "Quality Control, Visualization and Processing for High-Throughput Sequencing data", "Description": "We provide efficient, easy-to-use tools for High-Throughput Sequencing (ChIP-seq, RNAseq etc.). These include MDS plots (analogues to PCA), detecting inefficient immuno-precipitation or over-amplification artifacts, tools to identify and test for genomic regions with large accumulation of reads, and visualization of coverage profiles.", "biocViews": [ "QualityControl", "Sequencing", "Software" ], "Author": "Evarist Planet, Camille Stephan-Otto, Oscar Reina, Oscar Flores, David Rossell", "Maintainer": "Oscar Reina ", "source.ver": "src/contrib/htSeqTools_1.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/htSeqTools_1.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/htSeqTools_1.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/htSeqTools_1.22.0.tgz", "vignettes": [ "vignettes/htSeqTools/inst/doc/htSeqTools.pdf" ], "vignetteTitles": [ "Manual for the htSeqTools library" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/htSeqTools/inst/doc/htSeqTools.R" ] }, "HTSFilter": { "Package": "HTSFilter", "Version": "1.14.1", "Depends": [ "R (>= 3.3.0)" ], "Imports": [ "edgeR (>= 3.9.14)", "DESeq2 (>= 1.10.1)", "DESeq (>= 1.22.1)", "BiocParallel (>= 1.4.3)", "Biobase", "utils", "stats", "grDevices", "graphics", "methods" ], "Suggests": [ "EDASeq (>= 2.1.4)", "BiocStyle", "testthat" ], "License": "Artistic-2.0", "MD5sum": "3ef7e88ce9f1b822658037bea8516896", "NeedsCompilation": "no", "Title": "Filter replicated high-throughput transcriptome sequencing data", "Description": "This package implements a filtering procedure for replicated transcriptome sequencing data based on a global Jaccard similarity index in order to identify genes with low, constant levels of expression across one or more experimental conditions.", "biocViews": [ "DifferentialExpression", "GeneExpression", "Normalization", "Preprocessing", "RNASeq", "Sequencing", "Software" ], "Author": "Andrea Rau, Melina Gallopin, Gilles Celeux, and Florence Jaffrezic", "Maintainer": "Andrea Rau ", "source.ver": "src/contrib/HTSFilter_1.14.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/HTSFilter_1.14.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/HTSFilter_1.14.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/HTSFilter_1.14.1.tgz", "vignettes": [ "vignettes/HTSFilter/inst/doc/HTSFilter.pdf" ], "vignetteTitles": [ "HTSFilter Vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/HTSFilter/inst/doc/HTSFilter.R" ] }, "HybridMTest": { "Package": "HybridMTest", "Version": "1.18.0", "Depends": [ "R (>= 2.9.0)", "Biobase", "fdrtool", "MASS", "survival" ], "Imports": [ "stats" ], "License": "GPL Version 2 or later", "MD5sum": "de98780fb7d82d3d033b7ee86e18b59d", "NeedsCompilation": "no", "Title": "Hybrid Multiple Testing", "Description": "Performs hybrid multiple testing that incorporates method selection and assumption evaluations into the analysis using empirical Bayes probability (EBP) estimates obtained by Grenander density estimation. For instance, for 3-group comparison analysis, Hybrid Multiple testing considers EBPs as weighted EBPs between F-test and H-test with EBPs from Shapiro Wilk test of normality as weigth. Instead of just using EBPs from F-test only or using H-test only, this methodology combines both types of EBPs through EBPs from Shapiro Wilk test of normality. This methodology uses then the law of total EBPs.", "biocViews": [ "GeneExpression", "Genetics", "Microarray", "Software" ], "Author": "Stan Pounds , Demba Fofana ", "Maintainer": "Demba Fofana ", "source.ver": "src/contrib/HybridMTest_1.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/HybridMTest_1.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/HybridMTest_1.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/HybridMTest_1.18.0.tgz", "vignettes": [ "vignettes/HybridMTest/inst/doc/HybridMTest.pdf" ], "vignetteTitles": [ "Hybrid Multiple Testing" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/HybridMTest/inst/doc/HybridMTest.R" ] }, "hyperdraw": { "Package": "hyperdraw", "Version": "1.26.0", "Depends": [ "R (>= 2.9.0)" ], "Imports": [ "methods", "grid", "graph", "hypergraph", "Rgraphviz", "stats4" ], "License": "GPL (>= 2)", "MD5sum": "96c6013709e49ba6c33f5feabd2303ef", "NeedsCompilation": "no", "Title": "Visualizing Hypergaphs", "Description": "Functions for visualizing hypergraphs.", "biocViews": [ "GraphAndNetwork", "Software", "Visualization" ], "Author": "Paul Murrell", "Maintainer": "Paul Murrell ", "SystemRequirements": "graphviz", "source.ver": "src/contrib/hyperdraw_1.26.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/hyperdraw_1.26.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/hyperdraw_1.26.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/hyperdraw_1.26.0.tgz", "vignettes": [ "vignettes/hyperdraw/inst/doc/hyperdraw.pdf" ], "vignetteTitles": [ "Hyperdraw" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/hyperdraw/inst/doc/hyperdraw.R" ], "dependsOnMe": [ "BiGGR" ] }, "hypergraph": { "Package": "hypergraph", "Version": "1.46.0", "Depends": [ "R (>= 2.1.0)", "methods", "utils", "graph" ], "Suggests": [ "BiocGenerics", "RUnit" ], "License": "Artistic-2.0", "MD5sum": "c2c9eeebc0832c49766dc64240f1c7e6", "NeedsCompilation": "no", "Title": "A package providing hypergraph data structures", "Description": "A package that implements some simple capabilities for representing and manipulating hypergraphs.", "biocViews": [ "GraphAndNetwork", "Software" ], "Author": "Seth Falcon, Robert Gentleman", "Maintainer": "Bioconductor Package Maintainer ", "source.ver": "src/contrib/hypergraph_1.46.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/hypergraph_1.46.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/hypergraph_1.46.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/hypergraph_1.46.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "dependsOnMe": [ "altcdfenvs", "RpsiXML" ], "importsMe": [ "BiGGR", "hyperdraw" ] }, "iASeq": { "Package": "iASeq", "Version": "1.18.0", "Depends": [ "R (>= 2.14.1)" ], "Imports": [ "graphics", "grDevices" ], "License": "GPL-2", "MD5sum": "763db46158609062d7746a0cbb14b313", "NeedsCompilation": "no", "Title": "iASeq: integrating multiple sequencing datasets for detecting allele-specific events", "Description": "It fits correlation motif model to multiple RNAseq or ChIPseq studies to improve detection of allele-specific events and describe correlation patterns across studies.", "biocViews": [ "ChIPSeq", "RNASeq", "SNP", "Software" ], "Author": "Yingying Wei, Hongkai Ji", "Maintainer": "Yingying Wei ", "source.ver": "src/contrib/iASeq_1.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/iASeq_1.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/iASeq_1.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/iASeq_1.18.0.tgz", "vignettes": [ "vignettes/iASeq/inst/doc/iASeqVignette.pdf" ], "vignetteTitles": [ "iASeq Vignette" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/iASeq/inst/doc/iASeqVignette.R" ] }, "iBBiG": { "Package": "iBBiG", "Version": "1.18.0", "Depends": [ "biclust" ], "Imports": [ "stats4", "xtable", "ade4" ], "Suggests": [ "methods" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "d9dae998bfa315a88d76936623f39afb", "NeedsCompilation": "yes", "Title": "Iterative Binary Biclustering of Genesets", "Description": "iBBiG is a bi-clustering algorithm which is optimizes for binary data analysis. We apply it to meta-gene set analysis of large numbers of gene expression datasets. The iterative algorithm extracts groups of phenotypes from multiple studies that are associated with similar gene sets. iBBiG does not require prior knowledge of the number or scale of clusters and allows discovery of clusters with diverse sizes", "biocViews": [ "Annotation", "Clustering", "GeneSetEnrichment", "Software" ], "Author": "Daniel Gusenleitner, Aedin Culhane", "Maintainer": "Aedin Culhane ", "URL": "http://bcb.dfci.harvard.edu/~aedin/publications/", "source.ver": "src/contrib/iBBiG_1.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/iBBiG_1.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/iBBiG_1.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/iBBiG_1.18.0.tgz", "vignettes": [ "vignettes/iBBiG/inst/doc/tutorial.pdf" ], "vignetteTitles": [ "iBBiG User Manual" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/iBBiG/inst/doc/tutorial.R" ] }, "ibh": { "Package": "ibh", "Version": "1.22.0", "Depends": [ "simpIntLists" ], "Suggests": [ "yeastCC", "stats" ], "License": "GPL (>= 2)", "MD5sum": "de4bf6706a1f768141f1e597e0c3135b", "NeedsCompilation": "no", "Title": "Interaction Based Homogeneity for Evaluating Gene Lists", "Description": "This package contains methods for calculating Interaction Based Homogeneity to evaluate fitness of gene lists to an interaction network which is useful for evaluation of clustering results and gene list analysis. BioGRID interactions are used in the calculation. The user can also provide their own interactions.", "biocViews": [ "DataImport", "GraphAndNetwork", "NetworkEnrichment", "QualityControl", "Software" ], "Author": "Kircicegi Korkmaz, Volkan Atalay, Rengul Cetin Atalay.", "Maintainer": "Kircicegi Korkmaz ", "source.ver": "src/contrib/ibh_1.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ibh_1.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ibh_1.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ibh_1.22.0.tgz", "vignettes": [ "vignettes/ibh/inst/doc/ibh.pdf" ], "vignetteTitles": [ "ibh" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ibh/inst/doc/ibh.R" ] }, "iBMQ": { "Package": "iBMQ", "Version": "1.14.0", "Depends": [ "R(>= 2.15.0)", "Biobase (>= 2.16.0)", "ggplot2 (>= 0.9.2)" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "180dd106f164e0376f1c57c46ae7aa50", "NeedsCompilation": "yes", "Title": "integrated Bayesian Modeling of eQTL data", "Description": "integrated Bayesian Modeling of eQTL data", "biocViews": [ "GeneExpression", "Microarray", "Preprocessing", "SNP", "Software" ], "Author": "Marie-Pier Scott-Boyer and Greg Imholte", "Maintainer": "Greg Imholte ", "URL": "http://www.rglab.org", "SystemRequirements": "GSL and OpenMP", "source.ver": "src/contrib/iBMQ_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/iBMQ_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/iBMQ_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/iBMQ_1.14.0.tgz", "vignettes": [ "vignettes/iBMQ/inst/doc/iBMQ.pdf" ], "vignetteTitles": [ "iBMQ: An Integrated Hierarchical Bayesian Model for Multivariate eQTL Mapping" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/iBMQ/inst/doc/iBMQ.R" ] }, "iCARE": { "Package": "iCARE", "Version": "1.2.0", "Depends": [ "R (>= 3.3.0)" ], "Suggests": [ "RUnit", "BiocGenerics" ], "License": "GPL-3 + file LICENSE", "Archs": "i386, x64", "MD5sum": "2ee124d7caae93264cb760f9d9297a75", "NeedsCompilation": "yes", "Title": "A Tool for Individualized Coherent Absolute Risk Estimation (iCARE)", "Description": "An R package to compute Individualized Coherent Absolute Risk Estimators.", "biocViews": [ "GenomeWideAssociation", "Software", "StatisticalMethod" ], "Author": "Paige Maas, Nilanjan Chatterjee and William Wheeler", "Maintainer": "Bill Wheeler ", "source.ver": "src/contrib/iCARE_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/iCARE_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/iCARE_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/iCARE_1.2.0.tgz", "vignettes": [ "vignettes/iCARE/inst/doc/vignette.pdf" ], "vignetteTitles": [ "iCARE Vignette" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/iCARE/inst/doc/vignette.R" ] }, "Icens": { "Package": "Icens", "Version": "1.46.0", "Depends": [ "survival" ], "Imports": [ "graphics" ], "License": "Artistic-2.0", "MD5sum": "5c69079601cbf75d9946bfdad136ad20", "NeedsCompilation": "no", "Title": "NPMLE for Censored and Truncated Data", "Description": "Many functions for computing the NPMLE for censored and truncated data.", "biocViews": [ "Infrastructure", "Software" ], "Author": "R. Gentleman and Alain Vandal", "Maintainer": "Bioconductor Package Maintainer ", "source.ver": "src/contrib/Icens_1.46.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Icens_1.46.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Icens_1.46.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Icens_1.46.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "dependsOnMe": [ "PROcess" ], "importsMe": [ "PROcess" ] }, "iCheck": { "Package": "iCheck", "Version": "1.4.0", "Depends": [ "R (>= 3.2.0)", "Biobase", "lumi", "gplots" ], "Imports": [ "stats", "graphics", "preprocessCore", "grDevices", "randomForest", "affy", "limma", "parallel", "GeneSelectMMD", "rgl", "MASS", "lmtest", "scatterplot3d", "utils" ], "License": "GPL (>= 2)", "MD5sum": "f5cab90d675af377c7eb2ecad86f4a92", "NeedsCompilation": "no", "Title": "QC Pipeline and Data Analysis Tools for High-Dimensional Illumina mRNA Expression Data", "Description": "QC pipeline and data analysis tools for high-dimensional Illumina mRNA expression data.", "biocViews": [ "DNAMethylation", "DifferentialExpression", "GeneExpression", "Microarray", "OneChannel", "Preprocessing", "QualityControl", "Software", "TwoChannel" ], "Author": "Weiliang Qiu [aut, cre], Brandon Guo [aut, ctb], Christopher Anderson [aut, ctb], Barbara Klanderman [aut, ctb], Vincent Carey [aut, ctb], Benjamin Raby [aut, ctb]", "Maintainer": "Weiliang Qiu ", "source.ver": "src/contrib/iCheck_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/iCheck_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/iCheck_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/iCheck_1.4.0.tgz", "vignettes": [ "vignettes/iCheck/inst/doc/iCheck.pdf" ], "vignetteTitles": [ "iCheck" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/iCheck/inst/doc/iCheck.R" ] }, "iChip": { "Package": "iChip", "Version": "1.28.0", "Depends": [ "R (>= 2.10.0)" ], "Imports": [ "limma" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "f63254bfde2287eeb0d9abcfb4a2b756", "NeedsCompilation": "yes", "Title": "Bayesian Modeling of ChIP-chip Data Through Hidden Ising Models", "Description": "This package uses hidden Ising models to identify enriched genomic regions in ChIP-chip data. It can be used to analyze the data from multiple platforms (e.g., Affymetrix, Agilent, and NimbleGen), and the data with single to multiple replicates.", "biocViews": [ "AgilentChip", "ChIPchip", "Microarray", "OneChannel", "Software" ], "Author": "Qianxing Mo", "Maintainer": "Qianxing Mo ", "source.ver": "src/contrib/iChip_1.28.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/iChip_1.28.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/iChip_1.28.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/iChip_1.28.0.tgz", "vignettes": [ "vignettes/iChip/inst/doc/iChip.pdf" ], "vignetteTitles": [ "iChip" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/iChip/inst/doc/iChip.R" ] }, "iClusterPlus": { "Package": "iClusterPlus", "Version": "1.10.0", "Depends": [ "R (>= 2.15.0)", "parallel" ], "Suggests": [ "RUnit", "BiocGenerics" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "c1bbde654697c37a46be579a829f7215", "NeedsCompilation": "yes", "Title": "Integrative clustering of multi-type genomic data", "Description": "Integrative clustering of multiple genomic data using a joint latent variable model", "biocViews": [ "Clustering", "Microarray", "Software" ], "Author": "Qianxing Mo, Ronglai Shen", "Maintainer": "Qianxing Mo , Ronglai Shen ", "source.ver": "src/contrib/iClusterPlus_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/iClusterPlus_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/iClusterPlus_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/iClusterPlus_1.10.0.tgz", "vignettes": [ "vignettes/iClusterPlus/inst/doc/iClusterPlus.pdf", "vignettes/iClusterPlus/inst/doc/iManual.pdf" ], "vignetteTitles": [ "iClusterPlus", "iManual.pdf" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "suggestsMe": [ "MultiDataSet" ] }, "iCOBRA": { "Package": "iCOBRA", "Version": "1.2.0", "Depends": [ "R (>= 3.2)" ], "Imports": [ "shiny (>= 0.9.1.9008)", "shinydashboard", "shinyBS", "reshape2", "ggplot2", "scales", "ROCR", "dplyr", "DT", "limma", "methods", "UpSetR" ], "Suggests": [ "knitr", "testthat" ], "License": "GPL (>=2)", "MD5sum": "90f18c3263a754b0aed1987950eb0483", "NeedsCompilation": "no", "Title": "Comparison and Visualization of Ranking and Assignment Methods", "Description": "This package provides functions for calculation and visualization of performance metrics for evaluation of ranking and binary classification (assignment) methods. It also contains a shiny application for interactive exploration of results.", "biocViews": [ "Classification", "Software" ], "Author": "Charlotte Soneson [aut, cre]", "Maintainer": "Charlotte Soneson ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/iCOBRA_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/iCOBRA_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/iCOBRA_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/iCOBRA_1.2.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/iCOBRA/inst/doc/iCOBRA.R" ], "htmlDocs": [ "vignettes/iCOBRA/inst/doc/iCOBRA.html" ], "htmlTitles": [ "iCOBRA User Guide" ] }, "IdeoViz": { "Package": "IdeoViz", "Version": "1.8.0", "Depends": [ "Biobase", "IRanges", "GenomicRanges", "RColorBrewer", "rtracklayer", "graphics", "GenomeInfoDb" ], "License": "GPL-2", "MD5sum": "671bdf012378ddb1e8a405efad0daefb", "NeedsCompilation": "no", "Title": "Plots data (continuous/discrete) along chromosomal ideogram", "Description": "Plots data associated with arbitrary genomic intervals along chromosomal ideogram.", "biocViews": [ "Microarray", "Software", "Visualization" ], "Author": "Shraddha Pai , Jingliang Ren", "Maintainer": "Shraddha Pai ", "source.ver": "src/contrib/IdeoViz_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/IdeoViz_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/IdeoViz_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/IdeoViz_1.8.0.tgz", "vignettes": [ "vignettes/IdeoViz/inst/doc/Vignette.pdf" ], "vignetteTitles": [ "IdeoViz: a package for plotting simple data along ideograms" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/IdeoViz/inst/doc/Vignette.R" ] }, "idiogram": { "Package": "idiogram", "Version": "1.50.0", "Depends": [ "R (>= 2.10)", "methods", "Biobase", "annotate", "plotrix" ], "Suggests": [ "hu6800.db", "hgu95av2.db", "golubEsets" ], "License": "GPL-2", "MD5sum": "7dcfa34b812d0fadbf9667c57b26ba6a", "NeedsCompilation": "no", "Title": "idiogram", "Description": "A package for plotting genomic data by chromosomal location", "biocViews": [ "Software", "Visualization" ], "Author": "Karl J. Dykema ", "Maintainer": "Karl J. Dykema ", "source.ver": "src/contrib/idiogram_1.50.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/idiogram_1.50.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/idiogram_1.50.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/idiogram_1.50.0.tgz", "vignettes": [ "vignettes/idiogram/inst/doc/idiogram.pdf" ], "vignetteTitles": [ "HOWTO: idiogram" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/idiogram/inst/doc/idiogram.R" ], "dependsOnMe": [ "reb" ] }, "IdMappingAnalysis": { "Package": "IdMappingAnalysis", "Version": "1.18.0", "Depends": [ "R (>= 2.14)", "R.oo (>= 1.13.0)", "rChoiceDialogs" ], "Imports": [ "boot", "mclust", "RColorBrewer", "Biobase" ], "License": "GPL-2", "MD5sum": "d8e789187ef25c77e37d2ee5a4374230", "NeedsCompilation": "no", "Title": "ID Mapping Analysis", "Description": "Identifier mapping performance analysis", "biocViews": [ "Annotation", "MultipleComparison", "Software" ], "Author": "Alex Lisovich, Roger Day", "Maintainer": "Alex Lisovich , Roger Day ", "source.ver": "src/contrib/IdMappingAnalysis_1.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/IdMappingAnalysis_1.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/IdMappingAnalysis_1.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/IdMappingAnalysis_1.18.0.tgz", "vignettes": [ "vignettes/IdMappingAnalysis/inst/doc/IdMappingAnalysis.pdf" ], "vignetteTitles": [ "Critically comparing identifier maps retrieved from bioinformatics annotation resources." ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/IdMappingAnalysis/inst/doc/IdMappingAnalysis.R" ] }, "IdMappingRetrieval": { "Package": "IdMappingRetrieval", "Version": "1.22.0", "Depends": [ "R.oo", "XML", "RCurl", "rChoiceDialogs" ], "Imports": [ "biomaRt", "ENVISIONQuery", "AffyCompatible", "R.methodsS3", "utils" ], "License": "GPL-2", "MD5sum": "b396d68428c45ced39530ebb00b596a7", "NeedsCompilation": "no", "Title": "ID Mapping Data Retrieval", "Description": "Data retrieval for identifier mapping performance analysis", "biocViews": [ "Annotation", "MultipleComparison", "Software" ], "Author": "Alex Lisovich, Roger Day", "Maintainer": "Alex Lisovich , Roger Day ", "source.ver": "src/contrib/IdMappingRetrieval_1.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/IdMappingRetrieval_1.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/IdMappingRetrieval_1.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/IdMappingRetrieval_1.22.0.tgz", "vignettes": [ "vignettes/IdMappingRetrieval/inst/doc/IdMappingRetrieval.pdf" ], "vignetteTitles": [ "Collection and subsequent fast retrieval of identifier mapping related information from various online sources." ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/IdMappingRetrieval/inst/doc/IdMappingRetrieval.R" ] }, "iGC": { "Package": "iGC", "Version": "1.4.0", "Depends": [ "R (>= 3.2.0)" ], "Imports": [ "plyr", "data.table" ], "Suggests": [ "BiocStyle", "knitr", "rmarkdown" ], "Enhances": [ "doMC" ], "License": "GPL-2", "MD5sum": "8c9a33b71dae00921c63cff4f43f3b95", "NeedsCompilation": "no", "Title": "An integrated analysis package of Gene expression and Copy number alteration", "Description": "This package is intended to identify differentially expressed genes driven by Copy Number Alterations from samples with both gene expression and CNA data.", "biocViews": [ "AssayDomain", "Biological Question", "CopyNumberVariation", "DifferentialExpression", "GeneExpression", "Genetics", "GenomicVariation", "Microarray", "MultipleComparison", "ResearchField", "Sequencing", "Software", "Technology", "WorkflowStep" ], "Author": "Yi-Pin Lai [aut], Liang-Bo Wang [aut, cre], Tzu-Pin Lu [aut], Eric Y. Chuang [aut]", "Maintainer": "Liang-Bo Wang ", "URL": "http://github.com/ccwang002/iGC", "VignetteBuilder": "knitr", "BugReports": "http://github.com/ccwang002/iGC/issues", "source.ver": "src/contrib/iGC_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/iGC_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/iGC_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/iGC_1.4.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/iGC/inst/doc/Introduction.R" ], "htmlDocs": [ "vignettes/iGC/inst/doc/Introduction.html" ], "htmlTitles": [ "Introduction to iGC" ] }, "IHW": { "Package": "IHW", "Version": "1.2.0", "Depends": [ "R (>= 3.3.0)" ], "Imports": [ "methods", "slam", "lpsymphony", "fdrtool", "BiocGenerics" ], "Suggests": [ "ggplot2", "dplyr", "gridExtra", "scales", "DESeq2", "airway", "testthat", "Matrix", "BiocStyle", "knitr", "rmarkdown", "devtools" ], "License": "Artistic-2.0", "MD5sum": "7b22b1eb1f83cb428545d7a4fb63728b", "NeedsCompilation": "no", "Title": "Independent Hypothesis Weighting", "Description": "Independent hypothesis weighting (IHW) is a multiple testing procedure that increases power compared to the method of Benjamini and Hochberg by assigning data-driven weights to each hypothesis. The input to IHW is a two-column table of p-values and covariates. The covariate can be any continuous-valued or categorical variable that is thought to be informative on the statistical properties of each hypothesis test, while it is independent of the p-value under the null hypothesis.", "biocViews": [ "MultipleComparison", "RNASeq", "Software" ], "Author": "Nikos Ignatiadis [aut, cre], Wolfgang Huber [aut]", "Maintainer": "Nikos Ignatiadis ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/IHW_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/IHW_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/IHW_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/IHW_1.2.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/IHW/inst/doc/introduction_to_ihw.R" ], "htmlDocs": [ "vignettes/IHW/inst/doc/introduction_to_ihw.html" ], "htmlTitles": [ "\"Introduction to IHW\"" ], "suggestsMe": [ "DESeq2" ], "dependsOnMe": [ "IHWpaper" ] }, "illuminaio": { "Package": "illuminaio", "Version": "0.16.0", "Imports": [ "base64" ], "Suggests": [ "RUnit", "BiocGenerics", "IlluminaDataTestFiles (>= 1.0.2)", "BiocStyle" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "ea2ba7f88b654cb2de32d367dcf96361", "NeedsCompilation": "yes", "Title": "Parsing Illumina Microarray Output Files", "Description": "Tools for parsing Illumina's microarray output files, including IDAT.", "biocViews": [ "DataImport", "Infrastructure", "Microarray", "ProprietaryPlatforms", "Software" ], "Author": "Keith Baggerly [aut], Henrik Bengtsson [aut], Kasper Daniel Hansen [aut, cre], Matt Ritchie [aut], Mike L. Smith [aut], Tim Triche Jr. [ctb]", "Maintainer": "Kasper Daniel Hansen ", "URL": "https://github.com/HenrikBengtsson/illuminaio", "BugReports": "https://github.com/HenrikBengtsson/illuminaio/issues", "source.ver": "src/contrib/illuminaio_0.16.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/illuminaio_0.16.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/illuminaio_0.16.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/illuminaio_0.16.0.tgz", "vignettes": [ "vignettes/illuminaio/inst/doc/EncryptedFormat.pdf", "vignettes/illuminaio/inst/doc/illuminaio.pdf" ], "vignetteTitles": [ "Description of Encrypted IDAT Format", "Introduction to illuminaio" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/illuminaio/inst/doc/illuminaio.R" ], "dependsOnMe": [ "normalize450K", "RnBeads", "wateRmelon" ], "importsMe": [ "beadarray", "crlmm", "methylumi", "minfi" ], "suggestsMe": [ "limma" ] }, "imageHTS": { "Package": "imageHTS", "Version": "1.24.0", "Depends": [ "R (>= 2.9.0)", "EBImage (>= 4.3.12)", "cellHTS2 (>= 2.10.0)" ], "Imports": [ "tools", "Biobase", "hwriter", "methods", "vsn", "stats", "utils", "e1071" ], "Suggests": [ "BiocStyle", "MASS" ], "License": "LGPL-2.1", "MD5sum": "d8efba2650c252b0069d091108cfed1a", "NeedsCompilation": "no", "Title": "Analysis of high-throughput microscopy-based screens", "Description": "imageHTS is an R package dedicated to the analysis of high-throughput microscopy-based screens. The package provides a modular and extensible framework to segment cells, extract quantitative cell features, predict cell types and browse screen data through web interfaces. Designed to operate in distributed environments, imageHTS provides a standardized access to remote data and facilitates the dissemination of high-throughput microscopy-based datasets.", "biocViews": [ "CellBasedAssays", "Preprocessing", "Software", "Visualization" ], "Author": "Gregoire Pau, Xian Zhang, Michael Boutros, Wolfgang Huber", "Maintainer": "Joseph Barry ", "source.ver": "src/contrib/imageHTS_1.24.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/imageHTS_1.24.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/imageHTS_1.24.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/imageHTS_1.24.0.tgz", "vignettes": [ "vignettes/imageHTS/inst/doc/imageHTS-introduction.pdf" ], "vignetteTitles": [ "Analysis of high-throughput microscopy-based screens with imageHTS" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/imageHTS/inst/doc/imageHTS-introduction.R" ], "dependsOnMe": [ "PGPC", "phenoDist" ] }, "Imetagene": { "Package": "Imetagene", "Version": "1.4.0", "Depends": [ "R (>= 3.2.0)", "metagene", "shiny" ], "Imports": [ "d3heatmap", "shinyBS", "shinyFiles", "shinythemes", "ggplot2" ], "Suggests": [ "knitr", "BiocStyle", "rmarkdown" ], "License": "Artistic-2.0 | file LICENSE", "MD5sum": "2bd1a37bf371d78f83cacf3c8f36dbe9", "NeedsCompilation": "no", "Title": "A graphical interface for the metagene package", "Description": "This package provide a graphical user interface to the metagene package. This will allow people with minimal R experience to easily complete metagene analysis.", "biocViews": [ "Alignment", "ChIPSeq", "Coverage", "Genetics", "MultipleComparison", "Sequencing", "Software" ], "Author": "Audrey Lemacon , Charles Joly Beauparlant , Arnaud Droit ", "Maintainer": "Audrey Lemacon ", "VignetteBuilder": "knitr", "BugReports": "https://github.com/andronekomimi/Imetagene/issues", "source.ver": "src/contrib/Imetagene_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Imetagene_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Imetagene_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Imetagene_1.4.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/Imetagene/inst/doc/imetagene.R" ], "htmlDocs": [ "vignettes/Imetagene/inst/doc/imetagene.html" ], "htmlTitles": [ "Presentation of Imetagene" ] }, "ImmuneSpaceR": { "Package": "ImmuneSpaceR", "Version": "1.2.0", "Imports": [ "methods", "data.table", "RCurl", "Rlabkey (>= 2.1.127)", "Biobase", "pheatmap", "ggplot2", "scales", "stats", "gtools", "gplots", "reshape2" ], "Suggests": [ "knitr", "rmarkdown", "testthat" ], "License": "GPL-2", "MD5sum": "246acf946eff5e57783e763e07c5d32d", "NeedsCompilation": "no", "Title": "A Thin Wrapper around the ImmuneSpace Database", "Description": "Provides a convenient API for accessing data sets within ImmuneSpace (www.immunespace.org), the data repository and analysis platform of the Human Immunology Project Consortium (HIPC).", "biocViews": [ "DataImport", "DataRepresentation", "Software", "ThirdPartyClient" ], "Author": "Greg Finak, Renan Sauteraud, Mike Jiang, Gil Guday", "Maintainer": "Renan Sauteraud ", "URL": "https://github.com/RGLab/ImmuneSpaceR", "VignetteBuilder": "knitr", "BugReports": "https://github.com/RGLab/ImmuneSpaceR/issues", "source.ver": "src/contrib/ImmuneSpaceR_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ImmuneSpaceR_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ImmuneSpaceR_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ImmuneSpaceR_1.2.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ImmuneSpaceR/inst/doc/arrays.R", "vignettes/ImmuneSpaceR/inst/doc/getDataset.R", "vignettes/ImmuneSpaceR/inst/doc/report_SDY144.R", "vignettes/ImmuneSpaceR/inst/doc/report_SDY180.R", "vignettes/ImmuneSpaceR/inst/doc/report_SDY269.R", "vignettes/ImmuneSpaceR/inst/doc/Using_RImmuneSpace.R" ], "htmlDocs": [ "vignettes/ImmuneSpaceR/inst/doc/arrays.html", "vignettes/ImmuneSpaceR/inst/doc/getDataset.html", "vignettes/ImmuneSpaceR/inst/doc/report_SDY144.html", "vignettes/ImmuneSpaceR/inst/doc/report_SDY180.html", "vignettes/ImmuneSpaceR/inst/doc/report_SDY269.html", "vignettes/ImmuneSpaceR/inst/doc/Using_RImmuneSpace.html" ], "htmlTitles": [ "Handling expression matrices with ImmuneSpaceR", "Downloading tables with getDataset", "Reproducing an online report using ImmuneSpaceR: Correlation of HAI/virus neutralizition titer and cell counts in SDY144", "Reproducing an online report using ImmuneSpaceR: Plasmablast abundance in SDY180", "Reproducing an online report using ImmuneSpaceR: Correlation between HAI and flow cytometry in SDY269", "An introduction to the ImmuneSpaceR package" ] }, "immunoClust": { "Package": "immunoClust", "Version": "1.6.0", "Depends": [ "R(>= 3.2)", "methods", "stats", "graphics", "grid", "lattice", "flowCore" ], "Suggests": [ "BiocStyle" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "dca737288ff20cf40c218481ae19bded", "NeedsCompilation": "yes", "Title": "immunoClust - Automated Pipeline for Population Detection in Flow Cytometry", "Description": "Model based clustering and meta-clustering of Flow Cytometry Data", "biocViews": [ "CellBasedAssays", "Clustering", "FlowCytometry", "Software" ], "Author": "Till Soerensen ", "Maintainer": "Till Soerensen ", "source.ver": "src/contrib/immunoClust_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/immunoClust_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/immunoClust_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/immunoClust_1.6.0.tgz", "vignettes": [ "vignettes/immunoClust/inst/doc/immunoClust.pdf" ], "vignetteTitles": [ "immunoClust package" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/immunoClust/inst/doc/immunoClust.R" ] }, "IMPCdata": { "Package": "IMPCdata", "Version": "1.8.0", "Depends": [ "R (>= 2.3.0)" ], "Imports": [ "rjson" ], "License": "file LICENSE", "MD5sum": "58dcf9a8b75382c5a67e570fd959d22e", "NeedsCompilation": "no", "Title": "Retrieves data from IMPC database", "Description": "Package contains methods for data retrieval from IMPC Database.", "biocViews": [ "ExperimentData", "Software" ], "Author": "Natalja Kurbatova, Jeremy Mason", "Maintainer": "Jeremy Mason ", "source.ver": "src/contrib/IMPCdata_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/IMPCdata_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/IMPCdata_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/IMPCdata_1.8.0.tgz", "vignettes": [ "vignettes/IMPCdata/inst/doc/IMPCdata.pdf" ], "vignetteTitles": [ "IMPCdata Vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/IMPCdata/inst/doc/IMPCdata.R" ] }, "ImpulseDE": { "Package": "ImpulseDE", "Version": "1.0.0", "Depends": [ "graphics", "grDevices", "stats", "utils", "parallel", "compiler", "R (>= 3.2.3)" ], "Imports": [ "amap", "boot" ], "Suggests": [ "longitudinal", "knitr" ], "License": "GPL-3", "MD5sum": "b5f17c32a94378a87cfde9dde67e6585", "NeedsCompilation": "no", "Title": "Detection of DE genes in time series data using impulse models", "Description": "ImpulseDE is suited to capture single impulse-like patterns in high throughput time series datasets. By fitting a representative impulse model to each gene, it reports differentially expressed genes whether across time points in a single experiment or between two time courses from two experiments. To optimize the running time, the code makes use of clustering steps and multi-threading.", "biocViews": [ "Software", "StatisticalMethod", "TimeCourse" ], "Author": "Jil Sander [aut, cre], Nir Yosef [aut]", "Maintainer": "Jil Sander , Nir Yosef ", "URL": "https://github.com/YosefLab/ImpulseDE", "VignetteBuilder": "knitr", "BugReports": "https://github.com/YosefLab/ImpulseDE/issues", "source.ver": "src/contrib/ImpulseDE_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ImpulseDE_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ImpulseDE_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ImpulseDE_1.0.0.tgz", "vignettes": [ "vignettes/ImpulseDE/inst/doc/ImpulseDE.pdf" ], "vignetteTitles": [ "ImpulseDE" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ImpulseDE/inst/doc/ImpulseDE.R" ] }, "impute": { "Package": "impute", "Version": "1.48.0", "Depends": [ "R (>= 2.10)" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "b8495a77bd675a86228a5bb5800a84c8", "NeedsCompilation": "yes", "Title": "impute: Imputation for microarray data", "Description": "Imputation for microarray data (currently KNN only)", "biocViews": [ "Microarray", "Software" ], "Author": "Trevor Hastie, Robert Tibshirani, Balasubramanian Narasimhan, Gilbert Chu", "Maintainer": "Balasubramanian Narasimhan ", "source.ver": "src/contrib/impute_1.48.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/impute_1.48.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/impute_1.48.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/impute_1.48.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "dependsOnMe": [ "CGHcall", "curatedBreastData", "FEM", "HCsnip", "prot2D", "TIN" ], "importsMe": [ "CancerSubtypes", "ChAMP", "DAPAR", "doppelgangR", "EGAD", "ENmix", "genomation", "MethylMix", "miRLAB", "MSnbase", "Pigengene", "Rnits", "statTarget" ], "suggestsMe": [ "BioNet", "MethPed", "RnBeads" ] }, "InPAS": { "Package": "InPAS", "Version": "1.6.0", "Depends": [ "R (>= 3.1)", "methods", "Biobase", "GenomicRanges", "GenomicFeatures", "S4Vectors" ], "Imports": [ "AnnotationDbi", "BSgenome", "cleanUpdTSeq", "Gviz", "seqinr", "preprocessCore", "IRanges", "GenomeInfoDb", "depmixS4", "limma", "BiocParallel" ], "Suggests": [ "RUnit", "BiocGenerics", "BiocStyle", "BSgenome.Hsapiens.UCSC.hg19", "BSgenome.Mmusculus.UCSC.mm10", "org.Hs.eg.db", "org.Mm.eg.db", "TxDb.Hsapiens.UCSC.hg19.knownGene", "TxDb.Mmusculus.UCSC.mm10.knownGene", "rtracklayer", "knitr" ], "License": "GPL (>= 2)", "MD5sum": "f680317730aa7b8cac800ba14511df32", "NeedsCompilation": "no", "Title": "Identification of Novel alternative PolyAdenylation Sites (PAS)", "Description": "Alternative polyadenylation (APA) is one of the important post-transcriptional regulation mechanisms which occurs in most human genes. InPAS facilitates the discovery of novel APA sites from RNAseq data. It leverages cleanUpdTSeq to fine tune identified APA sites.", "biocViews": [ "AlternativeSplicing", "Coverage", "DifferentialSplicing", "GeneRegulation", "RNASeq", "Sequencing", "Software", "Transcription" ], "Author": "Jianhong Ou, Sung Mi Park, Michael R. Green and Lihua Julie Zhu", "Maintainer": "Jianhong Ou ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/InPAS_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/InPAS_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/InPAS_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/InPAS_1.6.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/InPAS/inst/doc/InPAS.R" ], "htmlDocs": [ "vignettes/InPAS/inst/doc/InPAS.html" ], "htmlTitles": [ "InPAS Vignette" ] }, "INPower": { "Package": "INPower", "Version": "1.10.0", "Depends": [ "R (>= 3.1.0)", "mvtnorm" ], "Suggests": [ "RUnit", "BiocGenerics" ], "License": "GPL-2 + file LICENSE", "MD5sum": "18f67a60a7d49c60380ee8e0d4a5b7ee", "NeedsCompilation": "no", "Title": "An R package for computing the number of susceptibility SNPs", "Description": "An R package for computing the number of susceptibility SNPs and power of future studies", "biocViews": [ "SNP", "Software" ], "Author": "Ju-Hyun Park", "Maintainer": "Bill Wheeler ", "source.ver": "src/contrib/INPower_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/INPower_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/INPower_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/INPower_1.10.0.tgz", "vignettes": [ "vignettes/INPower/inst/doc/vignette.pdf" ], "vignetteTitles": [ "INPower Vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/INPower/inst/doc/vignette.R" ] }, "INSPEcT": { "Package": "INSPEcT", "Version": "1.4.0", "Depends": [ "R (>= 3.2)", "methods", "Biobase", "BiocParallel" ], "Imports": [ "pROC", "deSolve", "rootSolve", "compiler", "preprocessCore", "GenomicFeatures", "GenomicRanges", "IRanges", "BiocGenerics", "GenomicAlignments", "Rsamtools", "S4Vectors" ], "Suggests": [ "BiocStyle", "knitr", "TxDb.Mmusculus.UCSC.mm9.knownGene" ], "License": "GPL-2", "MD5sum": "eee6d249ff01b04bebb202bd7efe69df", "NeedsCompilation": "no", "Title": "Analysis of 4sU-seq and RNA-seq time-course data", "Description": "INSPEcT (INference of Synthesis, Processing and dEgradation rates in Time-Course experiments) analyses 4sU-seq and RNA-seq time-course data in order to evaluate synthesis, processing and degradation rates and asses via modeling the rates that determines changes in mature mRNA levels.", "biocViews": [ "GeneRegulation", "RNASeq", "Sequencing", "Software", "SystemsBiology", "TimeCourse" ], "Author": "Stefano de Pretis", "Maintainer": "Stefano de Pretis ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/INSPEcT_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/INSPEcT_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/INSPEcT_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/INSPEcT_1.4.0.tgz", "vignettes": [ "vignettes/INSPEcT/inst/doc/INSPEcT.pdf" ], "vignetteTitles": [ "INSPEcT" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/INSPEcT/inst/doc/INSPEcT.R" ] }, "intansv": { "Package": "intansv", "Version": "1.12.0", "Depends": [ "R (>= 2.14.0)", "plyr", "ggbio", "GenomicRanges" ], "Imports": [ "BiocGenerics", "IRanges" ], "License": "Artistic-2.0", "MD5sum": "4458219cdd5b991277ebee710b3daa65", "NeedsCompilation": "no", "Title": "Integrative analysis of structural variations", "Description": "This package provides efficient tools to read and integrate structural variations predicted by popular softwares. Annotation and visulation of structural variations are also implemented in the package.", "biocViews": [ "Annotation", "Genetics", "Sequencing", "Software" ], "Author": "Wen Yao ", "Maintainer": "Wen Yao ", "source.ver": "src/contrib/intansv_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/intansv_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/intansv_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/intansv_1.12.0.tgz", "vignettes": [ "vignettes/intansv/inst/doc/intansvOverview.pdf" ], "vignetteTitles": [ "An Introduction to intansv" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/intansv/inst/doc/intansvOverview.R" ] }, "InteractionSet": { "Package": "InteractionSet", "Version": "1.2.1", "Depends": [ "R (>= 3.3.0)", "GenomicRanges", "SummarizedExperiment (>= 1.1.6)" ], "Imports": [ "IRanges", "S4Vectors (>= 0.9.24)", "GenomeInfoDb", "BiocGenerics", "methods", "Matrix" ], "Suggests": [ "testthat", "knitr", "rmarkdown", "BiocStyle" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "59056cefab8b25f581e3bdcaebd8b338", "NeedsCompilation": "yes", "Title": "Base Classes for Storing Genomic Interaction Data", "Description": "Provides the GInteractions, InteractionSet and ContactMatrix objects and associated methods for storing and manipulating genomic interaction data from Hi-C and ChIA-PET experiments.", "biocViews": [ "DataRepresentation", "HiC", "Infrastructure", "Software" ], "Author": "Aaron Lun , Malcolm Perry , Liz Ing-Simmons ", "Maintainer": "Aaron Lun ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/InteractionSet_1.2.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/InteractionSet_1.2.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/InteractionSet_1.2.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/InteractionSet_1.2.1.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/InteractionSet/inst/doc/interactions.R" ], "htmlDocs": [ "vignettes/InteractionSet/inst/doc/interactions.html" ], "htmlTitles": [ "Interacting with InteractionSet classes for genomic interaction data" ], "dependsOnMe": [ "diffHic", "GenomicInteractions" ] }, "interactiveDisplay": { "Package": "interactiveDisplay", "Version": "1.12.0", "Depends": [ "R (>= 2.10)", "methods", "BiocGenerics", "grid" ], "Imports": [ "interactiveDisplayBase (>= 1.7.3)", "shiny", "RColorBrewer", "ggplot2", "reshape2", "plyr", "gridSVG", "XML", "Category", "AnnotationDbi" ], "Suggests": [ "RUnit", "hgu95av2.db", "knitr", "GenomicRanges", "SummarizedExperiment", "GOstats", "ggbio", "GO.db", "Gviz", "rtracklayer", "metagenomeSeq", "gplots", "vegan", "Biobase" ], "Enhances": [ "rstudio" ], "License": "Artistic-2.0", "MD5sum": "7d39ed6f5fd0ac195bbbca114197c566", "NeedsCompilation": "no", "Title": "Package for enabling powerful shiny web displays of Bioconductor objects", "Description": "The interactiveDisplay package contains the methods needed to generate interactive Shiny based display methods for Bioconductor objects.", "biocViews": [ "AnnotationData", "Classification", "DataRepresentation", "GO", "GUI", "GeneExpression", "Genetics", "Microarray", "Network", "QualityControl", "Sequencing", "Software", "Visualization" ], "Author": "Shawn Balcome, Marc Carlson", "Maintainer": "Shawn Balcome ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/interactiveDisplay_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/interactiveDisplay_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/interactiveDisplay_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/interactiveDisplay_1.12.0.tgz", "vignettes": [ "vignettes/interactiveDisplay/inst/doc/interactiveDisplay.pdf" ], "vignetteTitles": [ "interactiveDisplay: A package for enabling interactive visualization of Bioconductor objects" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/interactiveDisplay/inst/doc/interactiveDisplay.R" ], "suggestsMe": [ "metagenomeSeq" ], "importsMe": [ "RforProteomics" ] }, "interactiveDisplayBase": { "Package": "interactiveDisplayBase", "Version": "1.12.0", "Depends": [ "R (>= 2.10)", "methods", "BiocGenerics" ], "Imports": [ "shiny" ], "Suggests": [ "knitr" ], "Enhances": [ "rstudioapi" ], "License": "Artistic-2.0", "MD5sum": "bb3c434214362f3c289245a49ff67801", "NeedsCompilation": "no", "Title": "Base package for enabling powerful shiny web displays of Bioconductor objects", "Description": "The interactiveDisplayBase package contains the the basic methods needed to generate interactive Shiny based display methods for Bioconductor objects.", "biocViews": [ "AnnotationData", "Classification", "DataRepresentation", "GO", "GUI", "GeneExpression", "Genetics", "Microarray", "Network", "QualityControl", "Sequencing", "Software", "Visualization" ], "Author": "Shawn Balcome, Marc Carlson", "Maintainer": "Shawn Balcome ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/interactiveDisplayBase_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/interactiveDisplayBase_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/interactiveDisplayBase_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/interactiveDisplayBase_1.12.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/interactiveDisplayBase/inst/doc/interactiveDisplayBase.R" ], "htmlDocs": [ "vignettes/interactiveDisplayBase/inst/doc/interactiveDisplayBase.html" ], "htmlTitles": [ "Using interactiveDisplayBase for Bioconductor object visualization and modification" ], "importsMe": [ "AnnotationHub", "interactiveDisplay" ] }, "inveRsion": { "Package": "inveRsion", "Version": "1.22.0", "Depends": [ "methods", "haplo.stats" ], "Imports": [ "graphics", "methods", "utils" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "3322d8d459531250dc027150f9aedd8f", "NeedsCompilation": "yes", "Title": "Inversions in genotype data", "Description": "Package to find genetic inversions in genotype (SNP array) data.", "biocViews": [ "Microarray", "SNP", "Software" ], "Author": "Alejandro Caceres", "Maintainer": "Alejandro Caceres ", "source.ver": "src/contrib/inveRsion_1.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/inveRsion_1.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/inveRsion_1.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/inveRsion_1.22.0.tgz", "vignettes": [ "vignettes/inveRsion/inst/doc/inveRsion.pdf" ], "vignetteTitles": [ "Quick start guide for inveRsion package" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/inveRsion/inst/doc/inveRsion.R" ] }, "IONiseR": { "Package": "IONiseR", "Version": "1.4.4", "Depends": [ "R (>= 3.3)" ], "Imports": [ "rhdf5", "dplyr", "magrittr", "tidyr", "data.table", "ShortRead", "Biostrings", "ggplot2", "methods", "BiocGenerics", "XVector", "stats", "utils" ], "Suggests": [ "BiocStyle", "knitr", "rmarkdown", "gridExtra", "testthat", "minionSummaryData" ], "License": "MIT + file LICENSE", "MD5sum": "2cf4593c555d91b5448983a1ae4b7868", "NeedsCompilation": "no", "Title": "Quality Assessment Tools for Oxford Nanopore MinION data", "Description": "IONiseR provides tools for the quality assessment of Oxford Nanopore MinION data. It extracts summary statistics from a set of fast5 files and can be used either before or after base calling. In addition to standard summaries of the read-types produced, it provides a number of plots for visualising metrics relative to experiment run time or spatially over the surface of a flowcell.", "biocViews": [ "DataImport", "QualityControl", "Sequencing", "Software" ], "Author": "Mike Smith [aut, cre]", "Maintainer": "Mike Smith ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/IONiseR_1.4.4.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/IONiseR_1.4.4.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/IONiseR_1.4.4.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/IONiseR_1.4.4.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/IONiseR/inst/doc/IONiseR.R" ], "htmlDocs": [ "vignettes/IONiseR/inst/doc/IONiseR.html" ], "htmlTitles": [ "Quality assessment tools for nanopore data" ] }, "iontree": { "Package": "iontree", "Version": "1.20.0", "Depends": [ "methods", "rJava", "RSQLite", "XML" ], "Suggests": [ "iontreeData" ], "License": "GPL-2", "MD5sum": "f2e85093d36ac7803854a75410172e16", "NeedsCompilation": "no", "Title": "Data management and analysis of ion trees from ion-trap mass spectrometry", "Description": "Ion fragmentation provides structural information for metabolite identification. This package provides utility functions to manage and analyse MS2/MS3 fragmentation data from ion trap mass spectrometry. It was designed for high throughput metabolomics data with many biological samples and a large numer of ion trees collected. Tests have been done with data from low-resolution mass spectrometry but could be readily extended to precursor ion based fragmentation data from high resoultion mass spectrometry.", "biocViews": [ "MassSpectrometry", "Metabolomics", "Software" ], "Author": "Mingshu Cao", "Maintainer": "Mingshu Cao ", "source.ver": "src/contrib/iontree_1.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/iontree_1.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/iontree_1.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/iontree_1.20.0.tgz", "vignettes": [ "vignettes/iontree/inst/doc/iontree_doc.pdf" ], "vignetteTitles": [ "MSn" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/iontree/inst/doc/iontree_doc.R" ] }, "iPAC": { "Package": "iPAC", "Version": "1.18.0", "Depends": [ "R(>= 2.15)", "gdata", "scatterplot3d", "Biostrings", "multtest" ], "License": "GPL-2", "MD5sum": "ee7538c4b6a2d412c1b68e39aa96dbb8", "NeedsCompilation": "no", "Title": "Identification of Protein Amino acid Clustering", "Description": "iPAC is a novel tool to identify somatic amino acid mutation clustering within proteins while taking into account protein structure.", "biocViews": [ "Clustering", "Proteomics", "Software" ], "Author": "Gregory Ryslik, Hongyu Zhao", "Maintainer": "Gregory Ryslik ", "source.ver": "src/contrib/iPAC_1.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/iPAC_1.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/iPAC_1.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/iPAC_1.18.0.tgz", "vignettes": [ "vignettes/iPAC/inst/doc/iPAC.pdf" ], "vignetteTitles": [ "iPAC: identification of Protein Amino acid Mutations" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/iPAC/inst/doc/iPAC.R" ], "dependsOnMe": [ "GraphPAC", "QuartPAC", "SpacePAC" ] }, "IPO": { "Package": "IPO", "Version": "1.0.0", "Depends": [ "xcms", "rsm", "CAMERA", "grDevices", "graphics", "stats", "utils" ], "Suggests": [ "RUnit", "BiocGenerics", "msdata", "mtbls2", "faahKO", "knitr" ], "Enhances": [ "parallel" ], "License": "GPL (>= 2) + file LICENSE", "MD5sum": "4968825d7c43cd96c6ad7e8e6e775d10", "NeedsCompilation": "no", "Title": "Automated Optimization of XCMS Data Processing parameters", "Description": "The outcome of XCMS data processing strongly depends on the parameter settings. IPO (`Isotopologue Parameter Optimization`) is a parameter optimization tool that is applicable for different kinds of samples and liquid chromatography coupled to high resolution mass spectrometry devices, fast and free of labeling steps. IPO uses natural, stable 13C isotopes to calculate a peak picking score. Retention time correction is optimized by minimizing the relative retention time differences within features and grouping parameters are optimized by maximizing the number of features showing exactly one peak from each injection of a pooled sample. The different parameter settings are achieved by design of experiment. The resulting scores are evaluated using response surface models.", "biocViews": [ "MassSpectrometry", "Metabolomics", "Software" ], "Author": "Gunnar Libiseller , Christoph Magnes ", "Maintainer": "Thomas Riebenbauer ", "URL": "https://github.com/rietho/IPO", "VignetteBuilder": "knitr", "BugReports": "https://github.com/rietho/IPO/issues/new", "source.ver": "src/contrib/IPO_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/IPO_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/IPO_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/IPO_1.0.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/IPO/inst/doc/IPO.R" ], "htmlDocs": [ "vignettes/IPO/inst/doc/IPO.html" ], "htmlTitles": [ "XCMS Parameter Optimization with IPO" ] }, "IPPD": { "Package": "IPPD", "Version": "1.22.0", "Depends": [ "R (>= 2.12.0)", "MASS", "Matrix", "XML", "digest", "bitops" ], "Imports": [ "methods", "stats", "graphics" ], "License": "GPL (version 2 or later)", "Archs": "i386, x64", "MD5sum": "6cfc9d6eaac933cd825d46bbbf38da2b", "NeedsCompilation": "yes", "Title": "Isotopic peak pattern deconvolution for Protein Mass Spectrometry by template matching", "Description": "The package provides functionality to extract isotopic peak patterns from raw mass spectra. This is done by fitting a large set of template basis functions to the raw spectrum using either nonnegative least squares or least absolute deviation fittting. The package offers a flexible function which tries to estimate model parameters in a way tailored to the peak shapes in the data. The package also provides functionality to process LCMS runs.", "biocViews": [ "Proteomics", "Software" ], "Author": "Martin Slawski , Rene Hussong , Andreas Hildebrandt , Matthias Hein ", "Maintainer": "Martin Slawski ", "source.ver": "src/contrib/IPPD_1.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/IPPD_1.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/IPPD_1.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/IPPD_1.22.0.tgz", "vignettes": [ "vignettes/IPPD/inst/doc/IPPD.pdf" ], "vignetteTitles": [ "IPPD Manual" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/IPPD/inst/doc/IPPD.R" ], "suggestsMe": [ "RforProteomics" ] }, "IRanges": { "Package": "IRanges", "Version": "2.8.2", "Depends": [ "R (>= 3.1.0)", "methods", "utils", "stats", "BiocGenerics (>= 0.19.1)", "S4Vectors (>= 0.11.19)" ], "Imports": [ "stats4" ], "LinkingTo": [ "S4Vectors" ], "Suggests": [ "XVector", "GenomicRanges", "GenomicFeatures", "GenomicAlignments", "BSgenome.Celegans.UCSC.ce2", "RUnit" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "ae1e6b78c6b84e4df6bec44e98e2136c", "NeedsCompilation": "yes", "Title": "Infrastructure for manipulating intervals on sequences", "Description": "Provides efficient low-level and highly reusable S4 classes for storing, manipulating and aggregating over annotated ranges of integers. Implements an algebra of range operations, including efficient algorithms for finding overlaps and nearest neighbors. Defines efficient list-like classes for storing, transforming and aggregating large grouped data, i.e., collections of atomic vectors and DataFrames.", "biocViews": [ "DataRepresentation", "Infrastructure", "Software" ], "Author": "H. Pagès, P. Aboyoun and M. Lawrence", "Maintainer": "Bioconductor Package Maintainer ", "source.ver": "src/contrib/IRanges_2.8.2.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/IRanges_2.8.2.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/IRanges_2.8.2.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/IRanges_2.8.2.tgz", "vignettes": [ "vignettes/IRanges/inst/doc/IRangesOverview.pdf" ], "vignetteTitles": [ "An Introduction to IRanges" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/IRanges/inst/doc/IRangesOverview.R" ], "dependsOnMe": [ "AnnotationDbi", "AnnotationHubData", "ASpli", "BaalChIP", "BayesPeak", "biomvRCNS", "Biostrings", "BiSeq", "BSgenome", "BubbleTree", "bumphunter", "CAFE", "casper", "CexoR", "ChIPComp", "ChIPpeakAnno", "chipseq", "CODEX", "consensusSeekeR", "CSAR", "customProDB", "deepSNV", "DESeq2", "DEXSeq", "DirichletMultinomial", "DMRcaller", "EnrichedHeatmap", "epigenomix", "exomeCopy", "fCCAC", "FunciSNP.data", "geneRxCluster", "GenomeInfoDb", "GenomicAlignments", "GenomicFeatures", "GenomicRanges", "Genominator", "groHMM", "gtrellis", "Guitar", "Gviz", "harbChIP", "HDF5Array", "HelloRanges", "HilbertCurve", "HiTC", "HMMcopy", "htSeqTools", "IdeoViz", "isomiRs", "LiebermanAidenHiC2009", "methyAnalysis", "MotifDb", "motifRG", "oneChannelGUI", "OTUbase", "pd.ag", "pd.aragene.1.0.st", "pd.aragene.1.1.st", "pd.ath1.121501", "pd.barley1", "pd.bovgene.1.0.st", "pd.bovgene.1.1.st", "pd.bovine", "pd.bsubtilis", "pd.cangene.1.0.st", "pd.cangene.1.1.st", "pd.canine", "pd.canine.2", "pd.celegans", "pd.chicken", "pd.chigene.1.0.st", "pd.chigene.1.1.st", "pd.chogene.2.0.st", "pd.chogene.2.1.st", "pd.citrus", "pd.clariom.d.human", "pd.clariom.s.human", "pd.clariom.s.human.ht", "pd.clariom.s.mouse", "pd.clariom.s.mouse.ht", "pd.clariom.s.rat", "pd.clariom.s.rat.ht", "pd.cotton", "pd.cyngene.1.0.st", "pd.cyngene.1.1.st", "pd.cyrgene.1.0.st", "pd.cyrgene.1.1.st", "pd.cytogenetics.array", "pd.drogene.1.0.st", "pd.drogene.1.1.st", "pd.drosgenome1", "pd.drosophila.2", "pd.e.coli.2", "pd.ecoli", "pd.ecoli.asv2", "pd.elegene.1.0.st", "pd.elegene.1.1.st", "pd.equgene.1.0.st", "pd.equgene.1.1.st", "pd.felgene.1.0.st", "pd.felgene.1.1.st", "pd.fingene.1.0.st", "pd.fingene.1.1.st", "pd.genomewidesnp.5", "pd.genomewidesnp.6", "pd.guigene.1.0.st", "pd.guigene.1.1.st", "pd.hc.g110", "pd.hg.focus", "pd.hg.u133.plus.2", "pd.hg.u133a", "pd.hg.u133a.2", "pd.hg.u133a.tag", "pd.hg.u133b", "pd.hg.u219", "pd.hg.u95a", "pd.hg.u95av2", "pd.hg.u95b", "pd.hg.u95c", "pd.hg.u95d", "pd.hg.u95e", "pd.hg18.60mer.expr", "pd.ht.hg.u133.plus.pm", "pd.ht.hg.u133a", "pd.ht.mg.430a", "pd.hta.2.0", "pd.hu6800", "pd.huex.1.0.st.v2", "pd.hugene.1.0.st.v1", "pd.hugene.1.1.st.v1", "pd.hugene.2.0.st", "pd.hugene.2.1.st", "pd.maize", "pd.mapping250k.nsp", "pd.mapping250k.sty", "pd.mapping50k.hind240", "pd.mapping50k.xba240", "pd.margene.1.0.st", "pd.margene.1.1.st", "pd.medgene.1.0.st", "pd.medgene.1.1.st", "pd.medicago", "pd.mg.u74a", "pd.mg.u74av2", "pd.mg.u74b", "pd.mg.u74bv2", "pd.mg.u74c", "pd.mg.u74cv2", "pd.mirna.1.0", "pd.mirna.2.0", "pd.mirna.3.0", "pd.mirna.4.0", "pd.moe430a", "pd.moe430b", "pd.moex.1.0.st.v1", "pd.mogene.1.0.st.v1", "pd.mogene.1.1.st.v1", "pd.mogene.2.0.st", "pd.mogene.2.1.st", "pd.mouse430.2", "pd.mouse430a.2", "pd.mta.1.0", "pd.mu11ksuba", "pd.mu11ksubb", "pd.nugo.hs1a520180", "pd.nugo.mm1a520177", "pd.ovigene.1.0.st", "pd.ovigene.1.1.st", "pd.pae.g1a", "pd.plasmodium.anopheles", "pd.poplar", "pd.porcine", "pd.porgene.1.0.st", "pd.porgene.1.1.st", "pd.rabgene.1.0.st", "pd.rabgene.1.1.st", "pd.rae230a", "pd.rae230b", "pd.raex.1.0.st.v1", "pd.ragene.1.0.st.v1", "pd.ragene.1.1.st.v1", "pd.ragene.2.0.st", "pd.ragene.2.1.st", "pd.rat230.2", "pd.rcngene.1.0.st", "pd.rcngene.1.1.st", "pd.rg.u34a", "pd.rg.u34b", "pd.rg.u34c", "pd.rhegene.1.0.st", "pd.rhegene.1.1.st", "pd.rhesus", "pd.rice", "pd.rjpgene.1.0.st", "pd.rjpgene.1.1.st", "pd.rn.u34", "pd.rta.1.0", "pd.rusgene.1.0.st", "pd.rusgene.1.1.st", "pd.s.aureus", "pd.soybean", "pd.soygene.1.0.st", "pd.soygene.1.1.st", "pd.sugar.cane", "pd.tomato", "pd.u133.x3p", "pd.vitis.vinifera", "pd.wheat", "pd.x.laevis.2", "pd.x.tropicalis", "pd.xenopus.laevis", "pd.yeast.2", "pd.yg.s98", "pd.zebgene.1.0.st", "pd.zebgene.1.1.st", "pd.zebrafish", "pepStat", "PGA", "PING", "proBAMr", "PSICQUIC", "RefNet", "rfPred", "rGADEM", "rGREAT", "RIPSeeker", "rMAT", "scsR", "SGSeq", "SICtools", "SNPlocs.Hsapiens.dbSNP.20090506", "SNPlocs.Hsapiens.dbSNP.20100427", "SNPlocs.Hsapiens.dbSNP.20101109", "SNPlocs.Hsapiens.dbSNP.20110815", "SNPlocs.Hsapiens.dbSNP.20111119", "SNPlocs.Hsapiens.dbSNP.20120608", "SNPlocs.Hsapiens.dbSNP141.GRCh38", "SNPlocs.Hsapiens.dbSNP142.GRCh37", "TEQC", "TitanCNA", "traseR", "triform", "triplex", "VariantTools", "XtraSNPlocs.Hsapiens.dbSNP141.GRCh38", "XVector" ], "importsMe": [ "ALDEx2", "AllelicImbalance", "alpine", "AneuFinder", "annmap", "AnnotationDbi", "annotatr", "ArrayExpressHTS", "ballgown", "bamsignals", "BasicSTARRseq", "BayesPeak", "BBCAnalyzer", "beadarray", "Biostrings", "biovizBase", "BiSeq", "BitSeq", "BPRMeth", "BSgenome", "bsseq", "CAGEr", "cgdv17", "charm", "chipenrich", "chipenrich.data", "ChIPQC", "ChIPseeker", "chipseq", "ChIPseqR", "ChIPsim", "ChromHeatMap", "chromstaR", "CINdex", "cleaver", "clusterProfiler", "cn.mops", "CNEr", "CNPBayes", "CNVPanelizer", "CNVrd2", "cobindR", "coMET", "compEpiTools", "contiBAIT", "conumee", "copynumber", "CopywriteR", "CoverageView", "CRISPRseek", "CrispRVariants", "csaw", "customProDB", "debrowser", "DECIPHER", "derfinder", "derfinderHelper", "derfinderPlot", "DiffBind", "diffHic", "diffloop", "DMRcate", "DOQTL", "DRIMSeq", "easyRNASeq", "EDASeq", "ELMER", "ensembldb", "epivizr", "epivizrData", "facopy", "fastseg", "FindMyFriends", "fitCons.UCSC.hg19", "flipflop", "flowQ", "FunciSNP", "genbankr", "geneAttribution", "GeneGeneInteR", "GenoGAM", "genomation", "genomeIntervals", "GenomicAlignments", "GenomicFiles", "GenomicInteractions", "GenomicTuples", "genoset", "genotypeeval", "GenVisR", "GGBase", "ggbio", "GGtools", "girafe", "gmapR", "GoogleGenomics", "GOpro", "GOTHiC", "gQTLstats", "GUIDEseq", "gwascat", "h5vc", "HTSeqGenie", "InPAS", "INSPEcT", "intansv", "InteractionSet", "IVAS", "JunctionSeq", "LOLA", "M3D", "MADSEQ", "MafDb.1Kgenomes.phase1.hs37d5", "MafDb.1Kgenomes.phase3.hs37d5", "MafDb.ESP6500SI.V2.SSA137", "MafDb.ESP6500SI.V2.SSA137.GRCh38", "MafDb.ESP6500SI.V2.SSA137.hs37d5", "MafDb.ExAC.r0.3.1.nonTCGA.snvs.hs37d5", "MafDb.ExAC.r0.3.1.snvs.hs37d5", "MatrixRider", "MEAL", "MEDIPS", "metagene", "methVisual", "methyAnalysis", "methylKit", "methylPipe", "MethylSeekR", "methylumi", "minfi", "MinimumDistance", "mosaics", "motifbreakR", "motifRG", "MotIV", "msa", "MSnbase", "MultiAssayExperiment", "MultiDataSet", "MutationalPatterns", "NarrowPeaks", "normr", "nucleoSim", "nucleR", "oligoClasses", "OrganismDbi", "Pbase", "pcaExplorer", "pd.081229.hg18.promoter.medip.hx1", "pd.2006.07.18.hg18.refseq.promoter", "pd.2006.07.18.mm8.refseq.promoter", "pd.2006.10.31.rn34.refseq.promoter", "pd.atdschip.tiling", "pd.charm.hg18.example", "pd.feinberg.hg18.me.hx1", "pd.feinberg.mm8.me.hx1", "pd.mirna.3.1", "pdInfoBuilder", "phastCons100way.UCSC.hg19", "phastCons100way.UCSC.hg38", "phastCons7way.UCSC.hg38", "PICS", "PING", "plethy", "podkat", "polyester", "pqsfinder", "prebs", "PureCN", "Pviz", "QDNAseq", "qpgraph", "qsea", "QuasR", "R3CPET", "r3Cseq", "R453Plus1Toolbox", "RareVariantVis", "Rariant", "Rcade", "rCGH", "recount", "REDseq", "regioneR", "Repitools", "ReportingTools", "rGADEM", "RiboProfiling", "riboSeqR", "rMAT", "rnaSeqMap", "RnBeads", "roar", "Rqc", "Rsamtools", "rSFFreader", "RSVSim", "RTN", "rtracklayer", "SCAN.UPC", "segmentSeq", "SeqArray", "seqPattern", "seqplots", "SeqVarTools", "ShortRead", "simulatorZ", "skewr", "SMITE", "SNPchip", "SNPhood", "SNPlocs.Hsapiens.dbSNP.20090506", "SNPlocs.Hsapiens.dbSNP.20100427", "SNPlocs.Hsapiens.dbSNP.20101109", "SNPlocs.Hsapiens.dbSNP.20110815", "SNPlocs.Hsapiens.dbSNP.20111119", "SNPlocs.Hsapiens.dbSNP.20120608", "SNPlocs.Hsapiens.dbSNP141.GRCh38", "SNPlocs.Hsapiens.dbSNP142.GRCh37", "SNPlocs.Hsapiens.dbSNP144.GRCh37", "SNPlocs.Hsapiens.dbSNP144.GRCh38", "soGGi", "SomaticCancerAlterations", "SomaticSignatures", "spliceR", "spliceSites", "SplicingGraphs", "SPLINTER", "STAN", "SummarizedExperiment", "SVM2CRM", "TarSeqQC", "TCGAbiolinks", "TFBSTools", "tracktables", "trackViewer", "transcriptR", "TransView", "triform", "TSSi", "TVTB", "VanillaICE", "VariantAnnotation", "VariantFiltering", "wavClusteR", "waveTiling", "XtraSNPlocs.Hsapiens.dbSNP141.GRCh38", "XtraSNPlocs.Hsapiens.dbSNP144.GRCh37", "XtraSNPlocs.Hsapiens.dbSNP144.GRCh38", "XVector", "yamss" ], "suggestsMe": [ "annotate", "AnnotationHub", "BaseSpaceR", "BiocGenerics", "Chicago", "ClassifyR", "gQTLBase", "HilbertVis", "HilbertVisGUI", "MiRaGE", "regionReport", "RTCGA", "S4Vectors", "yeastRNASeq" ] }, "iSeq": { "Package": "iSeq", "Version": "1.26.0", "Depends": [ "R (>= 2.10.0)" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "d1331363ee5a8a926c6cecf6fac165bc", "NeedsCompilation": "yes", "Title": "Bayesian Hierarchical Modeling of ChIP-seq Data Through Hidden Ising Models", "Description": "This package uses Bayesian hidden Ising models to identify IP-enriched genomic regions from ChIP-seq data. It can be used to analyze ChIP-seq data with and without controls and replicates.", "biocViews": [ "ChIPSeq", "Sequencing", "Software" ], "Author": "Qianxing Mo", "Maintainer": "Qianxing Mo ", "source.ver": "src/contrib/iSeq_1.26.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/iSeq_1.26.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/iSeq_1.26.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/iSeq_1.26.0.tgz", "vignettes": [ "vignettes/iSeq/inst/doc/iSeq.pdf" ], "vignetteTitles": [ "iSeq" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/iSeq/inst/doc/iSeq.R" ] }, "isobar": { "Package": "isobar", "Version": "1.20.0", "Depends": [ "R (>= 2.10.0)", "Biobase", "stats", "methods" ], "Imports": [ "distr", "plyr", "biomaRt", "ggplot2" ], "Suggests": [ "MSnbase", "OrgMassSpecR", "XML", "RJSONIO", "Hmisc", "gplots", "RColorBrewer", "gridExtra", "limma", "boot", "DBI", "MASS" ], "License": "LGPL-2", "MD5sum": "cdaa4c3983602ce4ec8cbeecd56eed2e", "NeedsCompilation": "no", "Title": "Analysis and quantitation of isobarically tagged MSMS proteomics data", "Description": "isobar provides methods for preprocessing, normalization, and report generation for the analysis of quantitative mass spectrometry proteomics data labeled with isobaric tags, such as iTRAQ and TMT. Features modules for integrating and validating PTM-centric datasets (isobar-PTM). More information on http://www.ms-isobar.org.", "biocViews": [ "Bioinformatics", "MassSpectrometry", "MultipleComparisons", "Proteomics", "QualityControl", "Software" ], "Author": "Florian P Breitwieser and Jacques Colinge , with contributions from Alexey Stukalov , Xavier Robin and Florent Gluck ", "Maintainer": "Florian P Breitwieser ", "URL": "https://github.com/fbreitwieser/isobar", "BugReports": "https://github.com/fbreitwieser/isobar/issues", "source.ver": "src/contrib/isobar_1.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/isobar_1.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/isobar_1.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/isobar_1.20.0.tgz", "vignettes": [ "vignettes/isobar/inst/doc/isobar-devel.pdf", "vignettes/isobar/inst/doc/isobar-ptm.pdf", "vignettes/isobar/inst/doc/isobar-usecases.pdf", "vignettes/isobar/inst/doc/isobar.pdf" ], "vignetteTitles": [ "isobar for developers", "isobar for quantification of PTM datasets", "Usecases for isobar package", "isobar package for iTRAQ and TMT protein quantification" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/isobar/inst/doc/isobar-devel.R", "vignettes/isobar/inst/doc/isobar-ptm.R", "vignettes/isobar/inst/doc/isobar-usecases.R", "vignettes/isobar/inst/doc/isobar.R" ], "suggestsMe": [ "RforProteomics" ] }, "IsoGeneGUI": { "Package": "IsoGeneGUI", "Version": "2.10.0", "Depends": [ "tcltk", "xlsx" ], "Imports": [ "Rcpp", "tkrplot", "multtest", "relimp", "geneplotter", "RColorBrewer", "Iso", "IsoGene", "ORCME", "ORIClust", "orQA", "goric", "ff", "Biobase", "jpeg" ], "Suggests": [ "RUnit" ], "License": "GPL-2", "MD5sum": "c9c69e1ac53eb3180d28ca4e3d04c206", "NeedsCompilation": "no", "Title": "A graphical user interface to conduct a dose-response analysis of microarray data", "Description": "The IsoGene Graphical User Interface (IsoGene-GUI) is a user friendly interface of the IsoGene package which is aimed to identify for genes with a monotonic trend in the expression levels with respect to the increasing doses. Additionally, GUI extension of original package contains various tools to perform clustering of dose-response profiles. Testing is addressed through several test statistics: global likelihood ratio test (E2), Bartholomew 1961, Barlow et al. 1972 and Robertson et al. 1988), Williams (1971, 1972), Marcus (1976), the M (Hu et al. 2005) and the modified M (Lin et al. 2007). The p-values of the global likelihood ratio test (E2) are obtained using the exact distribution and permutations. The other four test statistics are obtained using permutations. Several p-values adjustment are provided: Bonferroni, Holm (1979), Hochberg (1988), and Sidak procedures for controlling the family-wise Type I error rate (FWER), and BH (Benjamini and Hochberg 1995) and BY (Benjamini and Yekutieli 2001) procedures are used for controlling the FDR. The inference is based on resampling methods, which control the False Discovery Rate (FDR), for both permutations (Ge et al., 2003) and the Significance Analysis of Microarrays (SAM, Tusher et al., 2001). Clustering methods are outsourced from CRAN packages ORCME, ORIClust. The package ORCME is based on delta-clustering method (Cheng and Church, 2000) and ORIClust on Order Restricted Information Criterion (Liu et al., 2009), both perform same task but from different perspective and their outputs are clusters of genes. Additionally, profile selection for given gene based on Generalized ORIC (Kuiper et al., 2014) from package goric and permutation test for E2 based on package orQA are included in IsoGene-GUI. None of these four packages has GUI.", "biocViews": [ "DifferentialExpression", "GUI", "Microarray", "Software" ], "Author": "Setia Pramana, Dan Lin, Philippe Haldermans, Tobias Verbeke, Martin Otava", "Maintainer": "Setia Pramana ", "URL": "http://ibiostat.be/online-resources/online-resources/isogenegui/isogenegui-package", "source.ver": "src/contrib/IsoGeneGUI_2.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/IsoGeneGUI_2.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/IsoGeneGUI_2.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/IsoGeneGUI_2.10.0.tgz", "vignettes": [ "vignettes/IsoGeneGUI/inst/doc/IsoGeneGUI.pdf" ], "vignetteTitles": [ "IsoGeneGUI Vignette" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/IsoGeneGUI/inst/doc/IsoGeneGUI.R" ] }, "ISoLDE": { "Package": "ISoLDE", "Version": "1.2.0", "Depends": [ "R (>= 3.3.0)", "graphics", "grDevices", "stats", "utils" ], "License": "GPL (>= 2.0)", "Archs": "i386, x64", "MD5sum": "d8ee91dd636a7bd6c4d787f3c2f7948a", "NeedsCompilation": "yes", "Title": "Integrative Statistics of alleLe Dependent Expression", "Description": "This package provides ISoLDE a new method for identifying imprinted genes. This method is dedicated to data arising from RNA sequencing technologies. The ISoLDE package implements original statistical methodology described in the publication below.", "biocViews": [ "Epigenetics", "GeneExpression", "GeneRegulation", "GeneSetEnrichment", "GeneticVariability", "Genetics", "MathematicalBiology", "MultipleComparison", "RNASeq", "SNP", "Sequencing", "Software", "Transcription" ], "Author": "Christelle Reynès [aut, cre], Marine Rohmer [aut], Guilhem Kister [aut]", "Maintainer": "Christelle Reynès ", "URL": "www.r-project.org", "source.ver": "src/contrib/ISoLDE_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ISoLDE_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ISoLDE_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ISoLDE_1.2.0.tgz", "hasREADME": true, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false }, "isomiRs": { "Package": "isomiRs", "Version": "1.2.0", "Depends": [ "R (>= 3.2)", "DiscriMiner", "IRanges", "S4Vectors (>= 0.9.25)", "GenomicRanges", "SummarizedExperiment (>= 1.1.6)" ], "Imports": [ "BiocGenerics (>= 0.7.5)", "DESeq2", "reshape", "tidyr", "plyr", "readr", "dplyr", "RColorBrewer", "gplots", "methods", "ggplot2", "gtools", "gridExtra", "grid", "GGally" ], "Suggests": [ "knitr", "RUnit", "org.Mm.eg.db", "cluster", "clusterProfiler", "BiocStyle" ], "License": "MIT + file LICENSE", "MD5sum": "4ac35c8e16846c2f26e88c5fa2254780", "NeedsCompilation": "no", "Title": "Analyze isomiRs and miRNAs from small RNA-seq", "Description": "Characterization of miRNAs and isomiRs, clustering and differential expression.", "biocViews": [ "Clustering", "DifferentialExpression", "RNASeq", "Software", "miRNA" ], "Author": "Lorena Pantano, Georgia Escaramis", "Maintainer": "Lorena Pantano ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/isomiRs_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/isomiRs_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/isomiRs_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/isomiRs_1.2.0.tgz", "vignettes": [ "vignettes/isomiRs/inst/doc/isomiRs-intro.pdf" ], "vignetteTitles": [ "isomiRs" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/isomiRs/inst/doc/isomiRs-intro.R" ] }, "ITALICS": { "Package": "ITALICS", "Version": "2.34.0", "Depends": [ "R (>= 2.0.0)", "GLAD", "ITALICSData", "oligo", "affxparser", "pd.mapping50k.xba240" ], "Imports": [ "affxparser", "DBI", "GLAD", "oligo", "oligoClasses", "stats" ], "Suggests": [ "pd.mapping50k.hind240", "pd.mapping250k.sty", "pd.mapping250k.nsp" ], "License": "GPL-2", "MD5sum": "b7ff91941c700463d2ff5a2f30239b61", "NeedsCompilation": "no", "Title": "ITALICS", "Description": "A Method to normalize of Affymetrix GeneChip Human Mapping 100K and 500K set", "biocViews": [ "CopyNumberVariation", "Microarray", "Software" ], "Author": "Guillem Rigaill, Philippe Hupe", "Maintainer": "Guillem Rigaill ", "URL": "http://bioinfo.curie.fr", "source.ver": "src/contrib/ITALICS_2.34.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ITALICS_2.34.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ITALICS_2.34.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ITALICS_2.34.0.tgz", "vignettes": [ "vignettes/ITALICS/inst/doc/ITALICS.pdf" ], "vignetteTitles": [ "ITALICS" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ITALICS/inst/doc/ITALICS.R" ] }, "iterativeBMA": { "Package": "iterativeBMA", "Version": "1.32.0", "Depends": [ "BMA", "leaps", "Biobase (>= 2.5.5)" ], "License": "GPL (>= 2)", "MD5sum": "8782da00c5e7cd46515f741c2aaa15ce", "NeedsCompilation": "no", "Title": "The Iterative Bayesian Model Averaging (BMA) algorithm", "Description": "The iterative Bayesian Model Averaging (BMA) algorithm is a variable selection and classification algorithm with an application of classifying 2-class microarray samples, as described in Yeung, Bumgarner and Raftery (Bioinformatics 2005, 21: 2394-2402).", "biocViews": [ "Classification", "Microarray", "Software" ], "Author": "Ka Yee Yeung, University of Washington, Seattle, WA, with contributions from Adrian Raftery and Ian Painter", "Maintainer": "Ka Yee Yeung ", "URL": "http://faculty.washington.edu/kayee/research.html", "source.ver": "src/contrib/iterativeBMA_1.32.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/iterativeBMA_1.32.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/iterativeBMA_1.32.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/iterativeBMA_1.32.0.tgz", "vignettes": [ "vignettes/iterativeBMA/inst/doc/iterativeBMA.pdf" ], "vignetteTitles": [ "The Iterative Bayesian Model Averaging Algorithm" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/iterativeBMA/inst/doc/iterativeBMA.R" ] }, "iterativeBMAsurv": { "Package": "iterativeBMAsurv", "Version": "1.32.0", "Depends": [ "BMA", "leaps", "survival", "splines" ], "Imports": [ "graphics", "grDevices", "stats", "survival", "utils" ], "License": "GPL (>= 2)", "MD5sum": "37bda6802cd067eabc2eca36a3eb4400", "NeedsCompilation": "no", "Title": "The Iterative Bayesian Model Averaging (BMA) Algorithm For Survival Analysis", "Description": "The iterative Bayesian Model Averaging (BMA) algorithm for survival analysis is a variable selection method for applying survival analysis to microarray data.", "biocViews": [ "Microarray", "Software" ], "Author": "Amalia Annest, University of Washington, Tacoma, WA Ka Yee Yeung, University of Washington, Seattle, WA", "Maintainer": "Ka Yee Yeung ", "URL": "http://expression.washington.edu/ibmasurv/protected", "source.ver": "src/contrib/iterativeBMAsurv_1.32.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/iterativeBMAsurv_1.32.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/iterativeBMAsurv_1.32.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/iterativeBMAsurv_1.32.0.tgz", "vignettes": [ "vignettes/iterativeBMAsurv/inst/doc/iterativeBMAsurv.pdf" ], "vignetteTitles": [ "The Iterative Bayesian Model Averaging Algorithm For Survival Analysis" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/iterativeBMAsurv/inst/doc/iterativeBMAsurv.R" ] }, "IVAS": { "Package": "IVAS", "Version": "1.6.0", "Depends": [ "R (> 3.0.0)", "GenomicFeatures" ], "Imports": [ "doParallel", "lme4", "Matrix", "BiocGenerics", "GenomicRanges", "IRanges", "foreach", "AnnotationDbi", "S4Vectors", "GenomeInfoDb" ], "Suggests": [ "BiocStyle" ], "License": "GPL-2", "MD5sum": "a923c93d3c6a3845cf92704bf8161efc", "NeedsCompilation": "no", "Title": "Identification of genetic Variants affecting Alternative Splicing", "Description": "Identification of genetic variants affecting alternative splicing.", "biocViews": [ "AlternativeSplicing", "DifferentialExpression", "DifferentialSplicing", "GeneExpression", "GeneRegulation", "RNASeq", "Regression", "SNP", "Sequencing", "Software", "Transcription" ], "Author": "Seonggyun Han, Sangsoo Kim", "Maintainer": "Seonggyun Han ", "source.ver": "src/contrib/IVAS_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/IVAS_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/IVAS_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/IVAS_1.6.0.tgz", "vignettes": [ "vignettes/IVAS/inst/doc/IVAS.pdf" ], "vignetteTitles": [ "IVAS : Identification of genetic Variants affecting Alternative Splicing" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/IVAS/inst/doc/IVAS.R" ] }, "joda": { "Package": "joda", "Version": "1.22.0", "Depends": [ "R (>= 2.0)", "bgmm", "RBGL" ], "License": "GPL (>= 2)", "MD5sum": "a0ff1d5f557e10c2f54aa5a1e6befd8a", "NeedsCompilation": "no", "Title": "JODA algorithm for quantifying gene deregulation using knowledge", "Description": "Package 'joda' implements three steps of an algorithm called JODA. The algorithm computes gene deregulation scores. For each gene, its deregulation score reflects how strongly an effect of a certain regulator's perturbation on this gene differs between two different cell populations. The algorithm utilizes regulator knockdown expression data as well as knowledge about signaling pathways in which the regulators are involved (formalized in a simple matrix model).", "biocViews": [ "GraphAndNetwork", "Microarray", "NetworkInference", "Pathways", "Software", "StatisticalMethod" ], "Author": "Ewa Szczurek", "Maintainer": "Ewa Szczurek ", "URL": "http://www.bioconductor.org", "source.ver": "src/contrib/joda_1.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/joda_1.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/joda_1.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/joda_1.22.0.tgz", "vignettes": [ "vignettes/joda/inst/doc/JodaVignette.pdf" ], "vignetteTitles": [ "Introduction to joda" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/joda/inst/doc/JodaVignette.R" ] }, "JunctionSeq": { "Package": "JunctionSeq", "Version": "1.4.0", "Depends": [ "R (>= 3.2.2)", "methods", "SummarizedExperiment (>= 0.2.0)" ], "Imports": [ "DESeq2 (>= 1.10.0)", "statmod", "Hmisc", "plotrix", "stringr", "Biobase (>= 2.30.0)", "locfit", "BiocGenerics (>= 0.7.5)", "BiocParallel", "genefilter", "geneplotter", "S4Vectors", "IRanges", "GenomicRanges" ], "Suggests": [ "MASS", "knitr", "JctSeqData", "BiocStyle" ], "Enhances": [ "Cairo", "pryr" ], "License": "file LICENSE", "MD5sum": "4e467dc06ce264cec3aa6d02a6ad3378", "NeedsCompilation": "no", "Title": "JunctionSeq: A Utility for Detection of Differential Exon and Splice-Junction Usage in RNA-Seq data", "Description": "A Utility for Detection and Visualization of Differential Exon or Splice-Junction Usage in RNA-Seq data.", "biocViews": [ "DifferentialExpression", "RNASeq", "Sequencing", "Software" ], "Author": "Stephen Hartley [aut, cre] (PhD), Simon Anders [cph], Alejandro Reyes [cph]", "Maintainer": "Stephen Hartley ", "URL": "http://hartleys.github.io/JunctionSeq/index.html", "VignetteBuilder": "knitr", "BugReports": "https://github.com/hartleys/JunctionSeq/issues", "source.ver": "src/contrib/JunctionSeq_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/JunctionSeq_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/JunctionSeq_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/JunctionSeq_1.4.0.tgz", "vignettes": [ "vignettes/JunctionSeq/inst/doc/JunctionSeq.pdf" ], "vignetteTitles": [ "JunctionSeq Vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "suggestsMe": [ "JctSeqData" ] }, "KCsmart": { "Package": "KCsmart", "Version": "2.32.0", "Depends": [ "siggenes", "multtest", "KernSmooth" ], "Imports": [ "methods", "BiocGenerics" ], "Enhances": [ "Biobase", "CGHbase" ], "License": "GPL-3", "MD5sum": "6a2722f2c19b0b41d1caac1a7969318c", "NeedsCompilation": "no", "Title": "Multi sample aCGH analysis package using kernel convolution", "Description": "Multi sample aCGH analysis package using kernel convolution", "biocViews": [ "CopyNumberVariation", "Microarray", "Software", "Visualization", "aCGH" ], "Author": "Jorma de Ronde, Christiaan Klijn, Arno Velds", "Maintainer": "Jorma de Ronde ", "source.ver": "src/contrib/KCsmart_2.32.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/KCsmart_2.32.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/KCsmart_2.32.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/KCsmart_2.32.0.tgz", "vignettes": [ "vignettes/KCsmart/inst/doc/KCS.pdf" ], "vignetteTitles": [ "KCsmart example session" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/KCsmart/inst/doc/KCS.R" ] }, "kebabs": { "Package": "kebabs", "Version": "1.8.1", "Depends": [ "R (>= 3.2.0)", "Biostrings (>= 2.35.5)", "kernlab" ], "Imports": [ "methods", "stats", "Rcpp (>= 0.11.2)", "Matrix", "XVector (>= 0.7.3)", "S4Vectors (>= 0.5.11)", "e1071", "LiblineaR", "graphics", "grDevices", "utils", "apcluster" ], "LinkingTo": [ "IRanges", "XVector", "Biostrings", "Rcpp", "S4Vectors" ], "Suggests": [ "SparseM", "Biobase", "BiocGenerics", "knitr" ], "License": "GPL (>= 2.1)", "Archs": "i386, x64", "MD5sum": "a6e580b74551375fbd8d975eb5904c0e", "NeedsCompilation": "yes", "Title": "Kernel-Based Analysis Of Biological Sequences", "Description": "The package provides functionality for kernel-based analysis of DNA, RNA, and amino acid sequences via SVM-based methods. As core functionality, kebabs implements following sequence kernels: spectrum kernel, mismatch kernel, gappy pair kernel, and motif kernel. Apart from an efficient implementation of standard position-independent functionality, the kernels are extended in a novel way to take the position of patterns into account for the similarity measure. Because of the flexibility of the kernel formulation, other kernels like the weighted degree kernel or the shifted weighted degree kernel with constant weighting of positions are included as special cases. An annotation-specific variant of the kernels uses annotation information placed along the sequence together with the patterns in the sequence. The package allows for the generation of a kernel matrix or an explicit feature representation in dense or sparse format for all available kernels which can be used with methods implemented in other R packages. With focus on SVM-based methods, kebabs provides a framework which simplifies the usage of existing SVM implementations in kernlab, e1071, and LiblineaR. Binary and multi-class classification as well as regression tasks can be used in a unified way without having to deal with the different functions, parameters, and formats of the selected SVM. As support for choosing hyperparameters, the package provides cross validation - including grouped cross validation, grid search and model selection functions. For easier biological interpretation of the results, the package computes feature weights for all SVMs and prediction profiles which show the contribution of individual sequence positions to the prediction result and indicate the relevance of sequence sections for the learning result and the underlying biological functions.", "biocViews": [ "Classification", "Clustering", "Regression", "Software", "SupportVectorMachine" ], "Author": "Johannes Palme", "Maintainer": "Ulrich Bodenhofer ", "URL": "http://www.bioinf.jku.at/software/kebabs/", "VignetteBuilder": "knitr", "source.ver": "src/contrib/kebabs_1.8.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/kebabs_1.8.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/kebabs_1.8.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/kebabs_1.8.1.tgz", "vignettes": [ "vignettes/kebabs/inst/doc/kebabs.pdf" ], "vignetteTitles": [ "KeBABS - An R Package for Kernel Based Analysis of Biological Sequences" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/kebabs/inst/doc/kebabs.R" ], "dependsOnMe": [ "procoil" ], "importsMe": [ "FindMyFriends", "odseq" ] }, "KEGGgraph": { "Package": "KEGGgraph", "Version": "1.32.0", "Imports": [ "methods", "XML (>= 2.3-0)", "graph" ], "Suggests": [ "Rgraphviz", "RBGL", "RUnit", "RColorBrewer", "KEGG.db", "org.Hs.eg.db", "hgu133plus2.db", "SPIA" ], "License": "GPL (>= 2)", "MD5sum": "926673052cba27aecc7b78cc704f6cd2", "NeedsCompilation": "no", "Title": "KEGGgraph: A graph approach to KEGG PATHWAY in R and Bioconductor", "Description": "KEGGGraph is an interface between KEGG pathway and graph object as well as a collection of tools to analyze, dissect and visualize these graphs. It parses the regularly updated KGML (KEGG XML) files into graph models maintaining all essential pathway attributes. The package offers functionalities including parsing, graph operation, visualization and etc.", "biocViews": [ "GraphAndNetwork", "KEGG", "Pathways", "Software", "Visualization" ], "Author": "Jitao David Zhang, with inputs from Paul Shannon", "Maintainer": "Jitao David Zhang ", "URL": "http://www.nextbiomotif.com", "source.ver": "src/contrib/KEGGgraph_1.32.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/KEGGgraph_1.32.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/KEGGgraph_1.32.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/KEGGgraph_1.32.0.tgz", "vignettes": [ "vignettes/KEGGgraph/inst/doc/KEGGgraph.pdf", "vignettes/KEGGgraph/inst/doc/KEGGgraphApp.pdf" ], "vignetteTitles": [ "KEGGgraph: graph approach to KEGG PATHWAY", "KEGGgraph: Application Examples" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/KEGGgraph/inst/doc/KEGGgraph.R", "vignettes/KEGGgraph/inst/doc/KEGGgraphApp.R" ], "dependsOnMe": [ "ROntoTools", "SPIA" ], "importsMe": [ "clipper", "DEGraph", "EnrichmentBrowser", "KEGGlincs", "MetaboSignal", "NCIgraph", "pathview", "ToPASeq" ], "suggestsMe": [ "DEGraph", "GenomicRanges" ] }, "KEGGlincs": { "Package": "KEGGlincs", "Version": "1.0.0", "Depends": [ "R (>= 3.3)", "KOdata", "hgu133a.db", "org.Hs.eg.db (>= 3.3.0)" ], "Imports": [ "AnnotationDbi", "KEGGgraph", "igraph", "plyr", "gtools", "httr", "RJSONIO", "KEGGREST", "methods", "graphics", "stats", "utils" ], "Suggests": [ "BiocInstaller (>= 1.20.3)", "knitr", "rmarkdown", "graph" ], "License": "GPL-3", "MD5sum": "47aab1ef63f41876cb315a1abef4e345", "NeedsCompilation": "no", "Title": "Visualize all edges within a KEGG pathway and overlay LINCS data [option]", "Description": "See what is going on 'under the hood' of KEGG pathways by explicitly re-creating the pathway maps from information obtained from KGML files.", "biocViews": [ "CellBiology", "DataRepresentation", "GeneExpression", "GraphAndNetwork", "KEGG", "Network", "NetworkInference", "Pathways", "Software", "ThirdPartyClient" ], "Author": "Shana White", "Maintainer": "Shana White ", "SystemRequirements": "Cytoscape (>= 3.3.0), Java (>= 8)", "VignetteBuilder": "knitr", "source.ver": "src/contrib/KEGGlincs_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/KEGGlincs_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/KEGGlincs_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/KEGGlincs_1.0.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/KEGGlincs/inst/doc/Cytoscape_formatting.R", "vignettes/KEGGlincs/inst/doc/Example-workflow.R" ], "htmlDocs": [ "vignettes/KEGGlincs/inst/doc/Cytoscape_formatting.html", "vignettes/KEGGlincs/inst/doc/Example-workflow.html" ], "htmlTitles": [ "KEGGlincs Workflows", "KEGGlincs Workflows" ] }, "keggorthology": { "Package": "keggorthology", "Version": "2.26.0", "Depends": [ "R (>= 2.5.0)", "stats", "graph", "hgu95av2.db" ], "Imports": [ "AnnotationDbi", "graph", "DBI", "graph", "grDevices", "methods", "stats", "tools", "utils" ], "Suggests": [ "RBGL", "ALL" ], "License": "Artistic-2.0", "MD5sum": "8ce2401ca7a502f69851102a947a870d", "NeedsCompilation": "no", "Title": "graph support for KO, KEGG Orthology", "Description": "graphical representation of the Feb 2010 KEGG Orthology. The KEGG orthology is a set of pathway IDs that are not to be confused with the KEGG ortholog IDs.", "biocViews": [ "GraphAndNetwork", "KEGG", "Pathways", "Software", "Visualization" ], "Author": "VJ Carey ", "Maintainer": "VJ Carey ", "source.ver": "src/contrib/keggorthology_2.26.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/keggorthology_2.26.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/keggorthology_2.26.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/keggorthology_2.26.0.tgz", "vignettes": [ "vignettes/keggorthology/inst/doc/keggorth.pdf" ], "vignetteTitles": [ "keggorthology overview" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/keggorthology/inst/doc/keggorth.R" ], "suggestsMe": [ "MLInterfaces" ] }, "KEGGprofile": { "Package": "KEGGprofile", "Version": "1.16.0", "Imports": [ "AnnotationDbi", "png", "TeachingDemos", "XML", "KEGG.db", "KEGGREST", "biomaRt" ], "License": "GPL (>= 2)", "MD5sum": "87d72a2848f516a623dde51fb2ab8dcb", "NeedsCompilation": "no", "Title": "An annotation and visualization package for multi-types and multi-groups expression data in KEGG pathway", "Description": "KEGGprofile is an annotation and visualization tool which integrated the expression profiles and the function annotation in KEGG pathway maps. The multi-types and multi-groups expression data can be visualized in one pathway map. KEGGprofile facilitated more detailed analysis about the specific function changes inner pathway or temporal correlations in different genes and samples.", "biocViews": [ "KEGG", "Pathways", "Software" ], "Author": "Shilin Zhao, Yan Guo, Yu Shyr", "Maintainer": "Shilin Zhao ", "source.ver": "src/contrib/KEGGprofile_1.16.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/KEGGprofile_1.16.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/KEGGprofile_1.16.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/KEGGprofile_1.16.0.tgz", "vignettes": [ "vignettes/KEGGprofile/inst/doc/KEGGprofile.pdf" ], "vignetteTitles": [ "KEGGprofile: Application Examples" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/KEGGprofile/inst/doc/KEGGprofile.R" ], "suggestsMe": [ "FGNet" ] }, "KEGGREST": { "Package": "KEGGREST", "Version": "1.14.1", "Imports": [ "methods", "httr", "png", "Biostrings" ], "Suggests": [ "RUnit", "BiocGenerics", "knitr" ], "License": "Artistic-2.0", "MD5sum": "430ce1c753d7414e848b5dcc4ae890b6", "NeedsCompilation": "no", "Title": "Client-side REST access to KEGG", "Description": "A package that provides a client interface to the KEGG REST server. Based on KEGGSOAP by J. Zhang, R. Gentleman, and Marc Carlson, and KEGG (python package) by Aurelien Mazurie.", "biocViews": [ "Annotation", "KEGG", "Pathways", "Software", "ThirdPartyClient" ], "Author": "Dan Tenenbaum", "Maintainer": "Bioconductor Package Maintainer ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/KEGGREST_1.14.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/KEGGREST_1.14.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/KEGGREST_1.14.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/KEGGREST_1.14.1.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/KEGGREST/inst/doc/KEGGREST-vignette.R" ], "htmlDocs": [ "vignettes/KEGGREST/inst/doc/KEGGREST-vignette.html" ], "htmlTitles": [ "Accessing the KEGG REST API" ], "dependsOnMe": [ "Hiiragi2013", "PAPi", "ROntoTools" ], "importsMe": [ "attract", "CNEr", "EnrichmentBrowser", "gage", "KEGGlincs", "KEGGprofile", "MetaboSignal", "mmnet", "pathview", "RnaSeqSampleSize", "StarBioTrek", "YAPSA" ] }, "kimod": { "Package": "kimod", "Version": "1.2.0", "Depends": [ "R(>= 3.3)", "methods" ], "Imports": [ "cluster", "graphics", "Biobase" ], "License": "GPL (>=2)", "MD5sum": "e4cf0f765c47f4e5630ad39f90e4cb1d", "NeedsCompilation": "no", "Title": "A k-tables approach to integrate multiple Omics-Data", "Description": "This package allows to work with mixed omics data (transcriptomics, proteomics, microarray-chips, rna-seq data), introducing the following improvements: distance options (for numeric and/or categorical variables) for each of the tables, bootstrap resampling techniques on the residuals matrices for all methods, that enable perform confidence ellipses for the projection of individuals, variables and biplot methodology to project variables (gene expression) on the compromise. Since the main purpose of the package is to use these techniques to omic data analysis, it includes an example data from four different microarray platforms (i.e.,Agilent, Affymetrix HGU 95, Affymetrix HGU 133 and Affymetrix HGU 133plus 2.0) on the NCI-60 cell lines.NCI60_4arrays is a list containing the NCI-60 microarray data with only few hundreds of genes randomly selected in each platform to keep the size of the package small. The data are the same that the package omicade4 used to implement the co-inertia analysis. The references in packages follow the style of the APA-6th norm.", "biocViews": [ "ExperimentData", "GeneExpression", "Microarray", "Proteomics", "Software", "Visualization" ], "Author": "Maria Laura Zingaretti, Johanna Altair Demey-Zambrano, Jose Luis Vicente-Villardon, Jhonny Rafael Demey", "Maintainer": "M L Zingaretti ", "source.ver": "src/contrib/kimod_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/kimod_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/kimod_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/kimod_1.2.0.tgz", "vignettes": [ "vignettes/kimod/inst/doc/kimod-vignette.pdf" ], "vignetteTitles": [ "kimod A K-tables approach to integrate multiple Omics-Data in R" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/kimod/inst/doc/kimod-vignette.R" ] }, "lapmix": { "Package": "lapmix", "Version": "1.40.0", "Depends": [ "R (>= 2.6.0)", "stats" ], "Imports": [ "Biobase", "graphics", "grDevices", "methods", "stats", "tools", "utils" ], "License": "GPL (>= 2)", "MD5sum": "6975f98d251be69204926e8024a5cef2", "NeedsCompilation": "no", "Title": "Laplace Mixture Model in Microarray Experiments", "Description": "Laplace mixture modelling of microarray experiments. A hierarchical Bayesian approach is used, and the hyperparameters are estimated using empirical Bayes. The main purpose is to identify differentially expressed genes.", "biocViews": [ "DifferentialExpression", "Microarray", "OneChannel", "Software" ], "Author": "Yann Ruffieux, contributions from Debjani Bhowmick, Anthony C. Davison, and Darlene R. Goldstein", "Maintainer": "Yann Ruffieux ", "URL": "http://www.r-project.org, http://www.bioconductor.org, http://stat.epfl.ch", "source.ver": "src/contrib/lapmix_1.40.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/lapmix_1.40.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/lapmix_1.40.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/lapmix_1.40.0.tgz", "vignettes": [ "vignettes/lapmix/inst/doc/lapmix-example.pdf" ], "vignetteTitles": [ "lapmix example" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/lapmix/inst/doc/lapmix-example.R" ] }, "LBE": { "Package": "LBE", "Version": "1.42.0", "Depends": [ "stats" ], "Imports": [ "graphics", "grDevices", "methods", "stats", "utils" ], "Suggests": [ "qvalue" ], "License": "GPL-2", "MD5sum": "c41651298945d31cc81e171012329ecf", "NeedsCompilation": "no", "Title": "Estimation of the false discovery rate.", "Description": "LBE is an efficient procedure for estimating the proportion of true null hypotheses, the false discovery rate (and so the q-values) in the framework of estimating procedures based on the marginal distribution of the p-values without assumption for the alternative hypothesis.", "biocViews": [ "MultipleComparison", "Software" ], "Author": "Cyril Dalmasso", "Maintainer": "Cyril Dalmasso ", "source.ver": "src/contrib/LBE_1.42.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/LBE_1.42.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/LBE_1.42.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/LBE_1.42.0.tgz", "vignettes": [ "vignettes/LBE/inst/doc/LBE.pdf" ], "vignetteTitles": [ "LBE Vignette" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/LBE/inst/doc/LBE.R" ] }, "ldblock": { "Package": "ldblock", "Version": "1.4.0", "Depends": [ "R (>= 3.1)", "methods" ], "Imports": [ "Matrix", "snpStats" ], "Suggests": [ "RUnit", "BiocGenerics", "knitr" ], "License": "Artistic-2.0", "MD5sum": "4864508e836fb879e216b4700b2edd2a", "NeedsCompilation": "no", "Title": "data structures for linkage disequilibrium measures in populations", "Description": "Define data structures for linkage disequilibrium measures in populations.", "Author": "VJ Carey ", "Maintainer": "VJ Carey ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/ldblock_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ldblock_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ldblock_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ldblock_1.4.0.tgz", "vignettes": [ "vignettes/ldblock/inst/doc/ldblock.pdf" ], "vignetteTitles": [ "LD block import and manipulation" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ldblock/inst/doc/ldblock.R" ], "biocViews": [ "Software" ] }, "LEA": { "Package": "LEA", "Version": "1.6.0", "Depends": [ "R (>= 3.0.2)", "methods", "stats", "utils" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "c1b2d2ab3c441afe2f5684ada64974fb", "NeedsCompilation": "yes", "Title": "LEA: an R package for Landscape and Ecological Association Studies", "Description": "LEA is an R package dedicated to landscape genomics and ecological association tests. LEA can run analyses of population structure and genome scans for local adaptation. It includes statistical methods for estimating ancestry coefficients from large genotypic matrices and evaluating the number of ancestral populations (snmf, pca); and identifying genetic polymorphisms that exhibit high correlation with some environmental gradient or with the variables used as proxies for ecological pressures (lfmm), and controlling the false discovery rate. LEA is mainly based on optimized C programs that can scale with the dimension of very large data sets.", "biocViews": [ "Clustering", "Regression", "Software", "StatisticalMethod" ], "Author": "Eric Frichot , Olivier Francois ", "Maintainer": "Eric Frichot ", "URL": "http://membres-timc.imag.fr/Olivier.Francois/lea.html", "source.ver": "src/contrib/LEA_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/LEA_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/LEA_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/LEA_1.6.0.tgz", "vignettes": [ "vignettes/LEA/inst/doc/LEA.pdf" ], "vignetteTitles": [ "LEA: An R Package for Landscape and Ecological Association Studies" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/LEA/inst/doc/LEA.R" ] }, "LedPred": { "Package": "LedPred", "Version": "1.8.0", "Depends": [ "R (>= 3.2.0)", "e1071 (>= 1.6)" ], "Imports": [ "akima", "ggplot2", "irr", "jsonlite", "parallel", "plot3D", "plyr", "RCurl", "ROCR", "testthat" ], "License": "MIT | file LICENSE", "MD5sum": "63d73fad92b1ecec1c6c521c26ad01a7", "NeedsCompilation": "no", "Title": "Learning from DNA to Predict Enhancers", "Description": "This package aims at creating a predictive model of regulatory sequences used to score unknown sequences based on the content of DNA motifs, next-generation sequencing (NGS) peaks and signals and other numerical scores of the sequences using supervised classification. The package contains a workflow based on the support vector machine (SVM) algorithm that maps features to sequences, optimize SVM parameters and feature number and creates a model that can be stored and used to score the regulatory potential of unknown sequences.", "biocViews": [ "ChIPSeq", "Classification", "MotifAnnotation", "Sequencing", "Software", "SupportVectorMachine" ], "Author": "Elodie Darbo, Denis Seyres, Aitor Gonzalez", "Maintainer": "Aitor Gonzalez ", "BugReports": "https://github.com/aitgon/LedPred/issues", "source.ver": "src/contrib/LedPred_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/LedPred_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/LedPred_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/LedPred_1.8.0.tgz", "vignettes": [ "vignettes/LedPred/inst/doc/LedPred.pdf" ], "vignetteTitles": [ "LedPred Example" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/LedPred/inst/doc/LedPred.R" ] }, "les": { "Package": "les", "Version": "1.24.0", "Depends": [ "R (>= 2.13.2)", "methods", "graphics", "fdrtool" ], "Imports": [ "boot", "gplots", "RColorBrewer" ], "Suggests": [ "Biobase", "limma" ], "Enhances": [ "parallel" ], "License": "GPL-3", "MD5sum": "a99cc9918824579b3921c430a1ca8f04", "NeedsCompilation": "no", "Title": "Identifying Differential Effects in Tiling Microarray Data", "Description": "The 'les' package estimates Loci of Enhanced Significance (LES) in tiling microarray data. These are regions of regulation such as found in differential transcription, CHiP-chip, or DNA modification analysis. The package provides a universal framework suitable for identifying differential effects in tiling microarray data sets, and is independent of the underlying statistics at the level of single probes.", "biocViews": [ "ChIPchip", "DNAMethylation", "DifferentialExpression", "Microarray", "Software", "Transcription" ], "Author": "Julian Gehring, Clemens Kreutz, Jens Timmer", "Maintainer": "Julian Gehring ", "source.ver": "src/contrib/les_1.24.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/les_1.24.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/les_1.24.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/les_1.24.0.tgz", "vignettes": [ "vignettes/les/inst/doc/les.pdf" ], "vignetteTitles": [ "Introduction to the les package: Identifying Differential Effects in Tiling Microarray Data with the Loci of Enhanced Significance Framework" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/les/inst/doc/les.R" ], "importsMe": [ "GSRI" ] }, "lfa": { "Package": "lfa", "Version": "1.4.0", "Depends": [ "R (>= 3.2)" ], "Imports": [ "corpcor" ], "Suggests": [ "knitr", "ggplot2" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "f815be98ee16854a33ff9a332dee1869", "NeedsCompilation": "yes", "Title": "Logistic Factor Analysis for Categorical Data", "Description": "LFA is a method for a PCA analogue on Binomial data via estimation of latent structure in the natural parameter.", "biocViews": [ "DimensionReduction", "PrincipalComponent", "SNP", "Software" ], "Author": "Wei Hao, Minsun Song, John D. Storey", "Maintainer": "Wei Hao , John D. Storey ", "URL": "https://github.com/StoreyLab/lfa", "VignetteBuilder": "knitr", "BugReports": "https://github.com/StoreyLab/lfa/issues", "source.ver": "src/contrib/lfa_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/lfa_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/lfa_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/lfa_1.4.0.tgz", "vignettes": [ "vignettes/lfa/inst/doc/lfa.pdf" ], "vignetteTitles": [ "lfa Package" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/lfa/inst/doc/lfa.R" ], "importsMe": [ "gcatest" ] }, "limma": { "Package": "limma", "Version": "3.30.13", "Depends": [ "R (>= 2.3.0)" ], "Imports": [ "grDevices", "graphics", "stats", "utils", "methods" ], "Suggests": [ "affy", "AnnotationDbi", "BiasedUrn", "Biobase", "ellipse", "GO.db", "gplots", "illuminaio", "locfit", "MASS", "org.Hs.eg.db", "splines", "statmod (>= 1.2.2)", "vsn" ], "License": "GPL (>=2)", "Archs": "i386, x64", "MD5sum": "6505fdccd7ae146652224377cd104e6a", "NeedsCompilation": "yes", "Title": "Linear Models for Microarray Data", "Description": "Data analysis, linear models and differential expression for microarray data.", "biocViews": [ "AlternativeSplicing", "BatchEffect", "Bayesian", "Clustering", "DataImport", "DifferentialExpression", "DifferentialSplicing", "ExonArray", "GeneExpression", "GeneSetEnrichment", "Genetics", "Microarray", "MultipleComparison", "Normalization", "OneChannel", "Preprocessing", "ProprietaryPlatforms", "QualityControl", "RNASeq", "Regression", "Software", "TimeCourse", "Transcription", "TwoChannel", "mRNAMicroarray", "microRNAArray" ], "Author": "Gordon Smyth [cre,aut], Yifang Hu [ctb], Matthew Ritchie [ctb], Jeremy Silver [ctb], James Wettenhall [ctb], Davis McCarthy [ctb], Di Wu [ctb], Wei Shi [ctb], Belinda Phipson [ctb], Aaron Lun [ctb], Natalie Thorne [ctb], Alicia Oshlack [ctb], Carolyn de Graaf [ctb], Yunshun Chen [ctb], Mette Langaas [ctb], Egil Ferkingstad [ctb], Marcus Davy [ctb], Francois Pepin [ctb], Dongseok Choi [ctb]", "Maintainer": "Gordon Smyth ", "URL": "http://bioinf.wehi.edu.au/limma", "source.ver": "src/contrib/limma_3.30.13.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/limma_3.30.13.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/limma_3.30.13.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/limma_3.30.13.tgz", "vignettes": [ "vignettes/limma/inst/doc/intro.pdf", "vignettes/limma/inst/doc/usersguide.pdf" ], "vignetteTitles": [ "Limma One Page Introduction", "usersguide.pdf" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "dependsOnMe": [ "a4Base", "AffyExpress", "AgiMicroRna", "birta", "bsseq", "CALIB", "CCl4", "cghMCR", "ChimpHumanBrainData", "clippda", "codelink", "convert", "Cormotif", "coRNAi", "DrugVsDisease", "edgeR", "ExiMiR", "ExpressionAtlas", "FEM", "Fletcher2013a", "gCMAP", "genefu", "HD2013SGI", "HTqPCR", "maigesPack", "maPredictDSC", "marray", "metagenomeSeq", "metaseqR", "MLSeq", "MmPalateMiRNA", "PGPC", "prot2D", "qpcrNorm", "qusage", "RBM", "Ringo", "RnBeads", "Rnits", "snapCGH", "splineTimeR", "SRGnet", "SSPA", "tRanslatome", "TurboNorm", "wateRmelon" ], "importsMe": [ "ABSSeq", "affycoretools", "affylmGUI", "anamiR", "ArrayExpress", "arrayQuality", "arrayQualityMetrics", "ArrayTools", "attract", "ballgown", "BatchQC", "beadarray", "BeadArrayUseCases", "betr", "birte", "BubbleTree", "bumphunter", "CALIB", "CancerMutationAnalysis", "CancerSubtypes", "casper", "ChAMP", "charm", "ChIPComp", "ChIPpeakAnno", "clusterExperiment", "compcodeR", "CONFESS", "CountClust", "crlmm", "crossmeta", "csaw", "ctsGE", "DAPAR", "debrowser", "derfinderPlot", "DEsubs", "DiffBind", "diffHic", "diffloop", "DmelSGI", "DMRcate", "EBSEA", "eegc", "EGAD", "EGSEA", "EnrichmentBrowser", "erccdashboard", "explorase", "flowBin", "gCrisprTools", "GeneSelectMMD", "GeneSelector", "GGBase", "GOsummaries", "gQTLstats", "GUIDEseq", "HTqPCR", "iCheck", "iChip", "iCOBRA", "InPAS", "limmaGUI", "Linnorm", "lmdme", "LVSmiRNA", "mAPKL", "MEAL", "methylKit", "MethylMix", "minfi", "miRLAB", "missMethyl", "MmPalateMiRNA", "monocle", "MoonlightR", "MSstats", "nem", "nethet", "nondetects", "OGSA", "OLIN", "PAA", "PADOG", "PathoStat", "pbcmc", "pcaExplorer", "PECA", "pepStat", "phenoTest", "polyester", "qsea", "rCGH", "regsplice", "ReportingTools", "Ringo", "RNAinteract", "RNAither", "RTCGAToolbox", "RTN", "RTopper", "scater", "sigaR", "SimBindProfiles", "snapCGH", "STATegRa", "SVAPLSseq", "systemPipeR", "TCGAbiolinks", "timecourse", "ToPASeq", "TPP", "tweeDEseq", "variancePartition", "vsn", "yamss", "yarn" ], "suggestsMe": [ "ABarray", "ADaCGH2", "beadarraySNP", "biobroom", "BiocCaseStudies", "BioNet", "Category", "categoryCompare", "ClassifyR", "CMA", "coGPS", "derfinder", "dyebias", "ELBOW", "gage", "GeneSelector", "GEOquery", "GeuvadisTranscriptExpr", "Glimma", "GSRI", "GSVA", "Harman", "Heatplus", "isobar", "les", "lumi", "mammaPrintData", "MAST", "mdgsa", "methylumi", "MLP", "npGSEA", "oligo", "oneChannelGUI", "oppar", "paxtoolsr", "PGSEA", "piano", "plw", "PREDA", "puma", "Rcade", "RTopper", "rtracklayer", "scran", "seventyGeneData", "subSeq", "sva", "tximport" ] }, "limmaGUI": { "Package": "limmaGUI", "Version": "1.50.0", "Imports": [ "limma", "tcltk", "BiocInstaller", "tkrplot", "R2HTML", "xtable", "gcrma", "AnnotationDbi" ], "License": "GPL (>=2)", "MD5sum": "2adfc18428326cce04544559a8dcc7ed", "NeedsCompilation": "no", "Title": "GUI for limma package with two color microarrays", "Description": "A Graphical User Interface for differential expression analysis of two-color microarray data using the limma package.", "biocViews": [ "BatchEffect", "Bayesian", "DataImport", "DifferentialExpression", "GUI", "GeneExpression", "Microarray", "MultipleComparison", "Normalization", "Preprocessing", "QualityControl", "Regression", "Software", "TimeCourse", "TwoChannel", "mRNAMicroarray" ], "Author": "James Wettenhall [aut], Gordon Smyth [aut], Keith Satterley [ctb], Yifang Hu [ctb]", "Maintainer": "Yifang Hu , Gordon Smyth , Keith Satterley ", "URL": "http://bioinf.wehi.edu.au/limmaGUI/", "source.ver": "src/contrib/limmaGUI_1.50.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/limmaGUI_1.50.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/limmaGUI_1.50.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/limmaGUI_1.50.0.tgz", "vignettes": [ "vignettes/limmaGUI/inst/doc/extract.pdf", "vignettes/limmaGUI/inst/doc/limmaGUI.pdf", "vignettes/limmaGUI/inst/doc/LinModIntro.pdf" ], "vignetteTitles": [ "Extracting limma objects from limmaGUI files", "limmaGUI Vignette", "LinModIntro.pdf" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/limmaGUI/inst/doc/limmaGUI.R" ], "htmlDocs": [ "vignettes/limmaGUI/inst/doc/about.html", "vignettes/limmaGUI/inst/doc/CustMenu.html", "vignettes/limmaGUI/inst/doc/import.html", "vignettes/limmaGUI/inst/doc/index.html", "vignettes/limmaGUI/inst/doc/InputFiles.html", "vignettes/limmaGUI/inst/doc/lgDevel.html", "vignettes/limmaGUI/inst/doc/windowsFocus.html" ], "htmlTitles": [ "about.html", "CustMenu.html", "import.html", "index.html", "InputFiles.html", "lgDevel.html", "windowsFocus.html" ] }, "LINC": { "Package": "LINC", "Version": "1.2.0", "Depends": [ "R (>= 3.3.1)", "methods", "stats" ], "Imports": [ "Rcpp (>= 0.11.0)", "DOSE", "ggtree", "gridExtra", "ape", "grid", "png", "Biobase", "sva", "reshape2", "utils", "grDevices", "org.Hs.eg.db", "clusterProfiler", "ggplot2", "ReactomePA" ], "LinkingTo": [ "Rcpp" ], "Suggests": [ "RUnit", "BiocGenerics", "knitr", "biomaRt" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "686abae2d8fcad037ec9f84da1af2e00", "NeedsCompilation": "yes", "Title": "co-expression of lincRNAs and protein-coding genes", "Description": "This package provides methods to compute co-expression networks of lincRNAs and protein-coding genes. Biological terms associated with the sets of protein-coding genes predict the biological contexts of lincRNAs according to the 'Guilty by Association' approach.", "biocViews": [ "BiologicalQuestion", "GeneExpression", "GeneRegulation", "Software" ], "Author": "Manuel Goepferich, Carl Herrmann", "Maintainer": "Manuel Goepferich ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/LINC_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/LINC_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/LINC_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/LINC_1.2.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/LINC/inst/doc/LINC.R" ], "htmlDocs": [ "vignettes/LINC/inst/doc/LINC.html" ], "htmlTitles": [ "\"LINC - Co-Expression Analysis of lincRNAs\"" ] }, "Linnorm": { "Package": "Linnorm", "Version": "1.2.11", "Depends": [ "R(>= 3.3)" ], "Imports": [ "Rcpp (>= 0.12.2)", "RcppArmadillo", "fpc", "vegan", "mclust", "apcluster", "ggplot2", "ellipse", "limma", "utils", "statmod", "MASS", "igraph", "grDevices", "graphics", "fastcluster", "ggdendro", "zoo", "stats", "amap" ], "LinkingTo": [ "Rcpp", "RcppArmadillo" ], "Suggests": [ "BiocStyle", "knitr", "rmarkdown", "gplots", "RColorBrewer" ], "License": "MIT + file LICENSE", "Archs": "i386, x64", "MD5sum": "9cc3e531e7e8fa23ae0b7841b1827878", "NeedsCompilation": "yes", "Title": "Linear model and normality based transformation method (Linnorm)", "Description": "Please note that significant updates to Linnorm are available in version 1.99.x +, we strongly suggest using the newest version. Linnorm is an R package for the analysis of RNA-seq, scRNA-seq, ChIP-seq count data or any large scale count data. It transforms such datasets for parametric tests. In addition to the transformtion function, the following pipelines are implemented: 1. Cell subpopluation analysis and visualization using PCA clustering, 2. Differential expression analysis or differential peak detection using limma, 3. Highly variable gene discovery and visualization, 4. Gene correlation network analysis and visualization. 5. Hierarchical clustering and plotting. Linnorm can work with raw count, CPM, RPKM, FPKM and TPM. Additionally, Linnorm provides the RnaXSim function for the simulation of RNA-seq raw counts for the evaluation of differential expression analysis methods. RnaXSim can simulate RNA-seq dataset in Gamma, Log Normal, Negative Binomial or Poisson distributions.", "biocViews": [ "BatchEffect", "ChIPSeq", "Clustering", "DifferentialExpression", "GeneExpression", "Genetics", "Network", "Normalization", "PeakDetection", "RNASeq", "Sequencing", "Software", "Transcription" ], "Author": "Shun Hang Yip , Panwen Wang , Jean-Pierre Kocher , Pak Chung Sham , Junwen Wang ", "Maintainer": "Ken Shun Hang Yip ", "URL": "http://www.jjwanglab.org/Linnorm/", "VignetteBuilder": "knitr", "source.ver": "src/contrib/Linnorm_1.2.11.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Linnorm_1.2.11.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Linnorm_1.2.11.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Linnorm_1.2.11.tgz", "vignettes": [ "vignettes/Linnorm/inst/doc/Linnorm_User_Manual.pdf" ], "vignetteTitles": [ "Linnorm User Manual" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/Linnorm/inst/doc/Linnorm_User_Manual.R" ] }, "LiquidAssociation": { "Package": "LiquidAssociation", "Version": "1.28.0", "Depends": [ "geepack", "methods", "yeastCC", "org.Sc.sgd.db" ], "Imports": [ "Biobase", "graphics", "grDevices", "methods", "stats" ], "License": "GPL (>=3)", "MD5sum": "bd2a60adb367c140ae5d1f5f954a38b6", "NeedsCompilation": "no", "Title": "LiquidAssociation", "Description": "The package contains functions for calculate direct and model-based estimators for liquid association. It also provides functions for testing the existence of liquid association given a gene triplet data.", "biocViews": [ "CellBiology", "GeneExpression", "Genetics", "Network", "Pathways", "Software", "TimeCourse" ], "Author": "Yen-Yi Ho ", "Maintainer": "Yen-Yi Ho ", "source.ver": "src/contrib/LiquidAssociation_1.28.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/LiquidAssociation_1.28.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/LiquidAssociation_1.28.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/LiquidAssociation_1.28.0.tgz", "vignettes": [ "vignettes/LiquidAssociation/inst/doc/LiquidAssociation.pdf" ], "vignetteTitles": [ "LiquidAssociation Vignette" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/LiquidAssociation/inst/doc/LiquidAssociation.R" ], "dependsOnMe": [ "fastLiquidAssociation" ] }, "lmdme": { "Package": "lmdme", "Version": "1.16.0", "Depends": [ "R (>= 2.14.1)", "pls", "stemHypoxia" ], "Imports": [ "stats", "methods", "limma" ], "Enhances": [ "parallel" ], "License": "GPL (>=2)", "MD5sum": "c9d7c886b275142dd8230c0298af9273", "NeedsCompilation": "no", "Title": "Linear Model decomposition for Designed Multivariate Experiments", "Description": "linear ANOVA decomposition of Multivariate Designed Experiments implementation based on limma lmFit. Features: i)Flexible formula type interface, ii) Fast limma based implementation, iii) p-values for each estimated coefficient levels in each factor, iv) F values for factor effects and v) plotting functions for PCA and PLS.", "biocViews": [ "Cancer", "DifferentialExpression", "ExperimentData", "Microarray", "OneChannel", "Software", "TwoChannel", "Visualization" ], "Author": "Cristobal Fresno and Elmer A. Fernandez", "Maintainer": "Cristobal Fresno ", "URL": "http://www.bdmg.com.ar/?page_id=38", "source.ver": "src/contrib/lmdme_1.16.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/lmdme_1.16.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/lmdme_1.16.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/lmdme_1.16.0.tgz", "vignettes": [ "vignettes/lmdme/inst/doc/lmdme-vignette.pdf" ], "vignetteTitles": [ "lmdme: linear model framework for PCA/PLS analysis of ANOVA decomposition on Designed Multivariate Experiments in R" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/lmdme/inst/doc/lmdme-vignette.R" ] }, "LMGene": { "Package": "LMGene", "Version": "2.30.0", "Depends": [ "R (>= 2.10.0)", "Biobase (>= 2.5.5)", "multtest", "survival", "affy" ], "Suggests": [ "affydata" ], "License": "LGPL", "MD5sum": "6cf301e8162659abcc3cf0b56405e49b", "NeedsCompilation": "no", "Title": "LMGene Software for Data Transformation and Identification of Differentially Expressed Genes in Gene Expression Arrays", "Description": "LMGene package for analysis of microarray data using a linear model and glog data transformation", "biocViews": [ "DifferentialExpression", "Microarray", "Preprocessing", "Software" ], "Author": "David Rocke, Geun Cheol Lee, John Tillinghast, Blythe Durbin-Johnson, and Shiquan Wu", "Maintainer": "Blythe Durbin-Johnson ", "URL": "http://dmrocke.ucdavis.edu/software.html", "source.ver": "src/contrib/LMGene_2.30.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/LMGene_2.30.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/LMGene_2.30.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/LMGene_2.30.0.tgz", "vignettes": [ "vignettes/LMGene/inst/doc/LMGene.pdf" ], "vignetteTitles": [ "LMGene User's Guide" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/LMGene/inst/doc/LMGene.R" ] }, "LOBSTAHS": { "Package": "LOBSTAHS", "Version": "1.0.0", "Depends": [ "R (>= 3.3)", "xcms", "CAMERA", "methods" ], "Imports": [ "utils" ], "Suggests": [ "PtH2O2lipids", "knitr", "rmarkdown" ], "License": "GPL (>= 3) + file LICENSE", "MD5sum": "bc0a9ca607fc5afba59f56266307ffce", "NeedsCompilation": "no", "Title": "Lipid and Oxylipin Biomarker Screening through Adduct Hierarchy Sequences", "Description": "LOBSTAHS is a multifunction package for screening, annotation, and putative identification of mass spectral features in large, HPLC-MS lipid datasets. In silico data for a wide range of lipids, oxidized lipids, and oxylipins can be generated from user-supplied structural criteria with a database generation function. LOBSTAHS then applies these databases to assign putative compound identities to features in any high-mass accuracy dataset that has been processed using xcms and CAMERA. Users can then apply a series of orthogonal screening criteria based on adduct ion formation patterns, chromatographic retention time, and other properties, to evaluate and assign confidence scores to this list of preliminary assignments. During the screening routine, LOBSTAHS rejects assignments that do not meet the specified criteria, identifies potential isomers and isobars, and assigns a variety of annotation codes to assist the user in evaluating the accuracy of each assignment.", "biocViews": [ "DataImport", "Lipidomics", "MassSpectrometry", "Metabolomics", "Software" ], "Author": "James Collins [aut, cre], Helen Fredricks [aut], Bethanie Edwards [aut], Benjamin Van Mooy [aut]", "Maintainer": "James Collins ", "URL": "http://bioconductor.org/packages/LOBSTAHS", "VignetteBuilder": "knitr", "BugReports": "https://github.com/vanmooylipidomics/LOBSTAHS/issues/new", "source.ver": "src/contrib/LOBSTAHS_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/LOBSTAHS_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/LOBSTAHS_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/LOBSTAHS_1.0.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/LOBSTAHS/inst/doc/LOBSTAHS.R" ], "htmlDocs": [ "vignettes/LOBSTAHS/inst/doc/LOBSTAHS.html" ], "htmlTitles": [ "Discovery, Identification, and Screening of Lipids and Oxylipins in HPLC-MS Datasets Using LOBSTAHS" ], "dependsOnMe": [ "PtH2O2lipids" ] }, "logicFS": { "Package": "logicFS", "Version": "1.44.0", "Depends": [ "LogicReg", "mcbiopi" ], "Suggests": [ "genefilter", "siggenes" ], "License": "LGPL (>= 2)", "MD5sum": "74ac874eff6653311565aa0e754ef999", "NeedsCompilation": "no", "Title": "Identification of SNP Interactions", "Description": "Identification of interactions between binary variables using Logic Regression. Can, e.g., be used to find interesting SNP interactions. Contains also a bagging version of logic regression for classification.", "biocViews": [ "Classification", "Genetics", "SNP", "Software" ], "Author": "Holger Schwender", "Maintainer": "Holger Schwender ", "source.ver": "src/contrib/logicFS_1.44.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/logicFS_1.44.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/logicFS_1.44.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/logicFS_1.44.0.tgz", "vignettes": [ "vignettes/logicFS/inst/doc/logicFS.pdf" ], "vignetteTitles": [ "logicFS Manual" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/logicFS/inst/doc/logicFS.R" ], "suggestsMe": [ "trio" ] }, "logitT": { "Package": "logitT", "Version": "1.32.0", "Depends": [ "affy" ], "Suggests": [ "SpikeInSubset" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "859580e68700c2c60c9c52d353f855b1", "NeedsCompilation": "yes", "Title": "logit-t Package", "Description": "The logitT library implements the Logit-t algorithm introduced in --A high performance test of differential gene expression for oligonucleotide arrays-- by William J Lemon, Sandya Liyanarachchi and Ming You for use with Affymetrix data stored in an AffyBatch object in R.", "biocViews": [ "DifferentialExpression", "Microarray", "Software" ], "Author": "Tobias Guennel ", "Maintainer": "Tobias Guennel ", "URL": "http://www.bioconductor.org", "source.ver": "src/contrib/logitT_1.32.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/logitT_1.32.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/logitT_1.32.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/logitT_1.32.0.tgz", "vignettes": [ "vignettes/logitT/inst/doc/logitT.pdf" ], "vignetteTitles": [ "logitT primer" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/logitT/inst/doc/logitT.R" ] }, "lol": { "Package": "lol", "Version": "1.22.0", "Depends": [ "penalized", "Matrix" ], "Imports": [ "Matrix", "penalized", "graphics", "grDevices", "stats" ], "License": "GPL-2", "MD5sum": "a57875361554bbba7b392efe98ef69b8", "NeedsCompilation": "no", "Title": "Lots Of Lasso", "Description": "Various optimization methods for Lasso inference with matrix warpper", "biocViews": [ "Software", "StatisticalMethod" ], "Author": "Yinyin Yuan", "Maintainer": "Yinyin Yuan ", "source.ver": "src/contrib/lol_1.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/lol_1.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/lol_1.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/lol_1.22.0.tgz", "vignettes": [ "vignettes/lol/inst/doc/lol.pdf" ], "vignetteTitles": [ "An introduction to the lol package" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/lol/inst/doc/lol.R" ] }, "LOLA": { "Package": "LOLA", "Version": "1.4.0", "Imports": [ "BiocGenerics", "S4Vectors", "IRanges", "GenomicRanges", "data.table" ], "Suggests": [ "knitr", "parallel", "testthat" ], "Enhances": [ "simpleCache", "qvalue" ], "License": "GPL-3", "MD5sum": "98bf205426d236511f7f28b7813cbe55", "NeedsCompilation": "no", "Title": "Location overlap analysis for enrichment of genomic ranges", "Description": "Provides functions for testing overlap of sets of genomic regions with public and custom region set (genomic ranges) databases. This make is possible to do automated enrichment analysis for genomic region sets, thus facilitating interpretation of functional genomics and epigenomics data.", "biocViews": [ "ChIPSeq", "FunctionalGenomics", "GeneRegulation", "GeneSetEnrichment", "GenomeAnnotation", "MethylSeq", "Sequencing", "Software", "SystemsBiology" ], "Author": "Nathan Sheffield [aut, cre], Christoph Bock [cre]", "Maintainer": "Nathan Sheffield ", "URL": "http://databio.org/lola", "VignetteBuilder": "knitr", "BugReports": "http://github.com/sheffien/LOLA", "source.ver": "src/contrib/LOLA_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/LOLA_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/LOLA_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/LOLA_1.4.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/LOLA/inst/doc/choosingUniverse.R", "vignettes/LOLA/inst/doc/gettingStarted.R", "vignettes/LOLA/inst/doc/usingLOLACore.R" ], "htmlDocs": [ "vignettes/LOLA/inst/doc/choosingUniverse.html", "vignettes/LOLA/inst/doc/gettingStarted.html", "vignettes/LOLA/inst/doc/usingLOLACore.html" ], "htmlTitles": [ "Choosing a LOLA Universe", "Getting Started with LOLA", "Using LOLA Core" ], "suggestsMe": [ "DeepBlueR" ] }, "LowMACA": { "Package": "LowMACA", "Version": "1.6.0", "Depends": [ "R (>= 2.10)" ], "Imports": [ "cgdsr", "parallel", "stringr", "reshape2", "data.table", "RColorBrewer", "methods", "LowMACAAnnotation", "BiocParallel", "motifStack", "Biostrings" ], "Suggests": [ "BiocStyle", "knitr", "rmarkdown" ], "License": "GPL-3", "MD5sum": "ebcaa667175a02113c1f084af2ba0a1a", "NeedsCompilation": "no", "Title": "LowMACA - Low frequency Mutation Analysis via Consensus Alignment", "Description": "The LowMACA package is a simple suite of tools to investigate and analyze the mutation profile of several proteins or pfam domains via consensus alignment. You can conduct an hypothesis driven exploratory analysis using our package simply providing a set of genes or pfam domains of your interest.", "biocViews": [ "Alignment", "DataImport", "MultipleSequenceAlignment", "SequenceMatching", "Sequencing", "Software", "SomaticMutation", "WholeGenome" ], "Author": "Stefano de Pretis , Giorgio Melloni", "Maintainer": "Stefano de Pretis , Giorgio Melloni ", "SystemRequirements": "clustalo, gs, perl", "VignetteBuilder": "knitr", "source.ver": "src/contrib/LowMACA_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/LowMACA_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/LowMACA_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/LowMACA_1.6.0.tgz", "vignettes": [ "vignettes/LowMACA/inst/doc/LowMACA.pdf" ], "vignetteTitles": [ "LowMACA" ], "hasREADME": true, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/LowMACA/inst/doc/LowMACA.R" ] }, "LPE": { "Package": "LPE", "Version": "1.48.0", "Depends": [ "R (>= 2.10)" ], "Imports": [ "stats" ], "License": "LGPL", "MD5sum": "665e951c364ac57d3e8a51c94da4ed1b", "NeedsCompilation": "no", "Title": "Methods for analyzing microarray data using Local Pooled Error (LPE) method", "Description": "This LPE library is used to do significance analysis of microarray data with small number of replicates. It uses resampling based FDR adjustment, and gives less conservative results than traditional 'BH' or 'BY' procedures. Data accepted is raw data in txt format from MAS4, MAS5 or dChip. Data can also be supplied after normalization. LPE library is primarily used for analyzing data between two conditions. To use it for paired data, see LPEP library. For using LPE in multiple conditions, use HEM library.", "biocViews": [ "DifferentialExpression", "Microarray", "Software" ], "Author": "Nitin Jain , Michael O'Connell , Jae K. Lee . Includes R source code contributed by HyungJun Cho ", "Maintainer": "Nitin Jain ", "URL": "http://www.r-project.org, http://www.healthsystem.virginia.edu/internet/hes/biostat/bioinformatics/, http://sourceforge.net/projects/r-lpe/", "source.ver": "src/contrib/LPE_1.48.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/LPE_1.48.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/LPE_1.48.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/LPE_1.48.0.tgz", "vignettes": [ "vignettes/LPE/inst/doc/LPE.pdf" ], "vignetteTitles": [ "LPE test for microarray data with small number of replicates" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/LPE/inst/doc/LPE.R" ], "dependsOnMe": [ "LPEadj", "PLPE" ], "importsMe": [ "LPEadj" ], "suggestsMe": [ "ABarray" ] }, "LPEadj": { "Package": "LPEadj", "Version": "1.34.0", "Depends": [ "LPE" ], "Imports": [ "LPE", "stats" ], "License": "LGPL", "MD5sum": "5db73ba9ad9b9bfe6ffe2f65396d060b", "NeedsCompilation": "no", "Title": "A correction of the local pooled error (LPE) method to replace the asymptotic variance adjustment with an unbiased adjustment based on sample size.", "Description": "Two options are added to the LPE algorithm. The original LPE method sets all variances below the max variance in the ordered distribution of variances to the maximum variance. in LPEadj this option is turned off by default. The second option is to use a variance adjustment based on sample size rather than pi/2. By default the LPEadj uses the sample size based variance adjustment.", "biocViews": [ "Microarray", "Proteomics", "Software" ], "Author": "Carl Murie , Robert Nadon ", "Maintainer": "Carl Murie ", "source.ver": "src/contrib/LPEadj_1.34.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/LPEadj_1.34.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/LPEadj_1.34.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/LPEadj_1.34.0.tgz", "vignettes": [ "vignettes/LPEadj/inst/doc/LPEadj.pdf" ], "vignetteTitles": [ "LPEadj test for microarray data with small number of replicates" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/LPEadj/inst/doc/LPEadj.R" ] }, "lpNet": { "Package": "lpNet", "Version": "2.6.0", "Depends": [ "lpSolve", "nem" ], "License": "Artistic License 2.0", "MD5sum": "3ca5539e4e47efc1d30e09c54840f735", "NeedsCompilation": "no", "Title": "Linear Programming Model for Network Inference", "Description": "lpNet aims at infering biological networks, in particular signaling and gene networks. For that it takes perturbation data, either steady-state or time-series, as input and generates an LP model which allows the inference of signaling networks. For parameter identification either leave-one-out cross-validation or stratified n-fold cross-validation can be used.", "biocViews": [ "NetworkInference", "Software" ], "Author": "Bettina Knapp, Marta R. A. Matos, Johanna Mazur, Lars Kaderali", "Maintainer": "Lars Kaderali ", "source.ver": "src/contrib/lpNet_2.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/lpNet_2.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/lpNet_2.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/lpNet_2.6.0.tgz", "vignettes": [ "vignettes/lpNet/inst/doc/vignette_lpNet.pdf" ], "vignetteTitles": [ "lpNet, network inference with a linear optimization program." ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/lpNet/inst/doc/vignette_lpNet.R" ] }, "lpsymphony": { "Package": "lpsymphony", "Version": "1.2.0", "Depends": [ "R (>= 3.0.0)" ], "Suggests": [ "BiocStyle", "knitr" ], "Enhances": [ "slam" ], "License": "EPL", "Archs": "i386, x64", "MD5sum": "4e6cd258c1f33d1dc6e6bab97199a60c", "NeedsCompilation": "yes", "Title": "Symphony integer linear programming solver in R", "Description": "This package was derived from Rsymphony_0.1-17 from CRAN. These packages provide an R interface to SYMPHONY, an open-source linear programming solver written in C++. The main difference between this package and Rsymphony is that it includes the solver source code (SYMPHONY version 5.6), while Rsymphony expects to find header and library files on the users' system. Thus the intention of lpsymphony is to provide an easy to install interface to SYMPHONY. For Windows, precompiled DLLs are included in this package.", "biocViews": [ "Infrastructure", "Software", "ThirdPartyClient" ], "Author": "Vladislav Kim [aut, cre], Ted Ralphs [ctb], Menal Guzelsoy [ctb], Ashutosh Mahajan [ctb], Reinhard Harter [ctb], Kurt Hornik [ctb], Cyrille Szymanski [ctb], Stefan Theussl [ctb]", "Maintainer": "Vladislav Kim ", "URL": "http://R-Forge.R-project.org/projects/rsymphony, https://projects.coin-or.org/SYMPHONY, http://www.coin-or.org/download/source/SYMPHONY/", "VignetteBuilder": "knitr", "source.ver": "src/contrib/lpsymphony_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/lpsymphony_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/lpsymphony_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/lpsymphony_1.2.0.tgz", "vignettes": [ "vignettes/lpsymphony/inst/doc/lpsymphony.pdf" ], "vignetteTitles": [ "Introduction to lpsymphony" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/lpsymphony/inst/doc/lpsymphony.R" ], "importsMe": [ "IHW" ] }, "lumi": { "Package": "lumi", "Version": "2.26.4", "Depends": [ "R (>= 2.10)", "Biobase (>= 2.5.5)" ], "Imports": [ "affy (>= 1.23.4)", "methylumi (>= 2.3.2)", "GenomicFeatures", "GenomicRanges", "annotate", "lattice", "mgcv (>= 1.4-0)", "nleqslv", "KernSmooth", "preprocessCore", "RSQLite", "DBI", "AnnotationDbi", "MASS", "graphics", "stats", "stats4", "methods" ], "Suggests": [ "beadarray", "limma", "vsn", "lumiBarnes", "lumiHumanAll.db", "lumiHumanIDMapping", "genefilter", "RColorBrewer" ], "License": "LGPL (>= 2)", "MD5sum": "1391b28459029139f5f45de6f6d1f419", "NeedsCompilation": "no", "Title": "BeadArray Specific Methods for Illumina Methylation and Expression Microarrays", "Description": "The lumi package provides an integrated solution for the Illumina microarray data analysis. It includes functions of Illumina BeadStudio (GenomeStudio) data input, quality control, BeadArray-specific variance stabilization, normalization and gene annotation at the probe level. It also includes the functions of processing Illumina methylation microarrays, especially Illumina Infinium methylation microarrays.", "biocViews": [ "DNAMethylation", "Microarray", "OneChannel", "Preprocessing", "QualityControl", "Software", "TwoChannel" ], "Author": "Pan Du, Richard Bourgon, Gang Feng, Simon Lin", "Maintainer": "Pan Du , Lei Huang , Gang Feng ", "source.ver": "src/contrib/lumi_2.26.4.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/lumi_2.26.4.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/lumi_2.26.4.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/lumi_2.26.4.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "dependsOnMe": [ "arrayMvout", "ffpeExampleData", "iCheck", "lumiBarnes", "lumiHumanIDMapping", "lumiMouseIDMapping", "lumiRatIDMapping", "MAQCsubset", "MAQCsubsetILM", "mvoutData", "wateRmelon" ], "importsMe": [ "anamiR", "ffpe", "methyAnalysis", "MineICA" ], "suggestsMe": [ "beadarray", "blima", "Harman", "methylumi", "tigre" ] }, "LVSmiRNA": { "Package": "LVSmiRNA", "Version": "1.24.0", "Depends": [ "R (>= 3.1.0)", "methods", "splines" ], "Imports": [ "BiocGenerics", "stats4", "graphics", "stats", "utils", "MASS", "Biobase", "quantreg", "limma", "affy", "SparseM", "vsn", "zlibbioc" ], "Enhances": [ "parallel", "snow", "Rmpi" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "cf6e7984e727838608ab3dbfa0672466", "NeedsCompilation": "yes", "Title": "LVS normalization for Agilent miRNA data", "Description": "Normalization of Agilent miRNA arrays.", "biocViews": [ "AgilentChip", "Microarray", "OneChannel", "Preprocessing", "Software" ], "Author": "Stefano Calza, Suo Chen, Yudi Pawitan", "Maintainer": "Stefano Calza ", "source.ver": "src/contrib/LVSmiRNA_1.24.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/LVSmiRNA_1.24.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/LVSmiRNA_1.24.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/LVSmiRNA_1.24.0.tgz", "vignettes": [ "vignettes/LVSmiRNA/inst/doc/LVSmiRNA.pdf" ], "vignetteTitles": [ "LVSmiRNA" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/LVSmiRNA/inst/doc/LVSmiRNA.R" ] }, "LymphoSeq": { "Package": "LymphoSeq", "Version": "1.2.0", "Depends": [ "R (>= 3.2)", "LymphoSeqDB" ], "Imports": [ "data.table", "plyr", "dplyr", "reshape", "VennDiagram", "ggplot2", "ineq", "RColorBrewer", "circlize", "grid", "utils", "stats" ], "Suggests": [ "knitr", "pheatmap", "wordcloud" ], "License": "Artistic-2.0", "MD5sum": "64209ccd5bb6e22432fef0b89dc6dd1b", "NeedsCompilation": "no", "Title": "Analyze high-throughput sequencing of T and B cell receptors", "Description": "This R package analyzes high-throughput sequencing of T and B cell receptor complementarity determining region 3 (CDR3) sequences generated by Adaptive Biotechnologies' ImmunoSEQ assay. Its input comes from tab-separated value (.tsv) files exported from the ImmunoSEQ analyzer.", "biocViews": [ "Sequencing", "Software", "TargetedResequencing", "Technology" ], "Author": "David Coffey ", "Maintainer": "David Coffey ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/LymphoSeq_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/LymphoSeq_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/LymphoSeq_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/LymphoSeq_1.2.0.tgz", "vignettes": [ "vignettes/LymphoSeq/inst/doc/LymphoSeq.pdf" ], "vignetteTitles": [ "Analyze high throughput sequencing of T and B cell receptors with LymphoSeq" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/LymphoSeq/inst/doc/LymphoSeq.R" ] }, "M3D": { "Package": "M3D", "Version": "1.8.2", "Depends": [ "R (>= 3.3.0)" ], "Imports": [ "parallel", "Rcpp", "BiocGenerics", "S4Vectors", "IRanges", "GenomicRanges", "SummarizedExperiment", "BiSeq" ], "LinkingTo": [ "Rcpp" ], "Suggests": [ "BiocStyle", "knitr", "testthat" ], "License": "Artistic License 2.0", "Archs": "x64", "MD5sum": "db50962edfce0906522cb98f0a7532b5", "NeedsCompilation": "yes", "Title": "Identifies differentially methylated regions across testing groups", "Description": "This package identifies statistically significantly differentially methylated regions of CpGs. It uses kernel methods (the Maximum Mean Discrepancy) to measure differences in methylation profiles, and relates these to inter-replicate changes, whilst accounting for variation in coverage profiles.", "biocViews": [ "Coverage", "CpGIsland", "DNAMethylation", "DifferentialMethylation", "Software" ], "Author": "Tom Mayo", "Maintainer": "Tom Mayo ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/M3D_1.8.2.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/M3D_1.8.2.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/M3D_1.8.2.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/M3D_1.8.2.tgz", "vignettes": [ "vignettes/M3D/inst/doc/M3D_vignette.pdf" ], "vignetteTitles": [ "An Introduction to the M$^3$D method" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/M3D/inst/doc/M3D_vignette.R" ] }, "M3Drop": { "Package": "M3Drop", "Version": "1.0.0", "Depends": [ "R (>= 3.3)", "numDeriv" ], "Imports": [ "RColorBrewer", "gplots", "bbmle", "statmod", "grDevices", "graphics", "stats" ], "Suggests": [ "ROCR", "knitr", "M3DExampleData" ], "License": "GPL (>=2)", "MD5sum": "1ed30b4e672c2f4136980569c3d45e9a", "NeedsCompilation": "no", "Title": "Michaelis-Menten Modelling of Dropouts in single-cell RNASeq", "Description": "This package fits a Michaelis-Menten model to the pattern of dropouts in single-cell RNASeq data. This model is used as a null to identify significantly variable (i.e. differentially expressed) genes for use in downstream analysis, such as clustering cells.", "biocViews": [ "DifferentialExpression", "DimensionReduction", "FeatureExtraction", "GeneExpression", "RNASeq", "Sequencing", "Software", "Transcriptomics" ], "Author": "Tallulah Andrews ", "Maintainer": "Tallulah Andrews ", "URL": "https://github.com/tallulandrews/M3Drop", "VignetteBuilder": "knitr", "BugReports": "https://github.com/tallulandrews/M3Drop/issues", "source.ver": "src/contrib/M3Drop_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/M3Drop_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/M3Drop_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/M3Drop_1.0.0.tgz", "vignettes": [ "vignettes/M3Drop/inst/doc/M3Drop_Vignette.pdf" ], "vignetteTitles": [ "Introduction to M3Drop" ], "hasREADME": true, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/M3Drop/inst/doc/M3Drop_Vignette.R" ] }, "maanova": { "Package": "maanova", "Version": "1.44.0", "Depends": [ "R (>= 2.10)" ], "Imports": [ "Biobase", "graphics", "grDevices", "methods", "stats", "utils" ], "Suggests": [ "qvalue", "snow" ], "Enhances": [ "Rmpi" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "58d4ead9cf7d0a5901e84a20334f6af1", "NeedsCompilation": "yes", "Title": "Tools for analyzing Micro Array experiments", "Description": "Analysis of N-dye Micro Array experiment using mixed model effect. Containing analysis of variance, permutation and bootstrap, cluster and consensus tree.", "biocViews": [ "Clustering", "DifferentialExpression", "Microarray", "Software" ], "Author": "Hao Wu, modified by Hyuna Yang and Keith Sheppard with ideas from Gary Churchill, Katie Kerr and Xiangqin Cui.", "Maintainer": "Keith Sheppard ", "URL": "http://research.jax.org/faculty/churchill", "source.ver": "src/contrib/maanova_1.44.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/maanova_1.44.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/maanova_1.44.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/maanova_1.44.0.tgz", "vignettes": [ "vignettes/maanova/inst/doc/maanova.pdf" ], "vignetteTitles": [ "R/maanova HowTo" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false }, "macat": { "Package": "macat", "Version": "1.48.0", "Depends": [ "Biobase", "annotate" ], "Suggests": [ "hgu95av2.db", "stjudem" ], "License": "Artistic-2.0", "MD5sum": "e1d4622fdd7d83cfd57e70e89c7a0710", "NeedsCompilation": "no", "Title": "MicroArray Chromosome Analysis Tool", "Description": "This library contains functions to investigate links between differential gene expression and the chromosomal localization of the genes. MACAT is motivated by the common observation of phenomena involving large chromosomal regions in tumor cells. MACAT is the implementation of a statistical approach for identifying significantly differentially expressed chromosome regions. The functions have been tested on a publicly available data set about acute lymphoblastic leukemia (Yeoh et al.Cancer Cell 2002), which is provided in the library 'stjudem'.", "biocViews": [ "DifferentialExpression", "Microarray", "Software", "Visualization" ], "Author": "Benjamin Georgi, Matthias Heinig, Stefan Roepcke, Sebastian Schmeier, Joern Toedling", "Maintainer": "Joern Toedling ", "source.ver": "src/contrib/macat_1.48.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/macat_1.48.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/macat_1.48.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/macat_1.48.0.tgz", "vignettes": [ "vignettes/macat/inst/doc/macat.pdf" ], "vignetteTitles": [ "MicroArray Chromosome Analysis Tool" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/macat/inst/doc/macat.R" ] }, "maCorrPlot": { "Package": "maCorrPlot", "Version": "1.44.0", "Depends": [ "lattice" ], "Imports": [ "graphics", "grDevices", "lattice", "stats" ], "License": "GPL (>= 2)", "MD5sum": "ce53804ebbda2c11525f09f9227f79da", "NeedsCompilation": "no", "Title": "Visualize artificial correlation in microarray data", "Description": "Graphically displays correlation in microarray data that is due to insufficient normalization", "biocViews": [ "Microarray", "Preprocessing", "Software", "Visualization" ], "Author": "Alexander Ploner ", "Maintainer": "Alexander Ploner ", "URL": "http://www.pubmedcentral.gov/articlerender.fcgi?tool=pubmed&pubmedid=15799785", "source.ver": "src/contrib/maCorrPlot_1.44.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/maCorrPlot_1.44.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/maCorrPlot_1.44.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/maCorrPlot_1.44.0.tgz", "vignettes": [ "vignettes/maCorrPlot/inst/doc/maCorrPlot.pdf" ], "vignetteTitles": [ "maCorrPlot Introduction" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/maCorrPlot/inst/doc/maCorrPlot.R" ] }, "made4": { "Package": "made4", "Version": "1.48.0", "Depends": [ "ade4", "RColorBrewer", "gplots", "scatterplot3d" ], "Suggests": [ "affy" ], "License": "Artistic-2.0", "MD5sum": "dacb004d45112dfc8e00843cfe3a9aef", "NeedsCompilation": "no", "Title": "Multivariate analysis of microarray data using ADE4", "Description": "Multivariate data analysis and graphical display of microarray data. Functions include between group analysis and coinertia analysis. It contains functions that require ADE4.", "biocViews": [ "Classification", "Clustering", "MultipleComparison", "Software" ], "Author": "Aedin Culhane", "Maintainer": "Aedin Culhane ", "URL": "http://www.hsph.harvard.edu/aedin-culhane/", "source.ver": "src/contrib/made4_1.48.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/made4_1.48.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/made4_1.48.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/made4_1.48.0.tgz", "vignettes": [ "vignettes/made4/inst/doc/introduction.pdf" ], "vignetteTitles": [ "introduction.pdf" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/made4/inst/doc/introduction.R" ], "dependsOnMe": [ "bgafun" ], "importsMe": [ "omicade4" ], "suggestsMe": [ "prot2D" ] }, "MADSEQ": { "Package": "MADSEQ", "Version": "1.0.0", "Depends": [ "R(>= 3.3)", "rjags(>= 4-6)" ], "Imports": [ "VGAM", "coda", "BSgenome", "BSgenome.Hsapiens.UCSC.hg19", "S4Vectors", "methods", "preprocessCore", "GenomicAlignments", "Rsamtools", "Biostrings", "GenomicRanges", "IRanges", "VariantAnnotation", "SummarizedExperiment", "GenomeInfoDb", "rtracklayer", "graphics", "stats", "grDevices", "utils", "zlibbioc" ], "Suggests": [ "knitr" ], "License": "GPL(>=2)", "MD5sum": "0cea24e6075190f31f8dffa411f34d92", "NeedsCompilation": "no", "Title": "Mosaic Aneuploidy Detection and Quantification using Massive Parallel Sequencing Data", "Description": "The MADSEQ package provides a group of hierarchical Bayeisan models for the detection of mosaic aneuploidy, the inference of the type of aneuploidy and also for the quantification of the fraction of aneuploid cells in the sample.", "biocViews": [ "Bayesian", "CopyNumberVariation", "Coverage", "GenomicVariation", "Sequencing", "Software", "SomaticMutation", "VariantDetection" ], "Author": "Yu Kong, Adam Auton, John Murray Greally", "Maintainer": "Yu Kong ", "URL": "https://github.com/ykong2/MADSEQ", "VignetteBuilder": "knitr", "BugReports": "https://github.com/ykong2/MADSEQ/issues", "source.ver": "src/contrib/MADSEQ_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MADSEQ_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MADSEQ_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MADSEQ_1.0.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MADSEQ/inst/doc/MADSEQ-vignette.R" ], "htmlDocs": [ "vignettes/MADSEQ/inst/doc/MADSEQ-vignette.html" ], "htmlTitles": [ "R Package MADSEQ" ] }, "maftools": { "Package": "maftools", "Version": "1.0.55", "Depends": [ "R (>= 3.3)" ], "Imports": [ "data.table", "ggplot2(>= 2.0)", "cowplot", "cometExactTest", "RColorBrewer", "NMF", "ggrepel", "methods", "ComplexHeatmap", "mclust", "VariantAnnotation", "Biostrings", "Rsamtools", "rjson", "grid", "DPpackage", "wordcloud", "grDevices", "changepoint" ], "Suggests": [ "knitr", "rmarkdown" ], "License": "MIT + file LICENSE", "MD5sum": "5043b6ba1c1b5aa16048b29c89f8226c", "NeedsCompilation": "no", "Title": "Summarize, Analyze and Visualize MAF files", "Description": "Analyze and visualize Mutation Annotation Format (MAF) files from large scale sequencing studies. This package provides various functions to perform most commonly used analyses in cancer genomics and to create feature rich customizable visualzations with minimal effort.", "biocViews": [ "Classification", "DNASeq", "DataRepresentation", "DriverMutation", "FeatureExtraction", "FunctionalGenomics", "Sequencing", "Software", "SomaticMutation", "VariantAnnotation", "Visualization" ], "Author": "Anand Mayakonda ", "Maintainer": "Anand Mayakonda ", "URL": "https://github.com/PoisonAlien/maftools", "VignetteBuilder": "knitr", "BugReports": "https://github.com/PoisonAlien/maftools/issues", "source.ver": "src/contrib/maftools_1.0.55.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/maftools_1.0.55.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/maftools_1.0.55.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/maftools_1.0.55.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/maftools/inst/doc/maftools.R" ], "htmlDocs": [ "vignettes/maftools/inst/doc/maftools.html" ], "htmlTitles": [ "Summarize, Analyze and Visualize MAF files" ] }, "maigesPack": { "Package": "maigesPack", "Version": "1.38.0", "Depends": [ "R (>= 2.10)", "convert", "graph", "limma", "marray", "methods" ], "Suggests": [ "amap", "annotate", "class", "e1071", "MASS", "multtest", "OLIN", "R2HTML", "rgl", "som" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "fdbd7734d3893aa5e8e2279e8b790b7e", "NeedsCompilation": "yes", "Title": "Functions to handle cDNA microarray data, including several methods of data analysis", "Description": "This package uses functions of various other packages together with other functions in a coordinated way to handle and analyse cDNA microarray data", "biocViews": [ "Classification", "Clustering", "DifferentialExpression", "GraphAndNetwork", "Microarray", "Preprocessing", "Software", "ThirdPartyClient", "TwoChannel" ], "Author": "Gustavo H. Esteves , with contributions from Roberto Hirata Jr , E. Jordao Neves , Elier B. Cristo , Ana C. Simoes and Lucas Fahham ", "Maintainer": "Gustavo H. Esteves ", "URL": "http://www.maiges.org/en/software/", "source.ver": "src/contrib/maigesPack_1.38.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/maigesPack_1.38.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/maigesPack_1.38.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/maigesPack_1.38.0.tgz", "vignettes": [ "vignettes/maigesPack/inst/doc/maigesPack_tutorial.pdf" ], "vignetteTitles": [ "maigesPack Tutorial" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/maigesPack/inst/doc/maigesPack_tutorial.R" ] }, "MAIT": { "Package": "MAIT", "Version": "1.8.0", "Depends": [ "R (>= 2.10)", "CAMERA", "Rcpp", "pls" ], "Imports": [ "gplots", "e1071", "class", "MASS", "plsgenomics", "agricolae", "xcms", "methods", "caret" ], "Enhances": [ "rgl" ], "License": "GPL-2", "MD5sum": "4f72328059315d70b85da4faeb34e0ad", "NeedsCompilation": "no", "Title": "Statistical Analysis of Metabolomic Data", "Description": "The MAIT package contains functions to perform end-to-end statistical analysis of LC/MS Metabolomic Data. Special emphasis is put on peak annotation and in modular function design of the functions.", "biocViews": [ "MassSpectrometry", "Metabolomics", "Software" ], "Author": "Francesc Fernandez-Albert, Rafael Llorach, Cristina Andres-LaCueva, Alexandre Perera", "Maintainer": "Francesc Fernandez-Albert ", "source.ver": "src/contrib/MAIT_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MAIT_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MAIT_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MAIT_1.8.0.tgz", "vignettes": [ "vignettes/MAIT/inst/doc/MAIT_Vignette.pdf" ], "vignetteTitles": [ "\\maketitleMAIT Vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MAIT/inst/doc/MAIT_Vignette.R" ] }, "makecdfenv": { "Package": "makecdfenv", "Version": "1.50.0", "Depends": [ "R (>= 2.6.0)", "affyio" ], "Imports": [ "Biobase", "affy", "methods", "stats", "utils", "zlibbioc" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "6d7e641274e9339c7ab7c76e01cd8e66", "NeedsCompilation": "yes", "Title": "CDF Environment Maker", "Description": "This package has two functions. One reads a Affymetrix chip description file (CDF) and creates a hash table environment containing the location/probe set membership mapping. The other creates a package that automatically loads that environment.", "biocViews": [ "DataImport", "OneChannel", "Preprocessing", "Software" ], "Author": "Rafael A. Irizarry , Laurent Gautier , Wolfgang Huber , Ben Bolstad ", "Maintainer": "James W. MacDonald ", "source.ver": "src/contrib/makecdfenv_1.50.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/makecdfenv_1.50.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/makecdfenv_1.50.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/makecdfenv_1.50.0.tgz", "vignettes": [ "vignettes/makecdfenv/inst/doc/makecdfenv.pdf" ], "vignetteTitles": [ "makecdfenv primer" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/makecdfenv/inst/doc/makecdfenv.R" ], "dependsOnMe": [ "altcdfenvs" ] }, "MANOR": { "Package": "MANOR", "Version": "1.46.0", "Depends": [ "R (>= 2.10)", "GLAD" ], "Imports": [ "GLAD", "graphics", "grDevices", "stats", "utils" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "9dacd59ace2ce31acba4c994403dbcea", "NeedsCompilation": "yes", "Title": "CGH Micro-Array NORmalization", "Description": "Importation, normalization, visualization, and quality control functions to correct identified sources of variability in array-CGH experiments.", "biocViews": [ "CopyNumberVariation", "DataImport", "Microarray", "Preprocessing", "QualityControl", "Software", "TwoChannel" ], "Author": "Pierre Neuvial , Philippe Hupe ", "Maintainer": "Pierre Neuvial ", "URL": "http://bioinfo.curie.fr/projects/manor/index.html", "source.ver": "src/contrib/MANOR_1.46.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MANOR_1.46.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MANOR_1.46.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MANOR_1.46.0.tgz", "vignettes": [ "vignettes/MANOR/inst/doc/MANOR.pdf" ], "vignetteTitles": [ "MANOR overview" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MANOR/inst/doc/MANOR.R" ] }, "manta": { "Package": "manta", "Version": "1.20.0", "Depends": [ "R (>= 1.8.0)", "methods", "edgeR (>= 2.5.13)" ], "Imports": [ "Hmisc", "caroline(>= 0.6.6)" ], "Suggests": [ "RSQLite", "plotrix" ], "License": "Artistic-2.0", "MD5sum": "46ede51b1ba70d9f5bbcb276cc9cd060", "NeedsCompilation": "no", "Title": "Microbial Assemblage Normalized Transcript Analysis", "Description": "Tools for robust comparative metatranscriptomics.", "biocViews": [ "DataImport", "DifferentialExpression", "GeneExpression", "Genetics", "QualityControl", "RNASeq", "Sequencing", "Software", "Visualization" ], "Author": "Ginger Armbrust, Adrian Marchetti", "Maintainer": "Chris Berthiaume , Adrian Marchetti ", "URL": "http://manta.ocean.washington.edu/", "source.ver": "src/contrib/manta_1.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/manta_1.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/manta_1.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/manta_1.20.0.tgz", "vignettes": [ "vignettes/manta/inst/doc/manta.pdf" ], "vignetteTitles": [ "manta" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/manta/inst/doc/manta.R" ] }, "MantelCorr": { "Package": "MantelCorr", "Version": "1.44.0", "Depends": [ "R (>= 2.10)" ], "Imports": [ "stats" ], "License": "GPL (>= 2)", "MD5sum": "4ae18141c59c213a3bd454f71b37e1c6", "NeedsCompilation": "no", "Title": "Compute Mantel Cluster Correlations", "Description": "Computes Mantel cluster correlations from a (p x n) numeric data matrix (e.g. microarray gene-expression data).", "biocViews": [ "Clustering", "Software" ], "Author": "Brian Steinmeyer and William Shannon", "Maintainer": "Brian Steinmeyer ", "source.ver": "src/contrib/MantelCorr_1.44.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MantelCorr_1.44.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MantelCorr_1.44.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MantelCorr_1.44.0.tgz", "vignettes": [ "vignettes/MantelCorr/inst/doc/MantelCorrVignette.pdf" ], "vignetteTitles": [ "MantelCorrVignette" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MantelCorr/inst/doc/MantelCorrVignette.R" ] }, "mAPKL": { "Package": "mAPKL", "Version": "1.6.0", "Depends": [ "R (>= 3.2.0)", "Biobase" ], "Imports": [ "multtest", "clusterSim", "apcluster", "limma", "e1071", "AnnotationDbi", "methods", "parmigene", "igraph", "reactome.db" ], "Suggests": [ "BiocStyle", "knitr", "mAPKLData", "hgu133plus2.db", "RUnit", "BiocGenerics" ], "License": "GPL (>= 2)", "MD5sum": "3d32c96346887c1a5e205ca676952f92", "NeedsCompilation": "no", "Title": "A Hybrid Feature Selection method for gene expression data", "Description": "We propose a hybrid FS method (mAP-KL), which combines multiple hypothesis testing and affinity propagation (AP)-clustering algorithm along with the Krzanowski & Lai cluster quality index, to select a small yet informative subset of genes.", "biocViews": [ "DifferentialExpression", "FeatureExtraction", "GeneExpression", "Microarray", "Software" ], "Author": "Argiris Sakellariou", "Maintainer": "Argiris Sakellariou ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/mAPKL_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/mAPKL_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/mAPKL_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/mAPKL_1.6.0.tgz", "vignettes": [ "vignettes/mAPKL/inst/doc/mAPKL.pdf" ], "vignetteTitles": [ "mAPKL Tutorial" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/mAPKL/inst/doc/mAPKL.R" ] }, "maPredictDSC": { "Package": "maPredictDSC", "Version": "1.12.0", "Depends": [ "R (>= 2.15.0)", "MASS", "affy", "limma", "gcrma", "ROC", "class", "e1071", "caret", "hgu133plus2.db", "ROCR", "AnnotationDbi", "LungCancerACvsSCCGEO" ], "Suggests": [ "parallel" ], "License": "GPL-2", "MD5sum": "c04d6c0e7a622aeeb84a86e209af0a37", "NeedsCompilation": "no", "Title": "Phenotype prediction using microarray data: approach of the best overall team in the IMPROVER Diagnostic Signature Challenge", "Description": "This package implements the classification pipeline of the best overall team (Team221) in the IMPROVER Diagnostic Signature Challenge. Additional functionality is added to compare 27 combinations of data preprocessing, feature selection and classifier types.", "biocViews": [ "Classification", "Microarray", "Software" ], "Author": "Adi Laurentiu Tarca ", "Maintainer": "Adi Laurentiu Tarca ", "URL": "http://bioinformaticsprb.med.wayne.edu/maPredictDSC", "source.ver": "src/contrib/maPredictDSC_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/maPredictDSC_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/maPredictDSC_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/maPredictDSC_1.12.0.tgz", "vignettes": [ "vignettes/maPredictDSC/inst/doc/maPredictDSC.pdf" ], "vignetteTitles": [ "maPredictDSC" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/maPredictDSC/inst/doc/maPredictDSC.R" ] }, "marray": { "Package": "marray", "Version": "1.52.0", "Depends": [ "R (>= 2.10.0)", "limma", "methods" ], "Suggests": [ "tkWidgets" ], "License": "LGPL", "MD5sum": "a95fc584433fff8804ca37aea6c750a1", "NeedsCompilation": "no", "Title": "Exploratory analysis for two-color spotted microarray data", "Description": "Class definitions for two-color spotted microarray data. Fuctions for data input, diagnostic plots, normalization and quality checking.", "biocViews": [ "Microarray", "Preprocessing", "Software", "TwoChannel" ], "Author": "Yee Hwa (Jean) Yang with contributions from Agnes Paquet and Sandrine Dudoit.", "Maintainer": "Yee Hwa (Jean) Yang ", "URL": "http://www.maths.usyd.edu.au/u/jeany/", "source.ver": "src/contrib/marray_1.52.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/marray_1.52.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/marray_1.52.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/marray_1.52.0.tgz", "vignettes": [ "vignettes/marray/inst/doc/marray.pdf", "vignettes/marray/inst/doc/marrayClasses.pdf", "vignettes/marray/inst/doc/marrayClassesShort.pdf", "vignettes/marray/inst/doc/marrayInput.pdf", "vignettes/marray/inst/doc/marrayNorm.pdf", "vignettes/marray/inst/doc/marrayPlots.pdf" ], "vignetteTitles": [ "marray Overview", "marrayClasses Overview", "marrayClasses Tutorial (short)", "marrayInput Introduction", "marray Normalization", "marrayPlots Overview" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/marray/inst/doc/marray.R", "vignettes/marray/inst/doc/marrayClasses.R", "vignettes/marray/inst/doc/marrayClassesShort.R", "vignettes/marray/inst/doc/marrayInput.R", "vignettes/marray/inst/doc/marrayNorm.R", "vignettes/marray/inst/doc/marrayPlots.R" ], "dependsOnMe": [ "beta7", "CGHbase", "convert", "dyebias", "dyebiasexamples", "FEM", "maigesPack", "MineICA", "nnNorm", "OLIN", "RBM", "stepNorm", "TurboNorm" ], "importsMe": [ "arrayQuality", "ChAMP", "methylPipe", "MSstats", "nnNorm", "OLIN", "OLINgui", "piano", "plrs", "sigaR", "stepNorm", "timecourse" ], "suggestsMe": [ "AgiMicroRna", "DEGraph", "Mfuzz" ] }, "maSigPro": { "Package": "maSigPro", "Version": "1.46.0", "Depends": [ "R (>= 2.3.1)", "stats", "Biobase", "MASS" ], "Imports": [ "Biobase", "graphics", "grDevices", "venn", "mclust", "stats", "utils", "MASS" ], "License": "GPL (>= 2)", "MD5sum": "4d71b5a900624cd2425471920c472fd9", "NeedsCompilation": "no", "Title": "Significant Gene Expression Profile Differences in Time Course Gene Expression Data", "Description": "maSigPro is a regression based approach to find genes for which there are significant gene expression profile differences between experimental groups in time course microarray and RNA-Seq experiments.", "biocViews": [ "Differential Expression", "Microarray", "RNA-Seq", "Software", "TimeCourse" ], "Author": "Ana Conesa , Maria Jose Nueda ", "Maintainer": "Maria Jose Nueda ", "URL": "http://bioinfo.cipf.es/", "source.ver": "src/contrib/maSigPro_1.46.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/maSigPro_1.46.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/maSigPro_1.46.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/maSigPro_1.46.0.tgz", "vignettes": [ "vignettes/maSigPro/inst/doc/maSigPro.pdf", "vignettes/maSigPro/inst/doc/maSigProUsersGuide.pdf" ], "vignetteTitles": [ "maSigPro Vignette", "maSigProUsersGuide.pdf" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "suggestsMe": [ "oneChannelGUI" ] }, "maskBAD": { "Package": "maskBAD", "Version": "1.18.0", "Depends": [ "R (>= 2.10)", "gcrma (>= 2.27.1)", "affy" ], "Suggests": [ "hgu95av2probe" ], "License": "GPL version 2 or newer", "MD5sum": "37aa44aa577f7eb19226f0896713faa2", "NeedsCompilation": "no", "Title": "Masking probes with binding affinity differences", "Description": "Package includes functions to analyze and mask microarray expression data.", "biocViews": [ "Microarray", "Software" ], "Author": "Michael Dannemann ", "Maintainer": "Michael Dannemann ", "source.ver": "src/contrib/maskBAD_1.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/maskBAD_1.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/maskBAD_1.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/maskBAD_1.18.0.tgz", "vignettes": [ "vignettes/maskBAD/inst/doc/maskBAD.pdf" ], "vignetteTitles": [ "Package maskBAD" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/maskBAD/inst/doc/maskBAD.R" ] }, "MassArray": { "Package": "MassArray", "Version": "1.26.0", "Depends": [ "R (>= 2.10.0)", "methods" ], "Imports": [ "graphics", "grDevices", "methods", "stats", "utils" ], "License": "GPL (>=2)", "MD5sum": "7832c4eb835cf0118d0a3015b1dc5cc9", "NeedsCompilation": "no", "Title": "Analytical Tools for MassArray Data", "Description": "This package is designed for the import, quality control, analysis, and visualization of methylation data generated using Sequenom's MassArray platform. The tools herein contain a highly detailed amplicon prediction for optimal assay design. Also included are quality control measures of data, such as primer dimer and bisulfite conversion efficiency estimation. Methylation data are calculated using the same algorithms contained in the EpiTyper software package. Additionally, automatic SNP-detection can be used to flag potentially confounded data from specific CG sites. Visualization includes barplots of methylation data as well as UCSC Genome Browser-compatible BED tracks. Multiple assays can be positionally combined for integrated analysis.", "biocViews": [ "DNAMethylation", "DataImport", "Genetics", "MassSpectrometry", "SNP", "Software", "Visualization" ], "Author": "Reid F. Thompson , John M. Greally ", "Maintainer": "Reid F. Thompson ", "source.ver": "src/contrib/MassArray_1.26.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MassArray_1.26.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MassArray_1.26.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MassArray_1.26.0.tgz", "vignettes": [ "vignettes/MassArray/inst/doc/MassArray.pdf" ], "vignetteTitles": [ "1. Primer" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MassArray/inst/doc/MassArray.R" ] }, "massiR": { "Package": "massiR", "Version": "1.10.0", "Depends": [ "cluster", "gplots", "diptest", "Biobase", "R (>= 3.0.2)" ], "Suggests": [ "biomaRt", "RUnit", "BiocGenerics" ], "License": "GPL-3", "MD5sum": "caafc1bef52666a5753666f2d5b1badc", "NeedsCompilation": "no", "Title": "massiR: MicroArray Sample Sex Identifier", "Description": "Predicts the sex of samples in gene expression microarray datasets", "biocViews": [ "Classification", "Clustering", "GeneExpression", "Microarray", "QualityControl", "Software" ], "Author": "Sam Buckberry", "Maintainer": "Sam Buckberry ", "source.ver": "src/contrib/massiR_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/massiR_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/massiR_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/massiR_1.10.0.tgz", "vignettes": [ "vignettes/massiR/inst/doc/massiR_Vignette.pdf" ], "vignetteTitles": [ "massiR_Example" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/massiR/inst/doc/massiR_Vignette.R" ] }, "MassSpecWavelet": { "Package": "MassSpecWavelet", "Version": "1.40.0", "Depends": [ "waveslim" ], "Suggests": [ "xcms", "caTools" ], "License": "LGPL (>= 2)", "Archs": "i386, x64", "MD5sum": "a3577977a3072ba9d366987e0c34925d", "NeedsCompilation": "yes", "Title": "Mass spectrum processing by wavelet-based algorithms", "Description": "Processing Mass Spectrometry spectrum by using wavelet based algorithm", "biocViews": [ "MassSpectrometry", "Proteomics", "Software" ], "Author": "Pan Du, Warren Kibbe, Simon Lin", "Maintainer": "Pan Du ", "source.ver": "src/contrib/MassSpecWavelet_1.40.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MassSpecWavelet_1.40.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MassSpecWavelet_1.40.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MassSpecWavelet_1.40.0.tgz", "vignettes": [ "vignettes/MassSpecWavelet/inst/doc/MassSpecWavelet.pdf" ], "vignetteTitles": [ "MassSpecWavelet" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MassSpecWavelet/inst/doc/MassSpecWavelet.R" ], "importsMe": [ "cosmiq", "xcms" ] }, "MAST": { "Package": "MAST", "Version": "1.0.5", "Depends": [ "SummarizedExperiment", "R(>= 3.3)" ], "Imports": [ "Biobase", "BiocGenerics", "S4Vectors", "data.table", "ggplot2", "plyr", "stringr", "abind", "methods", "parallel", "reshape2", "stats", "stats4", "graphics", "utils" ], "Suggests": [ "knitr", "rmarkdown", "testthat", "lme4(>= 1.0)", "roxygen2(> 4.0.0)", "numDeriv", "car", "gdata", "lattice", "GGally", "GSEABase", "NMF", "TxDb.Hsapiens.UCSC.hg19.knownGene", "rsvd", "limma", "RColorBrewer" ], "License": "GPL(>= 2)", "MD5sum": "9577efb1bcc66a386297a6322bfda9c6", "NeedsCompilation": "no", "Title": "Model-based Analysis of Single Cell Transcriptomics", "Description": "Methods and models for handling zero-inflated single cell assay data.", "biocViews": [ "DifferentialExpression", "GeneExpression", "GeneSetEnrichment", "RNASeq", "SingleCell", "Software", "Transcriptomics" ], "Author": "Andrew McDavid , Greg Finak , Masanao Yajima ", "Maintainer": "Andrew McDavid ", "URL": "https://github.com/RGLab/MAST/", "VignetteBuilder": "knitr", "BugReports": "https://github.com/RGLab/MAST/issues", "source.ver": "src/contrib/MAST_1.0.5.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MAST_1.0.5.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MAST_1.0.5.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MAST_1.0.5.tgz", "vignettes": [ "vignettes/MAST/inst/doc/MAST-intro.pdf" ], "vignetteTitles": [ "MAST-intro" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MAST/inst/doc/MAITAnalysis.R", "vignettes/MAST/inst/doc/MAST-intro.R" ], "htmlDocs": [ "vignettes/MAST/inst/doc/MAITAnalysis.html" ], "htmlTitles": [ "Using MAST for filtering, differential expression and gene set enrichment in MAIT cells" ] }, "matchBox": { "Package": "matchBox", "Version": "1.16.0", "Depends": [ "R (>= 2.8.0)" ], "License": "Artistic-2.0", "MD5sum": "5ac1ed2f8031c380e1915f41520273ef", "NeedsCompilation": "no", "Title": "Utilities to compute, compare, and plot the agreement between ordered vectors of features (ie. distinct genomic experiments). The package includes Correspondence-At-the-TOP (CAT) analysis.", "Description": "The matchBox package enables comparing ranked vectors of features, merging multiple datasets, removing redundant features, using CAT-plots and Venn diagrams, and computing statistical significance.", "biocViews": [ "Annotation", "Microarray", "MultipleComparison", "Software", "Visualization" ], "Author": "Luigi Marchionni , Anuj Gupta ", "Maintainer": "Luigi Marchionni , Anuj Gupta ", "source.ver": "src/contrib/matchBox_1.16.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/matchBox_1.16.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/matchBox_1.16.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/matchBox_1.16.0.tgz", "vignettes": [ "vignettes/matchBox/inst/doc/matchBox.pdf" ], "vignetteTitles": [ "Working with the matchBox package" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/matchBox/inst/doc/matchBox.R" ] }, "MatrixRider": { "Package": "MatrixRider", "Version": "1.6.0", "Depends": [ "R (>= 3.1.2)" ], "Imports": [ "methods", "TFBSTools", "IRanges", "XVector", "Biostrings" ], "LinkingTo": [ "IRanges", "XVector", "Biostrings", "S4Vectors" ], "Suggests": [ "RUnit", "BiocGenerics", "BiocStyle", "JASPAR2014" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "e8b692442ebefb1be71cc9fb7bbb1e9d", "NeedsCompilation": "yes", "Title": "Obtain total affinity and occupancies for binding site matrices on a given sequence", "Description": "Calculates a single number for a whole sequence that reflects the propensity of a DNA binding protein to interact with it. The DNA binding protein has to be described with a PFM matrix, for example gotten from Jaspar.", "biocViews": [ "GeneRegulation", "Genetics", "MotifAnnotation", "Software" ], "Author": "Elena Grassi", "Maintainer": "Elena Grassi ", "source.ver": "src/contrib/MatrixRider_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MatrixRider_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MatrixRider_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MatrixRider_1.6.0.tgz", "vignettes": [ "vignettes/MatrixRider/inst/doc/MatrixRider.pdf" ], "vignetteTitles": [ "Total affinity and occupancies" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MatrixRider/inst/doc/MatrixRider.R" ] }, "matter": { "Package": "matter", "Version": "1.0.1", "Depends": [ "methods", "stats", "biglm" ], "Imports": [ "BiocGenerics", "irlba", "S4Vectors", "utils" ], "Suggests": [ "BiocStyle", "Cardinal", "testthat" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "82e303d9c664192310dac06b5f96e3a4", "NeedsCompilation": "yes", "Title": "A framework for rapid prototyping with binary data on disk", "Description": "Memory-efficient reading, writing, and manipulation of structured binary data on disk as vectors, matrices, and arrays. This package is designed to be used as a back-end for Cardinal for working with high-resolution mass spectrometry imaging data.", "biocViews": [ "Infrastructure", "Software" ], "Author": "Kylie A. Bemis ", "Maintainer": "Kylie A. Bemis ", "URL": "http://www.cardinalmsi.org", "source.ver": "src/contrib/matter_1.0.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/matter_1.0.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/matter_1.0.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/matter_1.0.1.tgz", "vignettes": [ "vignettes/matter/inst/doc/matter.pdf" ], "vignetteTitles": [ "matter: Rapid prototyping with data on disk" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/matter/inst/doc/matter.R" ] }, "MBAmethyl": { "Package": "MBAmethyl", "Version": "1.8.0", "Depends": [ "R (>= 2.15)" ], "License": "Artistic-2.0", "MD5sum": "256ff6e0ec6bc03f761fffd49df1c168", "NeedsCompilation": "no", "Title": "Model-based analysis of DNA methylation data", "Description": "This package provides a function for reconstructing DNA methylation values from raw measurements. It iteratively implements the group fused lars to smooth related-by-location methylation values and the constrained least squares to remove probe affinity effect across multiple sequences.", "biocViews": [ "DNAMethylation", "MethylationArray", "Software" ], "Author": "Tao Wang, Mengjie Chen", "Maintainer": "Tao Wang ", "source.ver": "src/contrib/MBAmethyl_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MBAmethyl_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MBAmethyl_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MBAmethyl_1.8.0.tgz", "vignettes": [ "vignettes/MBAmethyl/inst/doc/MBAmethyl.pdf" ], "vignetteTitles": [ "MBAmethyl Vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MBAmethyl/inst/doc/MBAmethyl.R" ] }, "MBASED": { "Package": "MBASED", "Version": "1.8.0", "Depends": [ "RUnit", "BiocGenerics", "BiocParallel", "GenomicRanges", "SummarizedExperiment" ], "Suggests": [ "BiocStyle" ], "License": "Artistic-2.0", "MD5sum": "ec1845b980f5be3cbda918e302eec371", "NeedsCompilation": "no", "Title": "Package containing functions for ASE analysis using Meta-analysis Based Allele-Specific Expression Detection", "Description": "The package implements MBASED algorithm for detecting allele-specific gene expression from RNA count data, where allele counts at individual loci (SNVs) are integrated into a gene-specific measure of ASE, and utilizes simulations to appropriately assess the statistical significance of observed ASE.", "biocViews": [ "GeneExpression", "Sequencing", "Software", "Transcription" ], "Author": "Oleg Mayba, Houston Gilbert", "Maintainer": "Oleg Mayba ", "source.ver": "src/contrib/MBASED_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MBASED_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MBASED_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MBASED_1.8.0.tgz", "vignettes": [ "vignettes/MBASED/inst/doc/MBASED.pdf" ], "vignetteTitles": [ "MBASED" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MBASED/inst/doc/MBASED.R" ] }, "MBCB": { "Package": "MBCB", "Version": "1.28.0", "Depends": [ "R (>= 2.9.0)", "tcltk", "tcltk2" ], "Imports": [ "preprocessCore", "stats", "utils" ], "License": "GPL (>= 2)", "MD5sum": "c30fa3c12e3b17a480c46f3d1352a21b", "NeedsCompilation": "no", "Title": "MBCB (Model-based Background Correction for Beadarray)", "Description": "This package provides a model-based background correction method, which incorporates the negative control beads to pre-process Illumina BeadArray data.", "biocViews": [ "Microarray", "Preprocessing", "Software" ], "Author": "Yang Xie ", "Maintainer": "Jeff Allen ", "URL": "http://www.utsouthwestern.edu", "source.ver": "src/contrib/MBCB_1.28.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MBCB_1.28.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MBCB_1.28.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MBCB_1.28.0.tgz", "vignettes": [ "vignettes/MBCB/inst/doc/MBCB.pdf" ], "vignetteTitles": [ "MBCB" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MBCB/inst/doc/MBCB.R" ] }, "mBPCR": { "Package": "mBPCR", "Version": "1.28.0", "Depends": [ "oligoClasses", "SNPchip" ], "Imports": [ "Biobase" ], "Suggests": [ "xtable" ], "License": "GPL (>= 2)", "MD5sum": "bbadd79cc987fc2a66e7af7b9641c746", "NeedsCompilation": "no", "Title": "Bayesian Piecewise Constant Regression for DNA copy number estimation", "Description": "Estimates the DNA copy number profile using mBPCR to detect regions with copy number changes", "biocViews": [ "CopyNumberVariation", "Microarray", "SNP", "Software", "aCGH" ], "Author": "P.M.V. Rancoita , with contributions from M. Hutter ", "Maintainer": "P.M.V. Rancoita ", "URL": "http://www.idsia.ch/~paola/mBPCR", "source.ver": "src/contrib/mBPCR_1.28.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/mBPCR_1.28.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/mBPCR_1.28.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/mBPCR_1.28.0.tgz", "vignettes": [ "vignettes/mBPCR/inst/doc/mBPCR.pdf" ], "vignetteTitles": [ "mBPCR" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/mBPCR/inst/doc/mBPCR.R" ] }, "MBttest": { "Package": "MBttest", "Version": "1.2.0", "Depends": [ "R (>= 3.3.0)", "stats", "gplots", "gtools", "graphics", "base", "utils", "grDevices" ], "Suggests": [ "BiocStyle", "BiocGenerics" ], "License": "GPL-3", "MD5sum": "fe322dddfb74f2bf991f9d0971c5077a", "NeedsCompilation": "no", "Title": "Multiple Beta t-Tests", "Description": "MBttest method was developed from beta t-test method of Baggerly et al(2003). Compared to baySeq (Hard castle and Kelly 2010), DESeq (Anders and Huber 2010) and exact test (Robinson and Smyth 2007, 2008) and the GLM of McCarthy et al(2012), MBttest is of high work efficiency,that is, it has high power, high conservativeness of FDR estimation and high stability. MBttest is suit- able to transcriptomic data, tag data, SAGE data (count data) from small samples or a few replicate libraries. It can be used to identify genes, mRNA isoforms or tags differentially expressed between two conditions.", "biocViews": [ "AlternativeSplicing", "Coverage", "DifferentialExpression", "DifferentialSplicing", "GeneExpression", "MultipleComparison", "SAGE", "Sequencing", "Software", "Transcription" ], "Author": "Yuan-De Tan", "Maintainer": "Yuan-De Tan ", "source.ver": "src/contrib/MBttest_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MBttest_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MBttest_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MBttest_1.2.0.tgz", "vignettes": [ "vignettes/MBttest/inst/doc/MBttest.pdf" ], "vignetteTitles": [ "Analysing RNA-Seq count data with the \"MBttest\" package" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MBttest/inst/doc/MBttest.R" ] }, "mcaGUI": { "Package": "mcaGUI", "Version": "1.22.0", "Depends": [ "lattice", "MASS", "proto", "foreign", "gWidgets(>= 0.0-36)", "gWidgetsRGtk2(>= 0.0-53)", "OTUbase", "vegan", "bpca" ], "Enhances": [ "iplots", "reshape", "ggplot2", "cairoDevice", "OTUbase" ], "License": "GPL (>= 2)", "MD5sum": "28060ae4faf7c2635b46553a387b0a1a", "NeedsCompilation": "no", "Title": "Microbial Community Analysis GUI", "Description": "Microbial community analysis GUI for R using gWidgets.", "biocViews": [ "Clustering", "GUI", "Sequencing", "Software", "Visualization" ], "Author": "Wade K. Copeland, Vandhana Krishnan, Daniel Beck, Matt Settles, James Foster, Kyu-Chul Cho, Mitch Day, Roxana Hickey, Ursel M.E. Schutte, Xia Zhou, Chris Williams, Larry J. Forney, Zaid Abdo, Poor Man's GUI (PMG) base code by John Verzani with contributions by Yvonnick Noel", "Maintainer": "Wade K. Copeland ", "URL": "http://www.ibest.uidaho.edu/ibest/index.php", "source.ver": "src/contrib/mcaGUI_1.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/mcaGUI_1.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/mcaGUI_1.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/mcaGUI_1.22.0.tgz", "hasREADME": true, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false }, "MCRestimate": { "Package": "MCRestimate", "Version": "2.30.0", "Depends": [ "R (>= 2.7.2)", "golubEsets (>= 1.4.6)" ], "Imports": [ "e1071 (>= 1.5-12)", "pamr (>= 1.22)", "randomForest (>= 3.9-6)", "RColorBrewer (>= 0.1-3)", "Biobase (>= 2.5.5)", "graphics", "grDevices", "stats", "utils" ], "Suggests": [ "xtable (>= 1.2-1)", "ROC (>= 1.8.0)", "genefilter (>= 1.12.0)", "gpls (>= 1.6.0)" ], "License": "GPL (>= 2)", "MD5sum": "e8589b02fa040b5efe11f07de0cf1575", "NeedsCompilation": "no", "Title": "Misclassification error estimation with cross-validation", "Description": "This package includes a function for combining preprocessing and classification methods to calculate misclassification errors", "biocViews": [ "Classification", "Software" ], "Author": "Marc Johannes, Markus Ruschhaupt, Holger Froehlich, Ulrich Mansmann, Andreas Buness, Patrick Warnat, Wolfgang Huber, Axel Benner, Tim Beissbarth", "Maintainer": "Marc Johannes ", "source.ver": "src/contrib/MCRestimate_2.30.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MCRestimate_2.30.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MCRestimate_2.30.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MCRestimate_2.30.0.tgz", "vignettes": [ "vignettes/MCRestimate/inst/doc/UsingMCRestimate.pdf" ], "vignetteTitles": [ "HOW TO use MCRestimate" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MCRestimate/inst/doc/UsingMCRestimate.R" ] }, "mdgsa": { "Package": "mdgsa", "Version": "1.6.0", "Depends": [ "R (>= 2.14)" ], "Imports": [ "AnnotationDbi", "DBI", "GO.db", "KEGG.db", "cluster", "Matrix" ], "Suggests": [ "BiocStyle", "knitr", "rmarkdown", "limma", "ALL", "hgu95av2.db", "RUnit", "BiocGenerics" ], "License": "GPL", "MD5sum": "bd342bda7b062210ce1c6c47f1795716", "NeedsCompilation": "no", "Title": "Multi Dimensional Gene Set Analysis.", "Description": "Functions to preform a Gene Set Analysis in several genomic dimensions. Including methods for miRNAs.", "biocViews": [ "Annotation", "GO", "GeneSetEnrichment", "Pathways", "Software" ], "Author": "David Montaner ", "Maintainer": "David Montaner ", "URL": "https://github.com/dmontaner/mdgsa, http://www.dmontaner.com", "VignetteBuilder": "knitr", "source.ver": "src/contrib/mdgsa_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/mdgsa_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/mdgsa_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/mdgsa_1.6.0.tgz", "vignettes": [ "vignettes/mdgsa/inst/doc/mdgsa_vignette.pdf" ], "vignetteTitles": [ "mdgsa_vignette" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/mdgsa/inst/doc/mdgsa_vignette.R" ] }, "mdqc": { "Package": "mdqc", "Version": "1.36.0", "Depends": [ "R (>= 2.2.1)", "cluster", "MASS" ], "License": "LGPL (>= 2)", "MD5sum": "79700baf6d2a0a2ed138571b4b66d0d8", "NeedsCompilation": "no", "Title": "Mahalanobis Distance Quality Control for microarrays", "Description": "MDQC is a multivariate quality assessment method for microarrays based on quality control (QC) reports. The Mahalanobis distance of an array's quality attributes is used to measure the similarity of the quality of that array against the quality of the other arrays. Then, arrays with unusually high distances can be flagged as potentially low-quality.", "biocViews": [ "Microarray", "QualityControl", "Software" ], "Author": "Justin Harrington", "Maintainer": "Gabriela Cohen-Freue ", "source.ver": "src/contrib/mdqc_1.36.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/mdqc_1.36.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/mdqc_1.36.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/mdqc_1.36.0.tgz", "vignettes": [ "vignettes/mdqc/inst/doc/mdqcvignette.pdf" ], "vignetteTitles": [ "Introduction to MDQC" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/mdqc/inst/doc/mdqcvignette.R" ], "importsMe": [ "arrayMvout" ] }, "MEAL": { "Package": "MEAL", "Version": "1.4.2", "Depends": [ "R (>= 3.2.0)", "Biobase", "MultiDataSet" ], "Imports": [ "GenomicRanges", "SNPassoc", "limma", "DMRcate", "snpStats", "vegan", "BiocGenerics", "minfi", "IRanges", "S4Vectors", "methods", "doParallel", "parallel", "ggplot2 (>= 2.0.0)", "sva", "permute" ], "Suggests": [ "testthat", "IlluminaHumanMethylation450kanno.ilmn12.hg19", "knitr", "minfiData", "MEALData", "BiocStyle" ], "License": "Artistic-2.0", "MD5sum": "9d59fc1b70271822dfd344d0baa7c996", "NeedsCompilation": "no", "Title": "Perform methylation analysis", "Description": "Package to integrate methylation and expression data. It can also perform methylation or expression analysis alone. Several plotting functionalities are included as well as a new region analysis based on redundancy analysis. Effect of SNPs on a region can also be estimated.", "biocViews": [ "DNAMethylation", "Microarray", "Software", "WholeGenome" ], "Author": "Carlos Ruiz [aut, cre], Carles Hernandez-Ferrer [aut], Juan R. Gonzlez [aut]", "Maintainer": "Carlos Ruiz ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/MEAL_1.4.2.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MEAL_1.4.2.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MEAL_1.4.2.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MEAL_1.4.2.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MEAL/inst/doc/caseExample.R", "vignettes/MEAL/inst/doc/MEAL.R" ], "htmlDocs": [ "vignettes/MEAL/inst/doc/caseExample.html", "vignettes/MEAL/inst/doc/MEAL.html" ], "htmlTitles": [ "MEAL case example", "Introduction to MEAL" ] }, "MeasurementError.cor": { "Package": "MeasurementError.cor", "Version": "1.46.0", "License": "LGPL", "MD5sum": "a100d2075ad6b0058decc06ccd0b5087", "NeedsCompilation": "no", "Title": "Measurement Error model estimate for correlation coefficient", "Description": "Two-stage measurement error model for correlation estimation with smaller bias than the usual sample correlation", "biocViews": [ "Software", "StatisticalMethod" ], "Author": "Beiying Ding", "Maintainer": "Beiying Ding ", "source.ver": "src/contrib/MeasurementError.cor_1.46.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MeasurementError.cor_1.46.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MeasurementError.cor_1.46.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MeasurementError.cor_1.46.0.tgz", "vignettes": [ "vignettes/MeasurementError.cor/inst/doc/MeasurementError.cor.pdf" ], "vignetteTitles": [ "MeasurementError.cor Tutorial" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MeasurementError.cor/inst/doc/MeasurementError.cor.R" ] }, "MEDIPS": { "Package": "MEDIPS", "Version": "1.24.0", "Depends": [ "R (>= 3.0)", "BSgenome", "Rsamtools" ], "Imports": [ "GenomicRanges", "Biostrings", "graphics", "gtools", "IRanges", "methods", "stats", "utils", "edgeR", "DNAcopy", "biomaRt", "rtracklayer", "preprocessCore" ], "Suggests": [ "BSgenome.Hsapiens.UCSC.hg19", "MEDIPSData", "BiocStyle" ], "License": "GPL (>=2)", "MD5sum": "ca9c2c2e0e55e3b6287348640bf1625b", "NeedsCompilation": "no", "Title": "DNA IP-seq data analysis", "Description": "MEDIPS was developed for analyzing data derived from methylated DNA immunoprecipitation (MeDIP) experiments followed by sequencing (MeDIP-seq). However, MEDIPS provides functionalities for the analysis of any kind of quantitative sequencing data (e.g. ChIP-seq, MBD-seq, CMS-seq and others) including calculation of differential coverage between groups of samples and saturation and correlation analysis.", "biocViews": [ "ChIPSeq", "CopyNumberVariation", "Coverage", "CpGIsland", "DNAMethylation", "DifferentialExpression", "Genetics", "GenomeAnnotation", "Microarray", "Preprocessing", "QualityControl", "SequenceMatching", "Sequencing", "Software", "Visualization" ], "Author": "Lukas Chavez, Matthias Lienhard, Joern Dietrich, Isaac Lopez Moyado", "Maintainer": "Lukas Chavez ", "source.ver": "src/contrib/MEDIPS_1.24.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MEDIPS_1.24.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MEDIPS_1.24.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MEDIPS_1.24.0.tgz", "vignettes": [ "vignettes/MEDIPS/inst/doc/MEDIPS.pdf" ], "vignetteTitles": [ "MEDIPS" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MEDIPS/inst/doc/MEDIPS.R" ] }, "MEDME": { "Package": "MEDME", "Version": "1.34.0", "Depends": [ "R (>= 2.15)", "grDevices", "graphics", "methods", "stats", "utils" ], "Imports": [ "Biostrings", "MASS", "drc" ], "Suggests": [ "BSgenome.Hsapiens.UCSC.hg18", "BSgenome.Mmusculus.UCSC.mm9" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "f8721d11eab04b4ccd4b51615e7df925", "NeedsCompilation": "yes", "Title": "Modelling Experimental Data from MeDIP Enrichment", "Description": "Description: MEDME allows the prediction of absolute and relative methylation levels based on measures obtained by MeDIP-microarray experiments", "biocViews": [ "CpGIsland", "DNAMethylation", "Microarray", "Software" ], "Author": "Mattia Pelizzola and Annette Molinaro", "Maintainer": "Mattia Pelizzola ", "source.ver": "src/contrib/MEDME_1.34.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MEDME_1.34.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MEDME_1.34.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MEDME_1.34.0.tgz", "vignettes": [ "vignettes/MEDME/inst/doc/MEDME.pdf" ], "vignetteTitles": [ "MEDME.pdf" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MEDME/inst/doc/MEDME.R" ] }, "MEIGOR": { "Package": "MEIGOR", "Version": "1.8.0", "Depends": [ "Rsolnp", "snowfall", "CNORode", "deSolve" ], "Suggests": [ "CellNOptR" ], "License": "GPL-3", "MD5sum": "2c5759e18dc5df03c406897604648f9a", "NeedsCompilation": "no", "Title": "MEIGO - MEtaheuristics for bIoinformatics Global Optimization", "Description": "Global Optimization", "biocViews": [ "Software", "SystemsBiology" ], "Author": "Jose Egea, David Henriques, Alexandre Fdez. Villaverde, Thomas Cokelaer", "Maintainer": "Jose Egea ", "source.ver": "src/contrib/MEIGOR_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MEIGOR_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MEIGOR_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MEIGOR_1.8.0.tgz", "vignettes": [ "vignettes/MEIGOR/inst/doc/MEIGOR-vignette.pdf" ], "vignetteTitles": [ "Main vignette:Global Optimization for Bioinformatics and Systems Biology" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MEIGOR/inst/doc/MEIGOR-vignette.R" ] }, "MergeMaid": { "Package": "MergeMaid", "Version": "2.46.0", "Depends": [ "R (>= 2.10.0)", "survival", "Biobase", "MASS", "methods" ], "License": "GPL (>= 2)", "MD5sum": "18b5f319a8040247d9d1720163e0ee19", "NeedsCompilation": "no", "Title": "Merge Maid", "Description": "The functions in this R extension are intended for cross-study comparison of gene expression array data. Required from the user is gene expression matrices, their corresponding gene-id vectors and other useful information, and they could be 'list','matrix', or 'ExpressionSet'. The main function is 'mergeExprs' which transforms the input objects into data in the merged format, such that common genes in different datasets can be easily found. And the function 'intcor' calculate the correlation coefficients. Other functions use the output from 'modelOutcome' to graphically display the results and cross-validate associations of gene expression data with survival.", "biocViews": [ "DifferentialExpression", "Microarray", "Software", "Visualization" ], "Author": "Xiaogang Zhong Leslie Cope Elizabeth Garrett Giovanni Parmigiani ", "Maintainer": "Xiaogang Zhong ", "URL": "http://astor.som.jhmi.edu/MergeMaid", "source.ver": "src/contrib/MergeMaid_2.46.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MergeMaid_2.46.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MergeMaid_2.46.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MergeMaid_2.46.0.tgz", "vignettes": [ "vignettes/MergeMaid/inst/doc/MergeMaid.pdf" ], "vignetteTitles": [ "MergeMaid primer" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "importsMe": [ "metaArray", "XDE" ], "suggestsMe": [ "oneChannelGUI" ] }, "Mergeomics": { "Package": "Mergeomics", "Version": "1.2.0", "Depends": [ "R (>= 3.0.1)" ], "Suggests": [ "RUnit", "BiocGenerics" ], "License": "GPL (>= 2)", "MD5sum": "a1758eb0dca181503798175abfa63eaf", "NeedsCompilation": "no", "Title": "Integrative network analysis of omics data", "Description": "The Mergeomics pipeline serves as a flexible framework for integrating multidimensional omics-disease associations, functional genomics, canonical pathways and gene-gene interaction networks to generate mechanistic hypotheses. It includes two main parts, 1) Marker set enrichment analysis (MSEA); 2) Weighted Key Driver Analysis (wKDA).", "biocViews": [ "Software" ], "Author": "Ville-Petteri Makinen, Le Shu, Yuqi Zhao, Zeyneb Kurt, Bin Zhang, Xia Yang", "Maintainer": "Zeyneb Kurt ", "source.ver": "src/contrib/Mergeomics_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Mergeomics_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Mergeomics_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Mergeomics_1.2.0.tgz", "vignettes": [ "vignettes/Mergeomics/inst/doc/Mergeomics.pdf" ], "vignetteTitles": [ "Mergeomics" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Mergeomics/inst/doc/Mergeomics.R" ] }, "MeSHDbi": { "Package": "MeSHDbi", "Version": "1.10.0", "Depends": [ "R (>= 3.0.1)", "BiocGenerics (>= 0.15.10)" ], "Imports": [ "methods", "AnnotationDbi (>= 1.31.19)", "RSQLite", "Biobase" ], "Suggests": [ "RUnit" ], "License": "Artistic-2.0", "MD5sum": "c2134a253b11cce3a9c6c53a999d400d", "NeedsCompilation": "no", "Title": "DBI to construct MeSH-related package from sqlite file", "Description": "The package is unified implementation of MeSH.db, MeSH.AOR.db, and MeSH.PCR.db and also is interface to construct Gene-MeSH package (MeSH.XXX.eg.db). loadMeSHDbiPkg import sqlite file and generate MeSH.XXX.eg.db.", "biocViews": [ "Annotation", "AnnotationData", "Infrastructure", "Software" ], "Author": "Koki Tsuyuzaki", "Maintainer": "Koki Tsuyuzaki ", "source.ver": "src/contrib/MeSHDbi_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MeSHDbi_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MeSHDbi_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MeSHDbi_1.10.0.tgz", "vignettes": [ "vignettes/MeSHDbi/inst/doc/MeSHDbi.pdf" ], "vignetteTitles": [ "MeSH.db" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "dependsOnMe": [ "MeSH.Aca.eg.db", "MeSH.Aga.PEST.eg.db", "MeSH.Ame.eg.db", "MeSH.Aml.eg.db", "MeSH.Ana.eg.db", "MeSH.Ani.FGSC.eg.db", "MeSH.AOR.db", "MeSH.Ath.eg.db", "MeSH.Bfl.eg.db", "MeSH.Bsu.168.eg.db", "MeSH.Bsu.TUB10.eg.db", "MeSH.Bta.eg.db", "MeSH.Cal.SC5314.eg.db", "MeSH.Cbr.eg.db", "MeSH.Cel.eg.db", "MeSH.Cfa.eg.db", "MeSH.Cin.eg.db", "MeSH.Cja.eg.db", "MeSH.Cpo.eg.db", "MeSH.Cre.eg.db", "MeSH.Dan.eg.db", "MeSH.db", "MeSH.Dda.3937.eg.db", "MeSH.Ddi.AX4.eg.db", "MeSH.Der.eg.db", "MeSH.Dgr.eg.db", "MeSH.Dme.eg.db", "MeSH.Dmo.eg.db", "MeSH.Dpe.eg.db", "MeSH.Dre.eg.db", "MeSH.Dse.eg.db", "MeSH.Dsi.eg.db", "MeSH.Dvi.eg.db", "MeSH.Dya.eg.db", "MeSH.Eco.55989.eg.db", "MeSH.Eco.CFT073.eg.db", "MeSH.Eco.ED1a.eg.db", "MeSH.Eco.HS.eg.db", "MeSH.Eco.IAI1.eg.db", "MeSH.Eco.IAI39.eg.db", "MeSH.Eco.K12.DH10B.eg.db", "MeSH.Eco.K12.MG1655.eg.db", "MeSH.Eco.O127.H6.E2348.69.eg.db", "MeSH.Eco.O157.H7.EDL933.eg.db", "MeSH.Eco.O157.H7.Sakai.eg.db", "MeSH.Eco.S88.eg.db", "MeSH.Eco.UMN026.eg.db", "MeSH.Eqc.eg.db", "MeSH.Gga.eg.db", "MeSH.Gma.eg.db", "MeSH.Hsa.eg.db", "MeSH.Laf.eg.db", "MeSH.Lma.eg.db", "MeSH.Mdo.eg.db", "MeSH.Mes.eg.db", "MeSH.Mga.eg.db", "MeSH.Miy.eg.db", "MeSH.Mml.eg.db", "MeSH.Mmu.eg.db", "MeSH.Mtr.eg.db", "MeSH.Nle.eg.db", "MeSH.Oan.eg.db", "MeSH.Ocu.eg.db", "MeSH.Oni.eg.db", "MeSH.Osa.eg.db", "MeSH.Pab.eg.db", "MeSH.Pae.PAO1.eg.db", "MeSH.PCR.db", "MeSH.Pfa.3D7.eg.db", "MeSH.Pto.eg.db", "MeSH.Ptr.eg.db", "MeSH.Rno.eg.db", "MeSH.Sau.USA300TCH1516.eg.db", "MeSH.Sce.S288c.eg.db", "MeSH.Sco.A32.eg.db", "MeSH.Sil.eg.db", "MeSH.Spo.972h.eg.db", "MeSH.Spu.eg.db", "MeSH.Ssc.eg.db", "MeSH.Syn.eg.db", "MeSH.Tbr.9274.eg.db", "MeSH.Tgo.ME49.eg.db", "MeSH.Tgu.eg.db", "MeSH.Vvi.eg.db", "MeSH.Xla.eg.db", "MeSH.Xtr.eg.db", "MeSH.Zma.eg.db", "meshr" ] }, "meshes": { "Package": "meshes", "Version": "1.0.0", "Depends": [ "R (>= 3.3.1)", "DOSE (>= 2.11.7)" ], "Imports": [ "AnnotationDbi", "GOSemSim (>= 1.99.3)", "MeSH.db", "methods" ], "Suggests": [ "BiocStyle", "knitr", "MeSH.Cel.eg.db", "MeSH.Hsa.eg.db" ], "License": "Artistic-2.0", "MD5sum": "7130cf77aa64ac358021d15c8283588f", "NeedsCompilation": "no", "Title": "MeSH Enrichment and Semantic analyses", "Description": "MeSH (Medical Subject Headings) is the NLM controlled vocabulary used to manually index articles for MEDLINE/PubMed. MeSH terms were associated by Entrez Gene ID by three methods, gendoo, gene2pubmed and RBBH. This association is fundamental for enrichment and semantic analyses. meshes supports enrichment analysis (over-representation and gene set enrichment analysis) of gene list or whole expression profile. The semantic comparisons of MeSH terms provide quantitative ways to compute similarities between genes and gene groups. meshes implemented five methods proposed by Resnik, Schlicker, Jiang, Lin and Wang respectively and supports more than 70 species.", "biocViews": [ "Annotation", "Clustering", "MultipleComparison", "Software" ], "Author": "Guangchuang Yu [aut, cre]", "Maintainer": "Guangchuang Yu ", "URL": "https://guangchuangyu.github.io/meshes", "VignetteBuilder": "knitr", "BugReports": "https://github.com/GuangchuangYu/meshes/issues", "source.ver": "src/contrib/meshes_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/meshes_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/meshes_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/meshes_1.0.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/meshes/inst/doc/meshes.R" ], "htmlDocs": [ "vignettes/meshes/inst/doc/meshes.html" ], "htmlTitles": [ "An introduction to meshes" ] }, "meshr": { "Package": "meshr", "Version": "1.10.0", "Depends": [ "R (>= 3.0.1)", "fdrtool", "Category", "BiocGenerics", "methods", "cummeRbund", "org.Hs.eg.db", "MeSH.db", "MeSH.AOR.db", "MeSH.PCR.db", "MeSHDbi", "MeSH.Hsa.eg.db", "MeSH.Aca.eg.db", "MeSH.Bsu.168.eg.db", "MeSH.Syn.eg.db", "S4Vectors" ], "License": "Artistic-2.0", "MD5sum": "6267f13eb86451afde270ce285ab41e8", "NeedsCompilation": "no", "Title": "Tools for conducting enrichment analysis of MeSH", "Description": "A set of annotation maps describing the entire MeSH assembled using data from MeSH", "biocViews": [ "Annotation", "AnnotationData", "Bioinformatics", "FunctionalAnnotation", "MeSHDb", "MultipleComparisons", "Software", "Statistics" ], "Author": "Itoshi Nikaido, Koki Tsuyuzaki, Gota Morota", "Maintainer": "Koki Tsuyuzaki ", "source.ver": "src/contrib/meshr_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/meshr_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/meshr_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/meshr_1.10.0.tgz", "vignettes": [ "vignettes/meshr/inst/doc/MeSH.pdf" ], "vignetteTitles": [ "MeSH.db" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/meshr/inst/doc/MeSH.R" ] }, "MeSHSim": { "Package": "MeSHSim", "Version": "1.6.0", "Depends": [ "R(>= 3.0.0)" ], "Imports": [ "XML", "RCurl" ], "License": "GPL-2", "MD5sum": "ce2f8fec17d022815b35237223aa6d3f", "NeedsCompilation": "no", "Title": "MeSH(Medical Subject Headings) Semantic Similarity Measures", "Description": "Provide for measuring semantic similarity over MeSH headings and MEDLINE documents", "biocViews": [ "Clustering", "Software" ], "Author": "Jing Zhou, Yuxuan Shui", "Maintainer": "Jing ZHou <12210240050@fudan.edu.cn>", "source.ver": "src/contrib/MeSHSim_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MeSHSim_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MeSHSim_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MeSHSim_1.6.0.tgz", "vignettes": [ "vignettes/MeSHSim/inst/doc/MeSHSim.pdf" ], "vignetteTitles": [ "MeSHSim Quick Overview" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MeSHSim/inst/doc/MeSHSim.R" ] }, "messina": { "Package": "messina", "Version": "1.10.0", "Depends": [ "R (>= 3.1.0)", "survival (>= 2.37-4)", "methods" ], "Imports": [ "Rcpp (>= 0.11.1)", "plyr (>= 1.8)", "ggplot2 (>= 0.9.3.1)", "grid (>= 3.1.0)", "foreach (>= 1.4.1)", "graphics" ], "LinkingTo": [ "Rcpp" ], "Suggests": [ "knitr (>= 1.5)", "antiProfilesData (>= 0.99.2)", "Biobase (>= 2.22.0)", "BiocStyle" ], "Enhances": [ "doMC (>= 1.3.3)" ], "License": "EPL (>= 1.0)", "Archs": "i386, x64", "MD5sum": "e28d1d371758884c705464f05be7695a", "NeedsCompilation": "yes", "Title": "Single-gene classifiers and outlier-resistant detection of differential expression for two-group and survival problems.", "Description": "Messina is a collection of algorithms for constructing optimally robust single-gene classifiers, and for identifying differential expression in the presence of outliers or unknown sample subgroups. The methods have application in identifying lead features to develop into clinical tests (both diagnostic and prognostic), and in identifying differential expression when a fraction of samples show unusual patterns of expression.", "biocViews": [ "BiomedicalInformatics", "Classification", "DifferentialExpression", "GeneExpression", "Software", "Survival" ], "Author": "Mark Pinese [aut], Mark Pinese [cre], Mark Pinese [cph]", "Maintainer": "Mark Pinese ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/messina_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/messina_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/messina_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/messina_1.10.0.tgz", "vignettes": [ "vignettes/messina/inst/doc/messina.pdf" ], "vignetteTitles": [ "Using Messina" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/messina/inst/doc/messina.R" ] }, "metaArray": { "Package": "metaArray", "Version": "1.52.0", "Imports": [ "Biobase", "MergeMaid", "graphics", "stats" ], "License": "LGPL-2", "Archs": "i386, x64", "MD5sum": "0f48270c0707213f8f069fd74595704f", "NeedsCompilation": "yes", "Title": "Integration of Microarray Data for Meta-analysis", "Description": "1) Data transformation for meta-analysis of microarray Data: Transformation of gene expression data to signed probability scale (MCMC/EM methods) 2) Combined differential expression on raw scale: Weighted Z-score after stabilizing mean-variance relation within platform", "biocViews": [ "DifferentialExpression", "Microarray", "Software" ], "Author": "Debashis Ghosh Hyungwon Choi ", "Maintainer": "Hyungwon Choi ", "source.ver": "src/contrib/metaArray_1.52.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/metaArray_1.52.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/metaArray_1.52.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/metaArray_1.52.0.tgz", "vignettes": [ "vignettes/metaArray/inst/doc/metaArray.pdf" ], "vignetteTitles": [ "metaArray Vignette" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/metaArray/inst/doc/metaArray.R" ], "suggestsMe": [ "oneChannelGUI" ] }, "Metab": { "Package": "Metab", "Version": "1.8.0", "Depends": [ "xcms", "R (>= 3.0.1)", "svDialogs" ], "Imports": [ "pander" ], "Suggests": [ "RUnit", "BiocGenerics" ], "License": "GPL (>=2)", "MD5sum": "2050e8937931656f3984b4f35565c35b", "NeedsCompilation": "no", "Title": "Metab: An R Package for a High-Throughput Analysis of Metabolomics Data Generated by GC-MS.", "Description": "Metab is an R package for high-throughput processing of metabolomics data analysed by the Automated Mass Spectral Deconvolution and Identification System (AMDIS) (http://chemdata.nist.gov/mass-spc/amdis/downloads/). In addition, it performs statistical hypothesis test (t-test) and analysis of variance (ANOVA). Doing so, Metab considerably speed up the data mining process in metabolomics and produces better quality results. Metab was developed using interactive features, allowing users with lack of R knowledge to appreciate its functionalities.", "biocViews": [ "AMDIS", "GCMS", "MassSpectrometry", "Metabolomics", "Software" ], "Author": "Raphael Aggio ", "Maintainer": "Raphael Aggio ", "source.ver": "src/contrib/Metab_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Metab_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Metab_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Metab_1.8.0.tgz", "vignettes": [ "vignettes/Metab/inst/doc/MetabPackage.pdf" ], "vignetteTitles": [ "Applying Metab" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Metab/inst/doc/MetabPackage.R" ] }, "metabomxtr": { "Package": "metabomxtr", "Version": "1.8.0", "Depends": [ "methods", "Biobase" ], "Imports": [ "optimx", "Formula", "plyr", "multtest" ], "Suggests": [ "xtable", "ggplot2", "reshape2" ], "License": "GPL-2", "MD5sum": "5ee408a32409c948adc46a3b74730a9c", "NeedsCompilation": "no", "Title": "A package to run mixture models for truncated metabolomics data with normal or lognormal distributions", "Description": "The functions in this package return optimized parameter estimates and log likelihoods for mixture models of truncated data with normal or lognormal distributions.", "biocViews": [ "MassSpectrometry", "Metabolomics", "Software" ], "Author": "Michael Nodzenski, Anna Reisetter, Denise Scholtens", "Maintainer": "Michael Nodzenski ", "source.ver": "src/contrib/metabomxtr_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/metabomxtr_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/metabomxtr_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/metabomxtr_1.8.0.tgz", "vignettes": [ "vignettes/metabomxtr/inst/doc/Metabomxtr_Vignette.pdf", "vignettes/metabomxtr/inst/doc/mixnorm_Vignette.pdf" ], "vignetteTitles": [ "metabomxtr", "mixnorm" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/metabomxtr/inst/doc/Metabomxtr_Vignette.R", "vignettes/metabomxtr/inst/doc/mixnorm_Vignette.R" ] }, "MetaboSignal": { "Package": "MetaboSignal", "Version": "1.4.0", "Depends": [ "R(>= 3.3)" ], "Imports": [ "KEGGgraph", "mygene", "hpar", "org.Hs.eg.db", "igraph", "RCurl", "biomaRt", "KEGGREST", "AnnotationDbi", "stats", "graphics", "utils" ], "Suggests": [ "RUnit", "BiocGenerics", "knitr", "BiocStyle", "rmarkdown" ], "License": "GPL-3", "MD5sum": "66b06b7b1fd50aa1a2c7f5b0678ec10c", "NeedsCompilation": "no", "Title": "MetaboSignal: a network-based approach to overlay and explore metabolic and signaling KEGG pathways", "Description": "MetaboSignal is an R package that allows merging, analyzing and customizing metabolic and signaling KEGG pathways. It is a network-based approach designed to explore the topological relationship between genes (signaling- or enzymatic-genes) and metabolites, representing a powerful tool to investigate the genetic landscape and regulatory networks of metabolic phenotypes.", "biocViews": [ "GeneSignaling", "GeneTarget", "GraphAndNetwork", "KEGG", "Network", "Pathways", "Reactome", "Software" ], "Author": "Andrea Rodriguez-Martinez , Rafael Ayala , Joram M. Posma , Ana L. Neves , Marc-Emmanuel Dumas ", "Maintainer": "Andrea Rodriguez-Martinez , Rafael Ayala ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/MetaboSignal_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MetaboSignal_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MetaboSignal_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MetaboSignal_1.4.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MetaboSignal/inst/doc/MetaboSignal.R" ], "htmlDocs": [ "vignettes/MetaboSignal/inst/doc/MetaboSignal.html" ], "htmlTitles": [ "MetaboSignal" ] }, "metaCCA": { "Package": "metaCCA", "Version": "1.2.0", "Suggests": [ "knitr" ], "License": "MIT + file LICENSE", "MD5sum": "58022616c4ba146770e151a129d25368", "NeedsCompilation": "no", "Title": "Summary Statistics-Based Multivariate Meta-Analysis of Genome-Wide Association Studies Using Canonical Correlation Analysis", "Description": "metaCCA performs multivariate analysis of a single or multiple GWAS based on univariate regression coefficients. It allows multivariate representation of both phenotype and genotype. metaCCA extends the statistical technique of canonical correlation analysis to the setting where original individual-level records are not available, and employs a covariance shrinkage algorithm to achieve robustness.", "biocViews": [ "Genetics", "GenomeWideAssociation", "Regression", "SNP", "Software", "StatisticalMethod" ], "Author": "Anna Cichonska ", "Maintainer": "Anna Cichonska ", "URL": "http://biorxiv.org/content/early/2015/07/16/022665", "VignetteBuilder": "knitr", "source.ver": "src/contrib/metaCCA_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/metaCCA_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/metaCCA_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/metaCCA_1.2.0.tgz", "vignettes": [ "vignettes/metaCCA/inst/doc/metaCCA.pdf" ], "vignetteTitles": [ "metaCCA" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/metaCCA/inst/doc/metaCCA.R" ] }, "metagene": { "Package": "metagene", "Version": "2.6.1", "Depends": [ "R (>= 3.2.0)", "R6 (>= 2.0)", "GenomicRanges", "BiocParallel" ], "Imports": [ "rtracklayer", "gplots", "tools", "GenomicAlignments", "GenomeInfoDb", "GenomicFeatures", "IRanges", "ggplot2", "muStat", "Rsamtools", "DBChIP", "matrixStats" ], "Suggests": [ "RUnit", "BiocGenerics", "knitr", "BiocStyle", "rmarkdown", "similaRpeak" ], "License": "Artistic-2.0 | file LICENSE", "MD5sum": "550ff65e1a476ae5e8cb11ecd6a6b5ce", "NeedsCompilation": "no", "Title": "A package to produce metagene plots", "Description": "This package produces metagene plots to compare the behavior of DNA-interacting proteins at selected groups of genes/features. Bam files are used to increase the resolution. Multiple combination of group of bam files and/or group of genomic regions can be compared in a single analysis. Bootstraping analysis is used to compare the groups and locate regions with statistically different enrichment profiles.", "biocViews": [ "Alignment", "ChIPSeq", "Coverage", "Genetics", "MultipleComparison", "Sequencing", "Software" ], "Author": "Charles Joly Beauparlant , Fabien Claude Lamaze , Rawane Samb , Astrid Louise Deschenes and Arnaud Droit .", "Maintainer": "Charles Joly Beauparlant ", "VignetteBuilder": "knitr", "BugReports": "https://github.com/CharlesJB/metagene/issues", "source.ver": "src/contrib/metagene_2.6.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/metagene_2.6.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/metagene_2.6.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/metagene_2.6.1.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/metagene/inst/doc/metagene.R" ], "htmlDocs": [ "vignettes/metagene/inst/doc/metagene.html" ], "htmlTitles": [ "Introduction to metagene" ], "dependsOnMe": [ "Imetagene" ] }, "metagenomeFeatures": { "Package": "metagenomeFeatures", "Version": "1.4.0", "Depends": [ "R (>= 3.3)", "Biobase (>= 2.17.8)" ], "Imports": [ "Biostrings (>= 2.36.4)", "ShortRead (>= 1.26.0)", "dplyr (>= 0.4.3)", "stringr (>= 1.0.0)", "lazyeval (>= 0.1.10)", "RSQLite (>= 1.0.0)", "magrittr (>= 1.5)", "methods (>= 3.3.1)", "lattice (>= 0.20.33)", "metagenomeSeq (>= 1.14.2)", "ape (>= 3.5)", "purrr (>= 0.2.2)" ], "Suggests": [ "knitr (>= 1.11)", "msd16s (>= 0.102.0)", "testthat (>= 0.10.0)", "rmarkdown" ], "License": "Artistic-2.0", "MD5sum": "43066a04b263b0a481dbd02adca73a4d", "NeedsCompilation": "no", "Title": "Exploration of marker-gene sequence taxonomic annotations", "Description": "metagenomeFeatures was developed for use in exploring the taxonomic annotations for a marker-gene metagenomic sequence dataset. The package can be used to explore the taxonomic composition of a marker-gene database or annotated sequences from a marker-gene metagenome experiment.", "biocViews": [ "Annotation", "Infrastructure", "Metagenomics", "Microbiome", "Sequencing", "Software" ], "Author": "Nathan D. Olson, Joseph Nathaniel Paulson, Hector Corrada Bravo", "Maintainer": "Nathan D. Olson ", "URL": "https://github.com/HCBravoLab/metagenomeFeatures", "VignetteBuilder": "knitr", "BugReports": "https://github.com/HCBravoLab/metagenomeFeatures/issues", "source.ver": "src/contrib/metagenomeFeatures_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/metagenomeFeatures_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/metagenomeFeatures_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/metagenomeFeatures_1.4.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/metagenomeFeatures/inst/doc/Example_16S_Annotation_Workflow.R", "vignettes/metagenomeFeatures/inst/doc/Exploring_a_MgDb.R" ], "htmlDocs": [ "vignettes/metagenomeFeatures/inst/doc/Example_16S_Annotation_Workflow.html", "vignettes/metagenomeFeatures/inst/doc/Exploring_a_MgDb.html" ], "htmlTitles": [ "Example 16S Annotation Workflow", "Vignette Title" ], "importsMe": [ "greengenes13.5MgDb" ] }, "metagenomeSeq": { "Package": "metagenomeSeq", "Version": "1.16.0", "Depends": [ "R(>= 3.0)", "Biobase", "limma", "glmnet", "methods", "RColorBrewer" ], "Imports": [ "parallel", "matrixStats", "foreach", "Matrix", "gplots" ], "Suggests": [ "annotate", "BiocGenerics", "biomformat", "knitr", "gss", "testthat (>= 0.8)", "vegan", "interactiveDisplay" ], "License": "Artistic-2.0", "MD5sum": "72b34587afb800c1a50edd047389d565", "NeedsCompilation": "no", "Title": "Statistical analysis for sparse high-throughput sequencing", "Description": "metagenomeSeq is designed to determine features (be it Operational Taxanomic Unit (OTU), species, etc.) that are differentially abundant between two or more groups of multiple samples. metagenomeSeq is designed to address the effects of both normalization and under-sampling of microbial communities on disease association detection and the testing of feature correlations.", "biocViews": [ "Classification", "Clustering", "DifferentialExpression", "GeneticVariability", "Metagenomics", "Microbiome", "MultipleComparison", "Normalization", "Sequencing", "Software", "Visualization" ], "Author": "Joseph Nathaniel Paulson, Hisham Talukder, Mihai Pop, Hector Corrada Bravo", "Maintainer": "Joseph N. Paulson ", "URL": "https://github.com/nosson/metagenomeSeq/", "VignetteBuilder": "knitr", "BugReports": "https://github.com/nosson/metagenomeSeq/issues", "source.ver": "src/contrib/metagenomeSeq_1.16.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/metagenomeSeq_1.16.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/metagenomeSeq_1.16.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/metagenomeSeq_1.16.0.tgz", "vignettes": [ "vignettes/metagenomeSeq/inst/doc/fitTimeSeries.pdf", "vignettes/metagenomeSeq/inst/doc/metagenomeSeq.pdf" ], "vignetteTitles": [ "fitTimeSeries: differential abundance analysis through time or location", "metagenomeSeq: statistical analysis for sparse high-throughput sequencing" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/metagenomeSeq/inst/doc/fitTimeSeries.R", "vignettes/metagenomeSeq/inst/doc/metagenomeSeq.R" ], "importsMe": [ "metagenomeFeatures" ], "suggestsMe": [ "interactiveDisplay", "phyloseq" ], "dependsOnMe": [ "etec16s", "msd16s" ] }, "metahdep": { "Package": "metahdep", "Version": "1.32.0", "Depends": [ "R (>= 2.10)", "methods" ], "Suggests": [ "affyPLM" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "e5bb065bdf00e6864fc4a5cc489e86d6", "NeedsCompilation": "yes", "Title": "Hierarchical Dependence in Meta-Analysis", "Description": "Tools for meta-analysis in the presence of hierarchical (and/or sampling) dependence, including with gene expression studies", "biocViews": [ "DifferentialExpression", "Microarray", "Software" ], "Author": "John R. Stevens, Gabriel Nicholas", "Maintainer": "John R. Stevens ", "source.ver": "src/contrib/metahdep_1.32.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/metahdep_1.32.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/metahdep_1.32.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/metahdep_1.32.0.tgz", "vignettes": [ "vignettes/metahdep/inst/doc/metahdep.pdf" ], "vignetteTitles": [ "metahdep Primer" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/metahdep/inst/doc/metahdep.R" ] }, "metaMS": { "Package": "metaMS", "Version": "1.10.0", "Depends": [ "R (>= 2.10)", "methods", "CAMERA", "xcms (>= 1.35)" ], "Imports": [ "Matrix", "tools", "robustbase", "BiocGenerics" ], "Suggests": [ "metaMSdata", "RUnit" ], "License": "GPL (>= 2)", "MD5sum": "e17fd878c86fafb0269e9f1ade4a6ff8", "NeedsCompilation": "no", "Title": "MS-based metabolomics annotation pipeline", "Description": "MS-based metabolomics data processing and compound annotation pipeline.", "biocViews": [ "MassSpectrometry", "Metabolomics", "Software" ], "Author": "Ron Wehrens [aut, cre] (author of GC-MS part), Pietro Franceschi [aut] (author of LC-MS part), Nir Shahaf [ctb], Matthias Scholz [ctb], Georg Weingart [ctb] (development of GC-MS approach), Elisabete Carvalho [ctb] (testing and feedback of GC-MS pipeline)", "Maintainer": "Ron Wehrens ", "source.ver": "src/contrib/metaMS_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/metaMS_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/metaMS_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/metaMS_1.10.0.tgz", "vignettes": [ "vignettes/metaMS/inst/doc/runGC.pdf", "vignettes/metaMS/inst/doc/runLC.pdf" ], "vignetteTitles": [ "runGC", "runLC" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/metaMS/inst/doc/runGC.R", "vignettes/metaMS/inst/doc/runLC.R" ] }, "metaSeq": { "Package": "metaSeq", "Version": "1.14.0", "Depends": [ "R (>= 2.13.0)", "NOISeq", "snow", "Rcpp" ], "License": "Artistic-2.0", "MD5sum": "6b3ce46dd5d64e8a22126d8bc4f526e7", "NeedsCompilation": "no", "Title": "Meta-analysis of RNA-Seq count data in multiple studies", "Description": "The probabilities by one-sided NOISeq are combined by Fisher's method or Stouffer's method", "biocViews": [ "DifferentialExpression", "RNASeq", "Sequencing", "Software" ], "Author": "Koki Tsuyuzaki, Itoshi Nikaido", "Maintainer": "Koki Tsuyuzaki ", "source.ver": "src/contrib/metaSeq_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/metaSeq_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/metaSeq_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/metaSeq_1.14.0.tgz", "vignettes": [ "vignettes/metaSeq/inst/doc/metaSeq.pdf" ], "vignetteTitles": [ "metaSeq" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/metaSeq/inst/doc/metaSeq.R" ] }, "metaseqR": { "Package": "metaseqR", "Version": "1.14.0", "Depends": [ "R (>= 2.13.0)", "EDASeq", "DESeq", "limma", "qvalue" ], "Imports": [ "edgeR", "NOISeq", "baySeq", "NBPSeq", "biomaRt", "utils", "gplots", "corrplot", "vsn", "brew", "rjson", "log4r" ], "Suggests": [ "BiocGenerics", "GenomicRanges", "rtracklayer", "Rsamtools", "survcomp", "VennDiagram", "knitr", "zoo", "RUnit", "BiocInstaller", "BSgenome", "RSQLite" ], "Enhances": [ "parallel", "TCC", "RMySQL" ], "License": "GPL (>= 3)", "MD5sum": "81bb4a2a37ccd83e44d7a5882ca2f28a", "NeedsCompilation": "no", "Title": "An R package for the analysis and result reporting of RNA-Seq data by combining multiple statistical algorithms.", "Description": "Provides an interface to several normalization and statistical testing packages for RNA-Seq gene expression data. Additionally, it creates several diagnostic plots, performs meta-analysis by combinining the results of several statistical tests and reports the results in an interactive way.", "biocViews": [ "DifferentialExpression", "GeneExpression", "Normalization", "Preprocessing", "QualityControl", "RNASeq", "ReportWriting", "Software", "WorkflowStep" ], "Author": "Panagiotis Moulos ", "Maintainer": "Panagiotis Moulos ", "URL": "http://www.fleming.gr", "VignetteBuilder": "knitr", "source.ver": "src/contrib/metaseqR_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/metaseqR_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/metaseqR_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/metaseqR_1.14.0.tgz", "vignettes": [ "vignettes/metaseqR/inst/doc/metaseqr-pdf.pdf" ], "vignetteTitles": [ "RNA-Seq data analysis using mulitple statistical algorithms with metaseqR" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/metaseqR/inst/doc/metaseqr-pdf.R" ] }, "MetCirc": { "Package": "MetCirc", "Version": "1.0.1", "Depends": [ "R (>= 3.3)", "amap (>= 0.8)", "circlize (>= 0.3.5)", "graphics (>= 3.3)", "grDevices (>= 3.3)", "methods (>= 3.3)", "scales (>= 0.3.0)", "shiny (>= 0.13.1)", "stats (>= 3.3)" ], "Suggests": [ "BiocGenerics", "knitr (>= 1.11)" ], "License": "GPL-2", "MD5sum": "08536f8d1ab597c1976c37e556b4fc78", "NeedsCompilation": "no", "Title": "A workflow to analyse and visualise metabolomics data", "Description": "MetCirc comprises a workflow to interactively explore metabolomics data: create MSP, bin m/z values, calculate similarity between precursors and visualise similarities.", "biocViews": [ "MassSpectrometry", "Metabolomics", "Software", "Visualization" ], "Author": "Thomas Naake and Emmanuel Gaquerel ", "Maintainer": "Thomas Naake ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/MetCirc_1.0.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MetCirc_1.0.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MetCirc_1.0.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MetCirc_1.0.1.tgz", "vignettes": [ "vignettes/MetCirc/inst/doc/MetCirc.pdf" ], "vignetteTitles": [ "Workflow for Metabolomics" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MetCirc/inst/doc/MetCirc.R" ] }, "MethPed": { "Package": "MethPed", "Version": "1.2.0", "Depends": [ "R (>= 3.0.0)", "Biobase" ], "Imports": [ "randomForest", "grDevices", "graphics", "stats" ], "Suggests": [ "BiocStyle", "knitr", "markdown", "impute" ], "License": "GPL-2", "MD5sum": "7538f0853a474304acd0e81f75039c18", "NeedsCompilation": "no", "Title": "A DNA methylation classifier tool for the identification of pediatric brain tumor subtypes", "Description": "Classification of pediatric tumors into biologically defined subtypes is challenging and multifaceted approaches are needed. For this aim, we developed a diagnostic classifier based on DNA methylation profiles. We offer MethPed as an easy-to-use toolbox that allows researchers and clinical diagnosticians to test single samples as well as large cohorts for subclass prediction of pediatric brain tumors. The current version of MethPed can classify the following tumor diagnoses/subgroups: Diffuse Intrinsic Pontine Glioma (DIPG), Ependymoma, Embryonal tumors with multilayered rosettes (ETMR), Glioblastoma (GBM), Medulloblastoma (MB) - Group 3 (MB_Gr3), Group 4 (MB_Gr3), Group WNT (MB_WNT), Group SHH (MB_SHH) and Pilocytic Astrocytoma (PiloAstro).", "biocViews": [ "Classification", "DNAMethylation", "Epigenetics", "Software" ], "Author": "Mohammad Tanvir Ahamed [aut, trl], Anna Danielsson [aut], Szilárd Nemes [aut, trl], Helena Carén [aut, cre, cph]", "Maintainer": "Helena Carén ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/MethPed_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MethPed_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MethPed_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MethPed_1.2.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MethPed/inst/doc/MethPed-vignette.R" ], "htmlDocs": [ "vignettes/MethPed/inst/doc/MethPed-vignette.html" ], "htmlTitles": [ "MethPed User Guide" ] }, "MethTargetedNGS": { "Package": "MethTargetedNGS", "Version": "1.6.0", "Depends": [ "R (>= 3.1.2)", "stringr", "seqinr", "gplots", "Biostrings" ], "License": "Artistic-2.0", "MD5sum": "7057679944ea4f7c8c8e72c8cc2359bd", "NeedsCompilation": "no", "Title": "Perform Methylation Analysis on Next Generation Sequencing Data", "Description": "Perform step by step methylation analysis of Next Generation Sequencing data.", "biocViews": [ "Alignment", "DataImport", "Genetics", "ResearchField", "SequenceMatching", "Sequencing", "Software" ], "Author": "Muhammad Ahmer Jamil with Contribution of Prof. Holger Frohlich and Priv.-Doz. Dr. Osman El-Maarri", "Maintainer": "Muhammad Ahmer Jamil ", "SystemRequirements": "HMMER3", "source.ver": "src/contrib/MethTargetedNGS_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MethTargetedNGS_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MethTargetedNGS_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MethTargetedNGS_1.6.0.tgz", "vignettes": [ "vignettes/MethTargetedNGS/inst/doc/MethTargetedNGS.pdf" ], "vignetteTitles": [ "Introduction to MethTargetedNGS" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MethTargetedNGS/inst/doc/MethTargetedNGS.R" ] }, "methVisual": { "Package": "methVisual", "Version": "1.26.0", "Depends": [ "R (>= 2.11.0)", "Biostrings(>= 2.4.8)", "plotrix", "gsubfn", "grid", "sqldf" ], "Imports": [ "Biostrings", "ca", "graphics", "grDevices", "grid", "gridBase", "IRanges", "stats", "utils" ], "License": "GPL (>= 2)", "MD5sum": "001e1d1602567803b59894ee90b286ff", "NeedsCompilation": "no", "Title": "Methods for visualization and statistics on DNA methylation data", "Description": "The package 'methVisual' allows the visualization of DNA methylation data after bisulfite sequencing.", "biocViews": [ "Classification", "Clustering", "DNAMethylation", "Software" ], "Author": "A. Zackay, C. Steinhoff", "Maintainer": "Arie Zackay ", "source.ver": "src/contrib/methVisual_1.26.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/methVisual_1.26.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/methVisual_1.26.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/methVisual_1.26.0.tgz", "vignettes": [ "vignettes/methVisual/inst/doc/methVisual.pdf" ], "vignetteTitles": [ "Introduction to methVisual" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/methVisual/inst/doc/methVisual.R" ] }, "methyAnalysis": { "Package": "methyAnalysis", "Version": "1.16.1", "Depends": [ "R (>= 2.10)", "grid", "BiocGenerics", "IRanges", "GenomeInfoDb", "GenomicRanges", "Biobase (>= 2.34.0)", "org.Hs.eg.db" ], "Imports": [ "grDevices", "stats", "utils", "lumi", "methylumi", "Gviz", "genoset", "SummarizedExperiment", "IRanges", "GenomicRanges", "VariantAnnotation", "rtracklayer", "GenomicFeatures", "annotate", "Biobase (>= 2.5.5)", "AnnotationDbi", "genefilter", "biomaRt", "methods", "parallel" ], "Suggests": [ "FDb.InfiniumMethylation.hg19", "TxDb.Hsapiens.UCSC.hg19.knownGene" ], "License": "Artistic-2.0", "MD5sum": "aae7a006f6ae32169f62e72375a0468f", "NeedsCompilation": "no", "Title": "DNA methylation data analysis and visualization", "Description": "The methyAnalysis package aims for the DNA methylation data analysis and visualization. A MethyGenoSet class is defined to keep the chromosome location information together with the data. The package also includes functions of estimating the methylation levels from Methy-Seq data.", "biocViews": [ "DNAMethylation", "Microarray", "Software", "Visualization" ], "Author": "Pan Du, Richard Bourgon", "Maintainer": "Pan Du , Lei Huang , Gang Feng ", "source.ver": "src/contrib/methyAnalysis_1.16.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/methyAnalysis_1.16.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/methyAnalysis_1.16.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/methyAnalysis_1.16.1.tgz", "vignettes": [ "vignettes/methyAnalysis/inst/doc/methyAnalysis.pdf" ], "vignetteTitles": [ "An Introduction to the methyAnalysis package" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/methyAnalysis/inst/doc/methyAnalysis.R" ], "suggestsMe": [ "methylumi" ] }, "MethylAid": { "Package": "MethylAid", "Version": "1.8.0", "Depends": [ "R (>= 3.0)" ], "Imports": [ "Biobase", "BiocParallel", "BiocGenerics", "ggplot2", "grid", "gridBase", "grDevices", "graphics", "hexbin", "matrixStats", "minfi (>= 1.17.9)", "methods", "RColorBrewer", "shiny", "stats", "utils" ], "Suggests": [ "BiocStyle", "knitr", "MethylAidData", "minfiData", "RUnit" ], "License": "GPL (>= 2)", "MD5sum": "e9a512dc0bc856a09bb1b9524c4e81e7", "NeedsCompilation": "no", "Title": "Visual and interactive quality control of large Illumina DNA Methylation array data sets", "Description": "A visual and interactive web application using RStudio's shiny package. Bad quality samples are detected using sample-dependent and sample-independent controls present on the array and user adjustable thresholds. In depth exploration of bad quality samples can be performed using several interactive diagnostic plots of the quality control probes present on the array. Furthermore, the impact of any batch effect provided by the user can be explored.", "biocViews": [ "BatchEffect", "DNAMethylation", "GUI", "MethylationArray", "Microarray", "QualityControl", "Software", "TwoChannel", "Visualization" ], "Author": "Maarten van Iterson [aut, cre], Elmar Tobi[ctb], Roderick Slieker[ctb], Wouter den Hollander[ctb], Rene Luijk[ctb] and Bas Heijmans[ctb]", "Maintainer": "M. van Iterson ", "URL": "https://github.com/mvaniterson/methylaid", "VignetteBuilder": "knitr", "BugReports": "https://github.com/mvaniterson/methylaid/issues", "source.ver": "src/contrib/MethylAid_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MethylAid_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MethylAid_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MethylAid_1.8.0.tgz", "vignettes": [ "vignettes/MethylAid/inst/doc/MethylAid.pdf" ], "vignetteTitles": [ "MethylAid: Visual and Interactive quality control of Illumina Human DNA Methylation array data" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MethylAid/inst/doc/MethylAid.R" ], "dependsOnMe": [ "MethylAidData" ] }, "methylKit": { "Package": "methylKit", "Version": "1.0.0", "Depends": [ "R (>= 3.3.0)", "GenomicRanges (>= 1.18.1)", "methods" ], "Imports": [ "IRanges", "data.table (>= 1.9.6)", "parallel", "S4Vectors", "GenomeInfoDb", "KernSmooth", "qvalue", "emdbook", "Rsamtools", "gtools", "fastseg", "rtracklayer", "mclust", "Rcpp", "R.utils", "limma", "grDevices", "graphics", "stats", "utils" ], "LinkingTo": [ "Rcpp", "Rhtslib", "zlibbioc" ], "Suggests": [ "testthat", "knitr", "rmarkdown", "genomation" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "167ee8c3e92bf61827bcc749da042cb9", "NeedsCompilation": "yes", "Title": "DNA methylation analysis from high-throughput bisulfite sequencing results", "Description": "methylKit is an R package for DNA methylation analysis and annotation from high-throughput bisulfite sequencing. The package is designed to deal with sequencing data from RRBS and its variants, but also target-capture methods and whole genome bisulfite sequencing. It also has functions to analyze base-pair resolution 5hmC data from experimental protocols such as oxBS-Seq and TAB-Seq. Perl is needed to read SAM files only.", "biocViews": [ "DNAMethylation", "MethylSeq", "Sequencing", "Software" ], "Author": "Altuna Akalin [aut, cre], Matthias Kormaksson [aut], Sheng Li [aut], Arsene Wabo [ctb], Adrian Bierling [aut], Alexander Gosdschan [aut]", "Maintainer": "Altuna Akalin ", "URL": "http://code.google.com/p/methylkit/", "VignetteBuilder": "knitr", "source.ver": "src/contrib/methylKit_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/methylKit_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/methylKit_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/methylKit_1.0.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/methylKit/inst/doc/methylKit.R" ], "htmlDocs": [ "vignettes/methylKit/inst/doc/methylKit.html" ], "htmlTitles": [ "Vignette Title" ] }, "MethylMix": { "Package": "MethylMix", "Version": "2.0.0", "Depends": [ "R (>= 3.2.0)" ], "Imports": [ "foreach", "RPMM", "RColorBrewer", "ggplot2", "RCurl", "impute", "data.table", "limma", "R.matlab", "digest" ], "Suggests": [ "BiocStyle", "doParallel", "testthat", "knitr", "rmarkdown" ], "License": "GPL-2", "MD5sum": "79f91783cfb0d95a4d2198e80afc475f", "NeedsCompilation": "no", "Title": "MethylMix: Identifying methylation driven cancer genes", "Description": "MethylMix is an algorithm implemented to identify hyper and hypomethylated genes for a disease. MethylMix is based on a beta mixture model to identify methylation states and compares them with the normal DNA methylation state. MethylMix uses a novel statistic, the Differential Methylation value or DM-value defined as the difference of a methylation state with the normal methylation state. Finally, matched gene expression data is used to identify, besides differential, functional methylation states by focusing on methylation changes that effect gene expression. References: Gevaert 0. MethylMix: an R package for identifying DNA methylation-driven genes. Bioinformatics (Oxford, England). 2015;31(11):1839-41. doi:10.1093/bioinformatics/btv020. Gevaert O, Tibshirani R, Plevritis SK. Pancancer analysis of DNA methylation-driven genes using MethylMix. Genome Biology. 2015;16(1):17. doi:10.1186/s13059-014-0579-8.", "biocViews": [ "DNAMethylation", "DifferentialExpression", "DifferentialMethylation", "GeneExpression", "GeneRegulation", "MethylationArray", "Network", "Pathways", "Software", "StatisticalMethod" ], "Author": "Olivier Gevaert", "Maintainer": "Olivier Gevaert ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/MethylMix_2.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MethylMix_2.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MethylMix_2.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MethylMix_2.0.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MethylMix/inst/doc/vignettes.R" ], "htmlDocs": [ "vignettes/MethylMix/inst/doc/vignettes.html" ], "htmlTitles": [ "MethylMix" ] }, "methylMnM": { "Package": "methylMnM", "Version": "1.12.0", "Depends": [ "R (>= 2.12.1)", "edgeR", "statmod" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "786c164acc776d35a6c5df5483e767a6", "NeedsCompilation": "yes", "Title": "detect different methylation level (DMR)", "Description": "To give the exactly p-value and q-value of MeDIP-seq and MRE-seq data for different samples comparation.", "biocViews": [ "DNAMethylation", "Sequencing", "Software" ], "Author": "Yan Zhou, Bo Zhang, Nan Lin, BaoXue Zhang and Ting Wang", "Maintainer": "Yan Zhou", "source.ver": "src/contrib/methylMnM_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/methylMnM_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/methylMnM_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/methylMnM_1.12.0.tgz", "vignettes": [ "vignettes/methylMnM/inst/doc/methylMnM.pdf" ], "vignetteTitles": [ "methylMnM" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/methylMnM/inst/doc/methylMnM.R" ] }, "methylPipe": { "Package": "methylPipe", "Version": "1.8.0", "Depends": [ "R (>= 3.2.0)", "methods", "grDevices", "graphics", "stats", "utils", "GenomicRanges", "SummarizedExperiment (>= 0.2.0)", "Rsamtools" ], "Imports": [ "marray", "gplots", "IRanges", "BiocGenerics", "Gviz", "GenomicAlignments", "Biostrings", "parallel", "data.table", "GenomeInfoDb", "S4Vectors" ], "Suggests": [ "BSgenome.Hsapiens.UCSC.hg18", "TxDb.Hsapiens.UCSC.hg18.knownGene", "knitr", "MethylSeekR" ], "License": "GPL(>=2)", "Archs": "i386, x64", "MD5sum": "20d19f8aeb09cd4e2c369cc58cb180f0", "NeedsCompilation": "yes", "Title": "Base resolution DNA methylation data analysis", "Description": "Memory efficient analysis of base resolution DNA methylation data in both the CpG and non-CpG sequence context. Integration of DNA methylation data derived from any methodology providing base- or low-resolution data.", "biocViews": [ "Coverage", "DNAMethylation", "MethylSeq", "Sequencing", "Software" ], "Author": "Kamal Kishore", "Maintainer": "Kamal Kishore ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/methylPipe_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/methylPipe_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/methylPipe_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/methylPipe_1.8.0.tgz", "vignettes": [ "vignettes/methylPipe/inst/doc/methylPipe.pdf" ], "vignetteTitles": [ "methylPipe.pdf" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/methylPipe/inst/doc/methylPipe.R" ], "importsMe": [ "compEpiTools" ], "dependsOnMe": [ "ListerEtAlBSseq" ] }, "MethylSeekR": { "Package": "MethylSeekR", "Version": "1.14.0", "Depends": [ "rtracklayer (>= 1.16.3)", "parallel (>= 2.15.1)", "mhsmm (>= 0.4.4)" ], "Imports": [ "IRanges (>= 1.16.3)", "BSgenome (>= 1.26.1)", "GenomicRanges (>= 1.10.5)", "geneplotter (>= 1.34.0)", "graphics (>= 2.15.2)", "grDevices (>= 2.15.2)", "parallel (>= 2.15.2)", "stats (>= 2.15.2)", "utils (>= 2.15.2)" ], "Suggests": [ "BSgenome.Hsapiens.UCSC.hg18" ], "License": "GPL (>=2)", "MD5sum": "fb7b4d34bcc4a2983f2c3e8c0e84d559", "NeedsCompilation": "no", "Title": "Segmentation of Bis-seq data", "Description": "This is a package for the discovery of regulatory regions from Bis-seq data", "biocViews": [ "DNAMethylation", "MethylSeq", "Sequencing", "Software" ], "Author": "Lukas Burger, Dimos Gaidatzis, Dirk Schubeler and Michael Stadler", "Maintainer": "Lukas Burger ", "source.ver": "src/contrib/MethylSeekR_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MethylSeekR_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MethylSeekR_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MethylSeekR_1.14.0.tgz", "vignettes": [ "vignettes/MethylSeekR/inst/doc/MethylSeekR.pdf" ], "vignetteTitles": [ "MethylSeekR" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MethylSeekR/inst/doc/MethylSeekR.R" ], "suggestsMe": [ "methylPipe" ] }, "methylumi": { "Package": "methylumi", "Version": "2.20.0", "Depends": [ "Biobase", "methods", "R (>= 2.13)", "scales", "reshape2", "ggplot2", "matrixStats", "FDb.InfiniumMethylation.hg19 (>= 2.2.0)", "minfi" ], "Imports": [ "BiocGenerics", "S4Vectors", "IRanges", "GenomeInfoDb", "GenomicRanges", "SummarizedExperiment", "Biobase", "graphics", "lattice", "annotate", "genefilter", "AnnotationDbi", "minfi", "stats4", "illuminaio" ], "Suggests": [ "lumi", "lattice", "limma", "xtable", "SQN", "MASS", "matrixStats", "parallel", "rtracklayer", "Biostrings", "methyAnalysis", "TCGAMethylation450k", "IlluminaHumanMethylation450kanno.ilmn12.hg19", "FDb.InfiniumMethylation.hg18 (>= 2.2.0)", "Homo.sapiens", "knitr" ], "License": "GPL-2", "MD5sum": "90dc0b456677fd01b5f599931519c508", "NeedsCompilation": "no", "Title": "Handle Illumina methylation data", "Description": "This package provides classes for holding and manipulating Illumina methylation data. Based on eSet, it can contain MIAME information, sample information, feature information, and multiple matrices of data. An \"intelligent\" import function, methylumiR can read the Illumina text files and create a MethyLumiSet. methylumIDAT can directly read raw IDAT files from HumanMethylation27 and HumanMethylation450 microarrays. Normalization, background correction, and quality control features for GoldenGate, Infinium, and Infinium HD arrays are also included.", "biocViews": [ "CpGIsland", "DNAMethylation", "Preprocessing", "QualityControl", "Software", "TwoChannel" ], "Author": "Sean Davis, Pan Du, Sven Bilke, Tim Triche, Jr., Moiz Bootwalla", "Maintainer": "Sean Davis ", "VignetteBuilder": "knitr", "BugReports": "https://github.com/seandavi/methylumi/issues/new", "source.ver": "src/contrib/methylumi_2.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/methylumi_2.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/methylumi_2.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/methylumi_2.20.0.tgz", "vignettes": [ "vignettes/methylumi/inst/doc/methylumi.pdf", "vignettes/methylumi/inst/doc/methylumi450k.pdf" ], "vignetteTitles": [ "An Introduction to the methylumi package", "Working with Illumina 450k Arrays using methylumi" ], "hasREADME": true, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/methylumi/inst/doc/methylumi.R", "vignettes/methylumi/inst/doc/methylumi450k.R" ], "dependsOnMe": [ "bigmelon", "RnBeads", "skewr", "wateRmelon" ], "importsMe": [ "ffpe", "lumi", "methyAnalysis", "missMethyl" ], "suggestsMe": [ "IlluminaHumanMethylation450k.db", "MultiDataSet" ] }, "Mfuzz": { "Package": "Mfuzz", "Version": "2.34.0", "Depends": [ "R (>= 2.5.0)", "Biobase (>= 2.5.5)", "e1071" ], "Imports": [ "tcltk", "tkWidgets" ], "Suggests": [ "marray" ], "License": "GPL-2", "MD5sum": "5248ce12576ecb219c469f4e20c03815", "NeedsCompilation": "no", "Title": "Soft clustering of time series gene expression data", "Description": "Package for noise-robust soft clustering of gene expression time-series data (including a graphical user interface)", "biocViews": [ "Clustering", "Microarray", "Preprocessing", "Software", "TimeCourse", "Visualization" ], "Author": "Matthias Futschik ", "Maintainer": "Matthias Futschik ", "URL": "http://mfuzz.sysbiolab.eu/", "source.ver": "src/contrib/Mfuzz_2.34.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Mfuzz_2.34.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Mfuzz_2.34.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Mfuzz_2.34.0.tgz", "vignettes": [ "vignettes/Mfuzz/inst/doc/Mfuzz.pdf" ], "vignetteTitles": [ "Introduction to Mfuzz" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Mfuzz/inst/doc/Mfuzz.R" ], "dependsOnMe": [ "cycle" ], "suggestsMe": [ "pwOmics" ] }, "MGFM": { "Package": "MGFM", "Version": "1.8.0", "Depends": [ "AnnotationDbi", "annotate" ], "Suggests": [ "hgu133a.db" ], "License": "GPL-3", "MD5sum": "eecb581e053c5d93cf12fd871f6f24fe", "NeedsCompilation": "no", "Title": "Marker Gene Finder in Microarray gene expression data", "Description": "The package is designed to detect marker genes from Microarray gene expression data sets", "biocViews": [ "GeneExpression", "Genetics", "Microarray", "Software" ], "Author": "Khadija El Amrani", "Maintainer": "Khadija El Amrani ", "source.ver": "src/contrib/MGFM_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MGFM_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MGFM_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MGFM_1.8.0.tgz", "vignettes": [ "vignettes/MGFM/inst/doc/MGFM.pdf" ], "vignetteTitles": [ "Using MGFM" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MGFM/inst/doc/MGFM.R" ] }, "MGFR": { "Package": "MGFR", "Version": "1.0.0", "Depends": [ "R (>= 3.3)" ], "Imports": [ "biomaRt", "annotate" ], "License": "GPL-3", "MD5sum": "f625289c0f88941f31691fcc8002c39e", "NeedsCompilation": "no", "Title": "Marker Gene Finder in RNA-seq data", "Description": "The package is designed to detect marker genes from RNA-seq data.", "biocViews": [ "GeneExpression", "Genetics", "RNASeq", "Software" ], "Author": "Khadija El Amrani", "Maintainer": "Khadija El Amrani ", "source.ver": "src/contrib/MGFR_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MGFR_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MGFR_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MGFR_1.0.0.tgz", "vignettes": [ "vignettes/MGFR/inst/doc/MGFR.pdf" ], "vignetteTitles": [ "Using MGFR" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MGFR/inst/doc/MGFR.R" ] }, "mgsa": { "Package": "mgsa", "Version": "1.22.0", "Depends": [ "R (>= 2.14.0)", "methods", "gplots" ], "Imports": [ "graphics", "stats", "utils" ], "Suggests": [ "DBI", "RSQLite", "GO.db", "testthat" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "6ad4614087c4c1e8538c1907f38da120", "NeedsCompilation": "yes", "Title": "Model-based gene set analysis", "Description": "Model-based Gene Set Analysis (MGSA) is a Bayesian modeling approach for gene set enrichment. The package mgsa implements MGSA and tools to use MGSA together with the Gene Ontology.", "biocViews": [ "GO", "GeneSetEnrichment", "Pathways", "Software" ], "Author": "Sebastian Bauer , Julien Gagneur ", "Maintainer": "Sebastian Bauer ", "URL": "https://github.com/sba1/mgsa-bioc", "source.ver": "src/contrib/mgsa_1.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/mgsa_1.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/mgsa_1.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/mgsa_1.22.0.tgz", "vignettes": [ "vignettes/mgsa/inst/doc/mgsa.pdf" ], "vignetteTitles": [ "Overview of the mgsa package." ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/mgsa/inst/doc/mgsa.R" ], "suggestsMe": [ "gCMAP" ] }, "MiChip": { "Package": "MiChip", "Version": "1.28.0", "Depends": [ "R (>= 2.3.0)", "Biobase" ], "Imports": [ "Biobase" ], "License": "GPL (>= 2)", "MD5sum": "e9709ff4169ccbc396d062f2b369ca35", "NeedsCompilation": "no", "Title": "MiChip Parsing and Summarizing Functions", "Description": "This package takes the MiChip miRNA microarray .grp scanner output files and parses these out, providing summary and plotting functions to analyse MiChip hybridizations. A set of hybridizations is packaged into an ExpressionSet allowing it to be used by other BioConductor packages.", "biocViews": [ "Microarray", "Preprocessing", "Software" ], "Author": "Jonathon Blake ", "Maintainer": "Jonathon Blake ", "source.ver": "src/contrib/MiChip_1.28.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MiChip_1.28.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MiChip_1.28.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MiChip_1.28.0.tgz", "vignettes": [ "vignettes/MiChip/inst/doc/MiChip.pdf" ], "vignetteTitles": [ "MiChip miRNA Microarray Processing" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MiChip/inst/doc/MiChip.R" ] }, "microRNA": { "Package": "microRNA", "Version": "1.32.0", "Depends": [ "R (>= 2.10)" ], "Imports": [ "Biostrings (>= 2.11.32)" ], "Suggests": [ "Biostrings (>= 2.11.32)" ], "Enhances": [ "Rlibstree" ], "License": "Artistic-2.0", "MD5sum": "00f1d98d0c33b4312b1e095d9299c496", "NeedsCompilation": "no", "Title": "Data and functions for dealing with microRNAs", "Description": "Different data resources for microRNAs and some functions for manipulating them.", "biocViews": [ "GenomeAnnotation", "Infrastructure", "SequenceMatching", "Software" ], "Author": "R. Gentleman, S. Falcon", "Maintainer": "\"James F. Reid\" ", "source.ver": "src/contrib/microRNA_1.32.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/microRNA_1.32.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/microRNA_1.32.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/microRNA_1.32.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "dependsOnMe": [ "Roleswitch" ], "suggestsMe": [ "MmPalateMiRNA", "rtracklayer" ] }, "MIMOSA": { "Package": "MIMOSA", "Version": "1.12.0", "Depends": [ "R (>= 3.0.2)", "MASS", "plyr", "reshape", "Biobase", "ggplot2" ], "Imports": [ "methods", "Formula", "data.table", "pracma", "MCMCpack", "coda", "modeest", "testthat", "Rcpp", "scales", "Kmisc" ], "LinkingTo": [ "Rcpp", "RcppArmadillo" ], "Suggests": [ "parallel", "knitr" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "cf1cc1b0fba67e10696ae457ce99f747", "NeedsCompilation": "yes", "Title": "Mixture Models for Single-Cell Assays", "Description": "Modeling count data using Dirichlet-multinomial and beta-binomial mixtures with applications to single-cell assays.", "biocViews": [ "CellBasedAssays", "FlowCytometry", "Software" ], "Author": "Greg Finak ", "Maintainer": "Greg Finak ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/MIMOSA_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MIMOSA_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MIMOSA_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MIMOSA_1.12.0.tgz", "vignettes": [ "vignettes/MIMOSA/inst/doc/MIMOSA.pdf" ], "vignetteTitles": [ "MIMOSA: Mixture Models For Single Cell Assays" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MIMOSA/inst/doc/MIMOSA.R" ] }, "MineICA": { "Package": "MineICA", "Version": "1.14.0", "Depends": [ "R (>= 2.10)", "methods", "BiocGenerics (>= 0.13.8)", "Biobase", "plyr", "ggplot2", "scales", "foreach", "xtable", "biomaRt", "gtools", "GOstats", "cluster", "marray", "mclust", "RColorBrewer", "colorspace", "igraph", "Rgraphviz", "graph", "annotate", "Hmisc", "fastICA", "JADE" ], "Imports": [ "AnnotationDbi", "lumi", "fpc", "lumiHumanAll.db" ], "Suggests": [ "biomaRt", "GOstats", "cluster", "hgu133a.db", "mclust", "igraph", "breastCancerMAINZ", "breastCancerTRANSBIG", "breastCancerUPP", "breastCancerVDX" ], "Enhances": [ "doMC" ], "License": "GPL-2", "MD5sum": "f214c4fcf50ed39e8733e4d589dd5474", "NeedsCompilation": "no", "Title": "Analysis of an ICA decomposition obtained on genomics data", "Description": "The goal of MineICA is to perform Independent Component Analysis (ICA) on multiple transcriptome datasets, integrating additional data (e.g molecular, clinical and pathological). This Integrative ICA helps the biological interpretation of the components by studying their association with variables (e.g sample annotations) and gene sets, and enables the comparison of components from different datasets using correlation-based graph.", "biocViews": [ "MultipleComparison", "Software", "Visualization" ], "Author": "Anne Biton", "Maintainer": "Anne Biton ", "source.ver": "src/contrib/MineICA_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MineICA_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MineICA_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MineICA_1.14.0.tgz", "vignettes": [ "vignettes/MineICA/inst/doc/MineICA.pdf" ], "vignetteTitles": [ "MineICA: Independent component analysis of genomic data" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MineICA/inst/doc/MineICA.R" ] }, "minet": { "Package": "minet", "Version": "3.32.0", "Imports": [ "infotheo" ], "License": "file LICENSE", "Archs": "i386, x64", "MD5sum": "461b66fe520ca3ece85ec86c339c443e", "NeedsCompilation": "yes", "Title": "Mutual Information NETworks", "Description": "This package implements various algorithms for inferring mutual information networks from data.", "biocViews": [ "GraphAndNetwork", "Microarray", "Network", "NetworkInference", "Software" ], "Author": "Patrick E. Meyer, Frederic Lafitte, Gianluca Bontempi", "Maintainer": "Patrick E. Meyer ", "URL": "http://minet.meyerp.com", "source.ver": "src/contrib/minet_3.32.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/minet_3.32.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/minet_3.32.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/minet_3.32.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": true, "dependsOnMe": [ "BUS", "geNetClassifier", "netresponse" ], "importsMe": [ "netbenchmark", "RTN", "TCGAbiolinks" ], "suggestsMe": [ "CNORfeeder", "predictionet" ] }, "minfi": { "Package": "minfi", "Version": "1.20.2", "Depends": [ "methods", "BiocGenerics (>= 0.15.3)", "Biobase (>= 2.17.8)", "GenomicRanges", "SummarizedExperiment (>= 1.1.6)", "Biostrings", "bumphunter (>= 1.1.9)" ], "Imports": [ "S4Vectors", "GenomeInfoDb", "IRanges", "beanplot", "RColorBrewer", "lattice", "nor1mix", "siggenes", "limma", "preprocessCore", "illuminaio", "matrixStats (>= 0.50.0)", "mclust", "genefilter", "nlme", "reshape", "MASS", "quadprog", "data.table", "GEOquery", "stats", "grDevices", "graphics", "utils" ], "Suggests": [ "IlluminaHumanMethylation450kmanifest (>= 0.2.0)", "IlluminaHumanMethylation450kanno.ilmn12.hg19 (>= 0.2.1)", "minfiData (>= 0.18.0)", "minfiDataEPIC", "FlowSorted.Blood.450k (>= 1.0.1)", "RUnit", "digest", "BiocStyle", "knitr", "rmarkdown" ], "License": "Artistic-2.0", "MD5sum": "ec6fa2a876104c771314e2cf6310b003", "NeedsCompilation": "no", "Title": "Analyze Illumina Infinium DNA methylation arrays", "Description": "Tools to analyze & visualize Illumina Infinium methylation arrays.", "biocViews": [ "DNAMethylation", "DataImport", "DifferentialMethylation", "Epigenetics", "MethylationArray", "Microarray", "MultiChannel", "Normalization", "Preprocessing", "QualityControl", "Software", "TwoChannel" ], "Author": "Kasper Daniel Hansen [cre, aut], Martin Aryee [aut], Rafael A. Irizarry [aut], Andrew E. Jaffe [ctb], Jovana Maksimovic [ctb], E. Andres Houseman [ctb], Jean-Philippe Fortin [ctb], Tim Triche [ctb], Shan V. Andrews [ctb]", "Maintainer": "Kasper Daniel Hansen ", "URL": "https://github.com/kasperdanielhansen/minfi", "VignetteBuilder": "knitr", "BugReports": "https://github.com/kasperdanielhansen/minfi/issues", "source.ver": "src/contrib/minfi_1.20.2.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/minfi_1.20.2.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/minfi_1.20.2.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/minfi_1.20.2.tgz", "vignettes": [ "vignettes/minfi/inst/doc/minfi.pdf" ], "vignetteTitles": [ "minfi User's Guide" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/minfi/inst/doc/minfi.R" ], "dependsOnMe": [ "bigmelon", "ChAMP", "conumee", "CopyNumber450kData", "DMRcate", "ENmix", "FlowSorted.Blood.450k", "FlowSorted.CordBlood.450k", "FlowSorted.CordBloodNorway.450k", "FlowSorted.DLPFC.450k", "IlluminaHumanMethylation27kanno.ilmn12.hg19", "IlluminaHumanMethylation27kmanifest", "IlluminaHumanMethylation450kanno.ilmn12.hg19", "IlluminaHumanMethylation450kmanifest", "IlluminaHumanMethylationEPICanno.ilm10b2.hg19", "IlluminaHumanMethylationEPICmanifest", "methylumi", "minfiData", "minfiDataEPIC", "shinyMethyl" ], "importsMe": [ "ELMER", "MEAL", "MethylAid", "methylumi", "missMethyl", "MultiDataSet", "quantro", "skewr" ], "suggestsMe": [ "Harman", "RnBeads" ] }, "MinimumDistance": { "Package": "MinimumDistance", "Version": "1.18.0", "Depends": [ "R (>= 3.3)", "VanillaICE (>= 1.31.3)" ], "Imports": [ "methods", "BiocGenerics", "Biobase", "S4Vectors (>= 0.9.25)", "IRanges", "GenomeInfoDb", "GenomicRanges (>= 1.17.16)", "SummarizedExperiment (>= 0.2.0)", "oligoClasses", "DNAcopy", "ff", "foreach", "matrixStats", "lattice", "data.table", "grid", "stats", "utils" ], "Suggests": [ "human610quadv1bCrlmm (>= 1.0.3)", "BSgenome.Hsapiens.UCSC.hg18", "BSgenome.Hsapiens.UCSC.hg19", "SNPchip", "RUnit" ], "Enhances": [ "snow", "doSNOW" ], "License": "Artistic-2.0", "MD5sum": "88cbccae04baa8c08c19264100b21068", "NeedsCompilation": "no", "Title": "A Package for De Novo CNV Detection in Case-Parent Trios", "Description": "Analysis of de novo copy number variants in trios from high-dimensional genotyping platforms.", "biocViews": [ "CopyNumberVariation", "Microarray", "SNP", "Software" ], "Author": "Robert B Scharpf and Ingo Ruczinski", "Maintainer": "Robert B Scharpf ", "source.ver": "src/contrib/MinimumDistance_1.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MinimumDistance_1.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MinimumDistance_1.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MinimumDistance_1.18.0.tgz", "vignettes": [ "vignettes/MinimumDistance/inst/doc/MinimumDistance.pdf" ], "vignetteTitles": [ "Detection of de novo copy number alterations in case-parent trios" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MinimumDistance/inst/doc/MinimumDistance.R" ] }, "MiPP": { "Package": "MiPP", "Version": "1.46.0", "Depends": [ "R (>= 2.4)" ], "Imports": [ "Biobase", "e1071", "MASS", "stats" ], "License": "GPL (>= 2)", "MD5sum": "d7e6c1362d9d4723d3cb9136e4d17710", "NeedsCompilation": "no", "Title": "Misclassification Penalized Posterior Classification", "Description": "This package finds optimal sets of genes that seperate samples into two or more classes.", "biocViews": [ "Classification", "Microarray", "Software" ], "Author": "HyungJun Cho , Sukwoo Kim , Mat Soukup , and Jae K. Lee ", "Maintainer": "Sukwoo Kim ", "URL": "http://www.healthsystem.virginia.edu/internet/hes/biostat/bioinformatics/", "source.ver": "src/contrib/MiPP_1.46.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MiPP_1.46.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MiPP_1.46.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MiPP_1.46.0.tgz", "vignettes": [ "vignettes/MiPP/inst/doc/MiPP.pdf" ], "vignetteTitles": [ "MiPP Overview" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false }, "MiRaGE": { "Package": "MiRaGE", "Version": "1.16.0", "Depends": [ "R (>= 3.1.0)", "Biobase(>= 2.23.3)" ], "Imports": [ "BiocGenerics", "S4Vectors", "AnnotationDbi" ], "Suggests": [ "seqinr (>= 3.0.7)", "biomaRt (>= 2.19.1)", "GenomicFeatures (>= 1.15.4)", "Biostrings (>= 2.31.3)", "BSgenome.Hsapiens.UCSC.hg19", "BSgenome.Mmusculus.UCSC.mm10", "miRNATarget", "humanStemCell", "IRanges", "GenomicRanges (>= 1.8.3)", "BSgenome", "beadarrayExampleData" ], "License": "GPL", "MD5sum": "a63d73ca3d01270e829d4ee288c9afe1", "NeedsCompilation": "no", "Title": "MiRNA Ranking by Gene Expression", "Description": "The package contains functions for inferece of target gene regulation by miRNA, based on only target gene expression profile.", "biocViews": [ "GeneExpression", "Microarray", "RNASeq", "SAGE", "Sequencing", "Software" ], "Author": "Y-h. Taguchi ", "Maintainer": "Y-h. Taguchi ", "source.ver": "src/contrib/MiRaGE_1.16.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MiRaGE_1.16.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MiRaGE_1.16.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MiRaGE_1.16.0.tgz", "vignettes": [ "vignettes/MiRaGE/inst/doc/MiRaGE.pdf" ], "vignetteTitles": [ "How to use MiRaGE Package" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MiRaGE/inst/doc/MiRaGE.R" ] }, "miRcomp": { "Package": "miRcomp", "Version": "1.4.0", "Depends": [ "R (>= 3.2)", "Biobase (>= 2.22.0)", "miRcompData" ], "Imports": [ "utils", "methods", "graphics", "KernSmooth", "stats" ], "Suggests": [ "BiocStyle", "knitr", "rmarkdown", "RUnit", "BiocGenerics", "shiny" ], "License": "GPL-3 | file LICENSE", "MD5sum": "68cd4dfdd9b90a0086b3ed979c4e8556", "NeedsCompilation": "no", "Title": "Tools to assess and compare miRNA expression estimatation methods", "Description": "Based on a large miRNA dilution study, this package provides tools to read in the raw amplification data and use these data to assess the performance of methods that estimate expression from the amplification curves.", "biocViews": [ "Preprocessing", "QualityControl", "Software", "qPCR" ], "Author": "Matthew N. McCall , Lauren Kemperman ", "Maintainer": "Matthew N. McCall ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/miRcomp_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/miRcomp_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/miRcomp_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/miRcomp_1.4.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/miRcomp/inst/doc/miRcomp.R" ], "htmlDocs": [ "vignettes/miRcomp/inst/doc/miRcomp.html" ], "htmlTitles": [ "Assessment and comparison of miRNA expression estimation methods (miRcomp)" ] }, "mirIntegrator": { "Package": "mirIntegrator", "Version": "1.4.0", "Depends": [ "R (>= 3.3)" ], "Imports": [ "graph", "ROntoTools", "ggplot2", "org.Hs.eg.db", "AnnotationDbi", "Rgraphviz" ], "Suggests": [ "RUnit", "BiocGenerics" ], "License": "GPL (>=3)", "MD5sum": "d1936acbdbc31a183516bdb2f61e7a72", "NeedsCompilation": "no", "Title": "Integrating microRNA expression into signaling pathways for pathway analysis", "Description": "Tools for augmenting signaling pathways to perform pathway analysis of microRNA and mRNA expression levels.", "biocViews": [ "GraphAndNetwork", "KEGG", "Microarray", "Network", "Pathways", "Software" ], "Author": "Diana Diaz ", "Maintainer": "Diana Diaz ", "URL": "http://datad.github.io/mirIntegrator/", "source.ver": "src/contrib/mirIntegrator_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/mirIntegrator_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/mirIntegrator_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/mirIntegrator_1.4.0.tgz", "vignettes": [ "vignettes/mirIntegrator/inst/doc/mirIntegrator.pdf" ], "vignetteTitles": [ "mirIntegrator Overview" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/mirIntegrator/inst/doc/mirIntegrator.R" ] }, "miRLAB": { "Package": "miRLAB", "Version": "1.4.0", "Imports": [ "RCurl", "httr", "stringr", "Hmisc", "energy", "entropy", "Roleswitch", "gplots", "glmnet", "impute", "limma", "pcalg" ], "Suggests": [ "knitr", "RUnit", "BiocGenerics", "AnnotationDbi", "org.Hs.eg.db", "GOstats", "Category" ], "License": "GPL (>=2)", "MD5sum": "c21dee35648355aae97a84540cbc4326", "NeedsCompilation": "no", "Title": "Dry lab for exploring miRNA-mRNA relationships", "Description": "Provide tools exploring miRNA-mRNA relationships, including popular miRNA target prediction methods, ensemble methods that integrate individual methods, functions to get data from online resources, functions to validate the results, and functions to conduct enrichment analyses.", "biocViews": [ "GeneExpression", "Network", "NetworkInference", "Software", "miRNA" ], "Author": "Thuc Duy Le, Junpeng Zhang", "Maintainer": "Thuc Duy Le ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/miRLAB_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/miRLAB_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/miRLAB_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/miRLAB_1.4.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/miRLAB/inst/doc/miRLAB-vignette.R" ], "htmlDocs": [ "vignettes/miRLAB/inst/doc/miRLAB-vignette.html" ], "htmlTitles": [ "miRLAB" ] }, "miRNAmeConverter": { "Package": "miRNAmeConverter", "Version": "1.2.0", "Depends": [ "miRBaseVersions.db" ], "Imports": [ "DBI", "AnnotationDbi" ], "Suggests": [ "methods", "testthat", "knitr", "rmarkdown" ], "License": "Artistic-2.0", "MD5sum": "5755c243694e958e82a6beacdbefd38f", "NeedsCompilation": "no", "Title": "Convert miRNA Names to Different miRBase Versions", "Description": "Package containing an S4 class for translating mature miRNA names to different miRBase versions, sequence retrieval, checking names for validity and detecting miRBase version of a given set of names (data from http://www.mirbase.org/).", "biocViews": [ "Preprocessing", "Software", "miRNA" ], "Author": "Stefan Haunsberger [aut, cre]", "Maintainer": "Stefan J. Haunsberger ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/miRNAmeConverter_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/miRNAmeConverter_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/miRNAmeConverter_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/miRNAmeConverter_1.2.0.tgz", "vignettes": [ "vignettes/miRNAmeConverter/inst/doc/miRNAmeConverter-vignette.pdf" ], "vignetteTitles": [ "miRNAmeConverter-vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/miRNAmeConverter/inst/doc/miRNAmeConverter-vignette.R" ] }, "miRNApath": { "Package": "miRNApath", "Version": "1.34.0", "Depends": [ "methods", "R(>= 2.7.0)" ], "License": "LGPL-2.1", "MD5sum": "0f7f9b21088520d78fda7cc79d3c06d1", "NeedsCompilation": "no", "Title": "miRNApath: Pathway Enrichment for miRNA Expression Data", "Description": "This package provides pathway enrichment techniques for miRNA expression data. Specifically, the set of methods handles the many-to-many relationship between miRNAs and the multiple genes they are predicted to target (and thus affect.) It also handles the gene-to-pathway relationships separately. Both steps are designed to preserve the additive effects of miRNAs on genes, many miRNAs affecting one gene, one miRNA affecting multiple genes, or many miRNAs affecting many genes.", "biocViews": [ "Annotation", "DifferentialExpression", "NetworkEnrichment", "Pathways", "Software", "miRNA" ], "Author": "James M. Ward with contributions from Yunling Shi, Cindy Richards, John P. Cogswell", "Maintainer": "James M. Ward ", "source.ver": "src/contrib/miRNApath_1.34.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/miRNApath_1.34.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/miRNApath_1.34.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/miRNApath_1.34.0.tgz", "vignettes": [ "vignettes/miRNApath/inst/doc/miRNApath.pdf" ], "vignetteTitles": [ "miRNApath: Pathway Enrichment for miRNA Expression Data" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/miRNApath/inst/doc/miRNApath.R" ], "suggestsMe": [ "oneChannelGUI" ] }, "miRNAtap": { "Package": "miRNAtap", "Version": "1.8.0", "Depends": [ "R (>= 3.3.0)", "AnnotationDbi" ], "Imports": [ "DBI", "RSQLite", "stringr", "sqldf", "plyr", "methods" ], "Suggests": [ "topGO", "org.Hs.eg.db", "miRNAtap.db", "testthat" ], "License": "GPL-2", "MD5sum": "cdd3a56fcd98e3c95b18a77a488cc8ce", "NeedsCompilation": "no", "Title": "miRNAtap: microRNA Targets - Aggregated Predictions", "Description": "The package facilitates implementation of workflows requiring miRNA predictions, it allows to integrate ranked miRNA target predictions from multiple sources available online and aggregate them with various methods which improves quality of predictions above any of the single sources. Currently predictions are available for Homo sapiens, Mus musculus and Rattus norvegicus (the last one through homology translation).", "biocViews": [ "Classification", "Microarray", "Sequencing", "Software", "miRNA" ], "Author": "Maciej Pajak, T. Ian Simpson", "Maintainer": "Maciej Pajak ", "source.ver": "src/contrib/miRNAtap_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/miRNAtap_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/miRNAtap_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/miRNAtap_1.8.0.tgz", "vignettes": [ "vignettes/miRNAtap/inst/doc/miRNAtap.pdf" ], "vignetteTitles": [ "miRNAtap" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/miRNAtap/inst/doc/miRNAtap.R" ], "importsMe": [ "miRNAtap.db", "SpidermiR" ], "suggestsMe": [ "oneChannelGUI" ], "dependsOnMe": [ "miRNAtap.db" ] }, "Mirsynergy": { "Package": "Mirsynergy", "Version": "1.10.0", "Depends": [ "R (>= 3.0.2)", "igraph", "ggplot2" ], "Imports": [ "graphics", "grDevices", "gridExtra", "Matrix", "parallel", "RColorBrewer", "reshape", "scales", "utils" ], "Suggests": [ "glmnet", "RUnit", "BiocGenerics", "knitr" ], "License": "GPL-2", "MD5sum": "560b02cf2e88b03aec216e20800006fb", "NeedsCompilation": "no", "Title": "Mirsynergy", "Description": "Detect synergistic miRNA regulatory modules by overlapping neighbourhood expansion.", "biocViews": [ "Clustering", "Software" ], "Author": "Yue Li", "Maintainer": "Yue Li ", "URL": "http://www.cs.utoronto.ca/~yueli/Mirsynergy.html", "VignetteBuilder": "knitr", "source.ver": "src/contrib/Mirsynergy_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Mirsynergy_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Mirsynergy_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Mirsynergy_1.10.0.tgz", "vignettes": [ "vignettes/Mirsynergy/inst/doc/Mirsynergy.pdf" ], "vignetteTitles": [ "Mirsynergy" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Mirsynergy/inst/doc/Mirsynergy.R" ] }, "missMethyl": { "Package": "missMethyl", "Version": "1.8.0", "Depends": [ "R (>= 2.3.0)" ], "Imports": [ "limma", "minfi", "methylumi", "IlluminaHumanMethylation450kmanifest", "statmod", "ruv", "stringr", "IlluminaHumanMethylation450kanno.ilmn12.hg19", "org.Hs.eg.db", "AnnotationDbi", "BiasedUrn", "GO.db", "IlluminaHumanMethylationEPICmanifest", "IlluminaHumanMethylationEPICanno.ilm10b2.hg19" ], "Suggests": [ "minfiData", "BiocStyle", "knitr", "rmarkdown", "edgeR", "tweeDEseqCountData" ], "License": "GPL-2", "MD5sum": "d5a9e1e516df9f0367f159c17b5723e8", "NeedsCompilation": "no", "Title": "Analysing Illumina HumanMethylation BeadChip Data", "Description": "Normalisation and testing for differential variability and differential methylation for data from Illumina's Infinium HumanMethylation450 array. The normalisation procedure is subset-quantile within-array normalisation (SWAN), which allows Infinium I and II type probes on a single array to be normalised together. The test for differential variability is based on an empirical Bayes version of Levene's test. Differential methylation testing is performed using RUV, which can adjust for systematic errors of unknown origin in high-dimensional data by using negative control probes. Gene ontology analysis is performed by taking into account the number of probes per gene on the array.", "biocViews": [ "DNAMethylation", "DifferentialMethylation", "GeneSetEnrichment", "GeneticVariability", "GenomicVariation", "MethylationArray", "Normalization", "Software" ], "Author": "Belinda Phipson and Jovana Maksimovic", "Maintainer": "Belinda Phipson , Jovana Maksimovic ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/missMethyl_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/missMethyl_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/missMethyl_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/missMethyl_1.8.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/missMethyl/inst/doc/missMethyl.R" ], "htmlDocs": [ "vignettes/missMethyl/inst/doc/missMethyl.html" ], "htmlTitles": [ "missMethyl: Analysing Illumina HumanMethylation BeadChip Data" ], "importsMe": [ "DMRcate" ] }, "mitoODE": { "Package": "mitoODE", "Version": "1.12.0", "Depends": [ "R (>= 2.14.0)", "minpack.lm", "MASS", "parallel", "mitoODEdata", "KernSmooth" ], "License": "LGPL", "Archs": "i386, x64", "MD5sum": "814bef9e1f0c8fd1ca049305d0fdb691", "NeedsCompilation": "yes", "Title": "Implementation of the differential equation model described in \"Dynamical modelling of phenotypes in a genome-wide RNAi live-cell imaging assay\"", "Description": "The package contains the methods to fit a cell-cycle model on cell count data and the code to reproduce the results shown in our paper \"Dynamical modelling of phenotypes in a genome-wide RNAi live-cell imaging assay\" by Pau, G., Walter, T., Neumann, B., Heriche, J.-K., Ellenberg, J., & Huber, W., BMC Bioinformatics (2013), 14(1), 308. doi:10.1186/1471-2105-14-308", "biocViews": [ "CellBasedAssays", "ExperimentData", "Preprocessing", "Software", "TimeCourse" ], "Author": "Gregoire Pau", "Maintainer": "Gregoire Pau ", "SystemRequirements": "", "source.ver": "src/contrib/mitoODE_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/mitoODE_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/mitoODE_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/mitoODE_1.12.0.tgz", "vignettes": [ "vignettes/mitoODE/inst/doc/mitoODE-introduction.pdf" ], "vignetteTitles": [ "mitoODE" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/mitoODE/inst/doc/mitoODE-introduction.R" ] }, "MLInterfaces": { "Package": "MLInterfaces", "Version": "1.54.0", "Depends": [ "R (>= 2.9)", "methods", "BiocGenerics (>= 0.13.11)", "Biobase", "annotate", "cluster" ], "Imports": [ "gdata", "pls", "sfsmisc", "MASS", "rpart", "rda", "genefilter", "fpc", "ggvis", "shiny", "gbm", "RColorBrewer", "hwriter", "threejs (>= 0.2.2)", "mlbench", "stats4" ], "Suggests": [ "class", "e1071", "ipred", "randomForest", "gpls", "pamr", "nnet", "ALL", "hgu95av2.db", "som", "rgl", "hu6800.db", "lattice", "caret (>= 5.07)", "golubEsets", "ada", "keggorthology", "kernlab", "mboost", "party" ], "Enhances": [ "parallel" ], "License": "LGPL", "MD5sum": "e15331452d85bde5cfb0bcbe70cf671b", "NeedsCompilation": "no", "Title": "Uniform interfaces to R machine learning procedures for data in Bioconductor containers", "Description": "This package provides uniform interfaces to machine learning code for data in R and Bioconductor containers.", "biocViews": [ "Classification", "Clustering", "Software" ], "Author": "Vince Carey , Robert Gentleman, Jess Mar, and contributions from Jason Vertrees and Laurent Gatto ", "Maintainer": "V. Carey ", "source.ver": "src/contrib/MLInterfaces_1.54.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MLInterfaces_1.54.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MLInterfaces_1.54.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MLInterfaces_1.54.0.tgz", "vignettes": [ "vignettes/MLInterfaces/inst/doc/MLint_devel.pdf", "vignettes/MLInterfaces/inst/doc/MLInterfaces.pdf", "vignettes/MLInterfaces/inst/doc/MLprac2_2.pdf", "vignettes/MLInterfaces/inst/doc/xvalComputerClusters.pdf" ], "vignetteTitles": [ "MLInterfaces devel for schema-based MLearn", "MLInterfaces Primer", "A machine learning tutorial: applications of the Bioconductor MLInterfaces package to expression and ChIP-Seq data", "MLInterfaces Computer Cluster" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MLInterfaces/inst/doc/MLint_devel.R", "vignettes/MLInterfaces/inst/doc/MLInterfaces.R", "vignettes/MLInterfaces/inst/doc/MLprac2_2.R", "vignettes/MLInterfaces/inst/doc/xvalComputerClusters.R" ], "dependsOnMe": [ "a4Classif", "pRoloc", "SigCheck" ], "suggestsMe": [ "BiocCaseStudies" ] }, "MLP": { "Package": "MLP", "Version": "1.22.0", "Depends": [ "AnnotationDbi", "affy", "plotrix", "gplots", "gmodels", "gdata", "gtools" ], "Suggests": [ "GO.db", "org.Hs.eg.db", "org.Mm.eg.db", "org.Rn.eg.db", "org.Cf.eg.db", "KEGG.db", "annotate", "Rgraphviz", "GOstats", "limma", "mouse4302.db", "reactome.db" ], "License": "GPL-3", "MD5sum": "c96771e0e2523b8713a23a22eb60d0bf", "NeedsCompilation": "no", "Title": "MLP", "Description": "Mean Log P Analysis", "biocViews": [ "Genetics", "KEGG", "Reactome", "Software" ], "Author": "Nandini Raghavan, Tobias Verbeke, An De Bondt with contributions by Javier Cabrera, Dhammika Amaratunga, Tine Casneuf and Willem Ligtenberg", "Maintainer": "Tobias Verbeke ", "source.ver": "src/contrib/MLP_1.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MLP_1.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MLP_1.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MLP_1.22.0.tgz", "vignettes": [ "vignettes/MLP/inst/doc/UsingMLP.pdf" ], "vignetteTitles": [ "UsingMLP" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MLP/inst/doc/UsingMLP.R" ], "importsMe": [ "esetVis" ], "suggestsMe": [ "a4" ] }, "MLSeq": { "Package": "MLSeq", "Version": "1.14.1", "Depends": [ "R (>= 3.0.0)", "caret", "DESeq2", "Biobase", "limma", "randomForest", "edgeR" ], "Imports": [ "methods" ], "Suggests": [ "knitr", "e1071", "kernlab", "earth", "ellipse", "fastICA", "gam", "ipred", "klaR", "MASS", "mda", "mgcv", "mlbench", "nnet", "party", "pls", "pROC", "proxy", "RANN", "spls", "affy" ], "License": "GPL(>=2)", "MD5sum": "6a0b30b91ffc2dec1509e80172405319", "NeedsCompilation": "no", "Title": "Machine learning interface for RNA-Seq data", "Description": "This package applies several machine learning methods, including SVM, bagSVM, Random Forest and CART, to RNA-Seq data.", "biocViews": [ "Classification", "Clustering", "RNASeq", "Sequencing", "Software" ], "Author": "Gokmen Zararsiz, Dincer Goksuluk, Selcuk Korkmaz, Vahap Eldem, Izzet Parug Duru, Turgay Unver, Ahmet Ozturk", "Maintainer": "Gokmen Zararsiz ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/MLSeq_1.14.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MLSeq_1.14.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MLSeq_1.14.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MLSeq_1.14.1.tgz", "vignettes": [ "vignettes/MLSeq/inst/doc/MLSeq.pdf" ], "vignetteTitles": [ "MLSeq" ], "hasREADME": true, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MLSeq/inst/doc/MLSeq.R" ] }, "MMDiff2": { "Package": "MMDiff2", "Version": "1.2.0", "Depends": [ "R (>= 3.3)", "Rsamtools", "Biobase" ], "Imports": [ "GenomicRanges", "locfit", "BSgenome", "Biostrings", "shiny", "ggplot2", "RColorBrewer", "graphics", "grDevices", "parallel", "S4Vectors", "methods" ], "Suggests": [ "MMDiffBamSubset", "MotifDb", "knitr", "BiocStyle", "BSgenome.Mmusculus.UCSC.mm9" ], "License": "Artistic-2.0", "MD5sum": "d756c6accc009072a0707b264667f82b", "NeedsCompilation": "no", "Title": "Statistical Testing for ChIP-Seq data sets", "Description": "This package detects statistically significant differences between read enrichment profiles in different ChIP-Seq samples. To take advantage of shape differences it uses Kernel methods (Maximum Mean Discrepancy, MMD).", "biocViews": [ "ChIPSeq", "DifferentialPeakCalling", "Sequencing", "Software" ], "Author": "Gabriele Schweikert [cre, aut], David Kuo [aut]", "Maintainer": "Gabriele Schweikert ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/MMDiff2_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MMDiff2_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MMDiff2_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MMDiff2_1.2.0.tgz", "vignettes": [ "vignettes/MMDiff2/inst/doc/MMDiff2.pdf" ], "vignetteTitles": [ "An Introduction to the MMDiff2 method" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MMDiff2/inst/doc/MMDiff2.R" ], "suggestsMe": [ "MMDiffBamSubset" ] }, "mmnet": { "Package": "mmnet", "Version": "1.12.0", "Depends": [ "R (>= 2.14)", "igraph", "biom" ], "Imports": [ "Biobase", "RJSONIO", "stringr", "reshape2", "ggplot2", "KEGGREST", "plyr", "XML", "RCurl", "flexmix", "Matrix", "methods", "tools" ], "Suggests": [ "RCytoscape", "graph", "knitr" ], "License": "GPL (>= 2)", "MD5sum": "3f5999b26286a9214d74e2114f16a578", "NeedsCompilation": "no", "Title": "A metagenomic pipeline for systems biology", "Description": "This package gives the implementations microbiome metabolic network constructing and analyzing. It introduces a unique metagenomic systems biology approach, mapping metagenomic data to the KEGG global metabolic pathway and constructing a systems-level network. The system-level network and the next topological analysis will be of great help to analysis the various functional properties, including regulation and metabolic functionality of the metagenome.", "biocViews": [ "GraphsAndNetwork", "Microbiome", "Pathways", "Sequencing", "Software", "SystemsBiology" ], "Author": "Yang Cao, Fei Li", "Maintainer": "Yang Cao , Fei Li ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/mmnet_1.12.0.tar.gz", "vignettes": [ "vignettes/mmnet/inst/doc/mmnet.pdf" ], "vignetteTitles": [ "mmnet" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/mmnet/inst/doc/mmnet.R" ] }, "MmPalateMiRNA": { "Package": "MmPalateMiRNA", "Version": "1.24.0", "Depends": [ "R (>= 2.13.0)", "methods", "Biobase", "xtable", "limma", "statmod", "lattice", "vsn" ], "Imports": [ "limma", "lattice", "Biobase" ], "Suggests": [ "GOstats", "graph", "Category", "org.Mm.eg.db", "microRNA", "targetscan.Mm.eg.db", "RSQLite", "DBI", "AnnotationDbi", "clValid", "class", "cluster", "multtest", "RColorBrewer", "latticeExtra" ], "License": "GPL-3", "MD5sum": "97fda516753bcb8a99e8e0a6500a3db5", "NeedsCompilation": "no", "Title": "Murine Palate miRNA Expression Analysis", "Description": "R package compendium for the analysis of murine palate miRNA two-color expression data.", "biocViews": [ "Clustering", "DifferentialExpression", "GO", "Microarray", "MultipleComparison", "Pathways", "Preprocessing", "QualityControl", "ReportWriting", "SequenceMatching", "Software", "TwoChannel" ], "Author": "Guy Brock , Partha Mukhopadhyay , Vasyl Pihur , Robert M. Greene , and M. Michele Pisano ", "Maintainer": "Guy Brock ", "source.ver": "src/contrib/MmPalateMiRNA_1.24.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MmPalateMiRNA_1.24.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MmPalateMiRNA_1.24.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MmPalateMiRNA_1.24.0.tgz", "vignettes": [ "vignettes/MmPalateMiRNA/inst/doc/MmPalateMiRNA.pdf" ], "vignetteTitles": [ "Palate miRNA Analysis" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MmPalateMiRNA/inst/doc/MmPalateMiRNA.R" ] }, "MODA": { "Package": "MODA", "Version": "1.0.0", "Depends": [ "R (>= 3.1.0)" ], "Imports": [ "WGCNA", "dynamicTreeCut", "igraph" ], "Suggests": [ "BiocStyle", "knitr" ], "License": "GPL (>= 2)", "MD5sum": "46b58bb6676829b2f262a355f185d664", "NeedsCompilation": "no", "Title": "MODA: MOdule Differential Analysis for weighted gene co-expression network", "Description": "MODA can be used to estimate and construct condition-specific gene co-expression networks, and identify differentially expressed subnetworks as conserved or condition specific modules which are potentially associated with relevant biological processes.", "biocViews": [ "DifferentialExpression", "GeneExpression", "Microarray", "Network", "Software" ], "Author": "Dong Li, James B. Brown, Luisa Orsini, Zhisong Pan, Guyu Hu and Shan He", "Maintainer": "Dong Li ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/MODA_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MODA_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MODA_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MODA_1.0.0.tgz", "vignettes": [ "vignettes/MODA/inst/doc/MODA.pdf" ], "vignetteTitles": [ "Usage of MODA" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MODA/inst/doc/MODA.R" ] }, "mogsa": { "Package": "mogsa", "Version": "1.8.0", "Depends": [ "R (>= 3.2.0)" ], "Imports": [ "methods", "graphite", "genefilter", "BiocGenerics", "gplots", "GSEABase", "Biobase", "parallel", "corpcor", "svd", "cluster" ], "Suggests": [ "BiocStyle", "knitr" ], "License": "GPL-2", "MD5sum": "f625facfd92912ef8f8a6cf79c77670c", "NeedsCompilation": "no", "Title": "Multiple omics data integrative clustering and gene set analysis", "Description": "This package provide a method for doing gene set analysis based on multiple omics data.", "biocViews": [ "Clustering", "GeneExpression", "PrincipalComponent", "Software", "StatisticalMethod" ], "Author": "Chen Meng", "Maintainer": "Chen Meng ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/mogsa_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/mogsa_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/mogsa_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/mogsa_1.8.0.tgz", "vignettes": [ "vignettes/mogsa/inst/doc/moCluster.pdf", "vignettes/mogsa/inst/doc/mogsa.pdf" ], "vignetteTitles": [ "mogsa: gene set analysis on multiple omics data", "mogsa: gene set analysis on multiple omics data" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/mogsa/inst/doc/moCluster.R", "vignettes/mogsa/inst/doc/mogsa.R" ] }, "monocle": { "Package": "monocle", "Version": "2.2.0", "Depends": [ "R (>= 2.10.0)", "methods", "Matrix (>= 1.2-6)", "Biobase", "ggplot2 (>= 1.0.0)", "VGAM (>= 1.0-1)", "DDRTree (>= 0.1.4)" ], "Imports": [ "parallel", "igraph (>= 1.0.1)", "BiocGenerics", "HSMMSingleCell (>= 0.101.5)", "plyr", "cluster", "combinat", "fastICA", "grid", "irlba (>= 2.0.0)", "matrixStats", "MASS", "reshape2", "limma", "dplyr", "qlcMatrix", "pheatmap", "stringr", "proxy", "slam", "stats" ], "Suggests": [ "knitr", "Hmisc", "testthat" ], "License": "Artistic-2.0", "MD5sum": "d255175648c8414f2a4d9a68ebbb2225", "NeedsCompilation": "no", "Title": "Clustering, differential expression, and trajectory analysis for single- cell RNA-Seq", "Description": "Monocle performs differential expression and time-series analysis for single-cell expression experiments. It orders individual cells according to progress through a biological process, without knowing ahead of time which genes define progress through that process. Monocle also performs differential expression analysis, clustering, visualization, and other useful tasks on single cell expression data. It is designed to work with RNA-Seq and qPCR data, but could be used with other types as well.", "biocViews": [ "Clustering", "DataImport", "DataRepresentation", "DifferentialExpression", "GeneExpression", "Infrastructure", "MultipleComparison", "QualityControl", "RNASeq", "Sequencing", "Software", "Visualization" ], "Author": "Cole Trapnell", "Maintainer": "Cole Trapnell ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/monocle_2.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/monocle_2.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/monocle_2.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/monocle_2.2.0.tgz", "vignettes": [ "vignettes/monocle/inst/doc/monocle-vignette.pdf" ], "vignetteTitles": [ "Monocle: Differential expression and time-series analysis for single-cell RNA-Seq and qPCR experiments." ], "hasREADME": true, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/monocle/inst/doc/monocle-vignette.R" ], "importsMe": [ "uSORT" ], "suggestsMe": [ "scater", "scran", "sincell" ] }, "MoonlightR": { "Package": "MoonlightR", "Version": "1.0.0", "Depends": [ "R (>= 3.3)", "doParallel", "foreach" ], "Imports": [ "parmigene", "randomForest", "SummarizedExperiment", "gplots", "circlize", "RColorBrewer", "HiveR", "clusterProfiler", "DOSE", "Biobase", "limma", "grDevices", "graphics", "TCGAbiolinks", "GEOquery", "stats", "RISmed", "grid", "utils" ], "Suggests": [ "BiocStyle", "knitr", "rmarkdown", "testthat", "devtools", "roxygen2", "png" ], "License": "GPL (>= 3)", "MD5sum": "0996852bbf0e3a40ea2a3f26a3febb43", "NeedsCompilation": "no", "Title": "Identify oncogenes and tumor suppressor genes from omics data", "Description": "Motivation: The understanding of cancer mechanism requires the identification of genes playing a role in the development of the pathology and the characterization of their role (notably oncogenes and tumor suppressors). Results: We present an R/bioconductor package called MoonlightR which returns a list of candidate driver genes for specific cancer types on the basis of TCGA expression data. The method first infers gene regulatory networks and then carries out a functional enrichment analysis (FEA) (implementing an upstream regulator analysis, URA) to score the importance of well-known biological processes with respect to the studied cancer type. Eventually, by means of random forests, MoonlightR predicts two specific roles for the candidate driver genes: i) tumor suppressor genes (TSGs) and ii) oncogenes (OCGs). As a consequence, this methodology does not only identify genes playing a dual role (e.g. TSG in one cancer type and OCG in another) but also helps in elucidating the biological processes underlying their specific roles. In particular, MoonlightR can be used to discover OCGs and TSGs in the same cancer type. This may help in answering the question whether some genes change role between early stages (I, II) and late stages (III, IV) in breast cancer. In the future, this analysis could be useful to determine the causes of different resistances to chemotherapeutic treatments.", "biocViews": [ "DNAMethylation", "DifferentialExpression", "DifferentialMethylation", "GeneExpression", "GeneRegulation", "GeneSetEnrichment", "MethylationArray", "Network", "NetworkEnrichment", "Pathways", "Software", "Survival" ], "Author": "Antonio Colaprico*, Catharina Olsen*, Claudia Cava, Thilde Terkelsen, Laura Cantini, Andre Olsen, Gloria Bertoli, Andrei Zinovyev, Emmanuel Barillot, Isabella Castiglioni, Elena Papaleo, Gianluca Bontempi", "Maintainer": "Antonio Colaprico , Catharina Olsen ", "URL": "https://github.com/torongs82/Moonlight", "VignetteBuilder": "knitr", "BugReports": "https://github.com/torongs82/Moonlight/issues", "source.ver": "src/contrib/MoonlightR_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MoonlightR_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MoonlightR_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MoonlightR_1.0.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MoonlightR/inst/doc/Moonlight.R" ], "htmlDocs": [ "vignettes/MoonlightR/inst/doc/Moonlight.html" ], "htmlTitles": [ "Vignette Title" ] }, "MoPS": { "Package": "MoPS", "Version": "1.8.0", "Imports": [ "Biobase" ], "License": "GPL-3", "MD5sum": "97bf812dbcfa0fcc93406b63673178f9", "NeedsCompilation": "no", "Title": "MoPS - Model-based Periodicity Screening", "Description": "Identification and characterization of periodic fluctuations in time-series data.", "biocViews": [ "Classification", "GeneRegulation", "Regression", "Software", "TimeCourse" ], "Author": "Philipp Eser, Achim Tresch", "Maintainer": "Philipp Eser ", "source.ver": "src/contrib/MoPS_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MoPS_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MoPS_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MoPS_1.8.0.tgz", "vignettes": [ "vignettes/MoPS/inst/doc/MoPS.pdf" ], "vignetteTitles": [ "Model-based Periodicity Screening" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MoPS/inst/doc/MoPS.R" ] }, "mosaics": { "Package": "mosaics", "Version": "2.12.0", "Depends": [ "R (>= 3.0.0)", "methods", "graphics", "Rcpp" ], "Imports": [ "MASS", "splines", "lattice", "IRanges", "GenomicRanges", "GenomicAlignments", "Rsamtools", "GenomeInfoDb", "S4Vectors" ], "LinkingTo": [ "Rcpp" ], "Suggests": [ "mosaicsExample" ], "Enhances": [ "parallel" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "d106f71ca1592632e2e33af7df76e0bf", "NeedsCompilation": "yes", "Title": "MOSAiCS (MOdel-based one and two Sample Analysis and Inference for ChIP-Seq)", "Description": "This package provides functions for fitting MOSAiCS and MOSAiCS-HMM, a statistical framework to analyze one-sample or two-sample ChIP-seq data of transcription factor binding and histone modification.", "biocViews": [ "Bioinformatics", "ChIPseq", "Genetics", "Sequencing", "Software", "Transcription" ], "Author": "Dongjun Chung, Pei Fen Kuan, Rene Welch, Sunduz Keles", "Maintainer": "Dongjun Chung ", "URL": "http://groups.google.com/group/mosaics_user_group", "SystemRequirements": "Perl", "source.ver": "src/contrib/mosaics_2.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/mosaics_2.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/mosaics_2.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/mosaics_2.12.0.tgz", "vignettes": [ "vignettes/mosaics/inst/doc/mosaics-example.pdf" ], "vignetteTitles": [ "MOSAiCS" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/mosaics/inst/doc/mosaics-example.R" ] }, "motifbreakR": { "Package": "motifbreakR", "Version": "1.4.0", "Depends": [ "R (>= 3.2)", "grid", "MotifDb" ], "Imports": [ "methods", "compiler", "grDevices", "grImport", "stringr", "BiocGenerics", "S4Vectors (>= 0.9.25)", "IRanges", "GenomeInfoDb", "GenomicRanges", "Biostrings", "BSgenome", "rtracklayer", "VariantAnnotation", "BiocParallel", "motifStack", "Gviz", "matrixStats", "TFMPvalue" ], "Suggests": [ "BSgenome.Hsapiens.UCSC.hg19", "SNPlocs.Hsapiens.dbSNP.20120608", "SNPlocs.Hsapiens.dbSNP142.GRCh37", "knitr", "rmarkdown", "BSgenome.Drerio.UCSC.danRer7", "BiocStyle" ], "License": "GPL-2", "MD5sum": "16954bdc8c0b19ab0ad699a0c8188093", "NeedsCompilation": "no", "Title": "A Package For Predicting The Disruptiveness Of Single Nucleotide Polymorphisms On Transcription Factor Binding Sites", "Description": "We introduce motifbreakR, which allows the biologist to judge in the first place whether the sequence surrounding the polymorphism is a good match, and in the second place how much information is gained or lost in one allele of the polymorphism relative to another. MotifbreakR is both flexible and extensible over previous offerings; giving a choice of algorithms for interrogation of genomes with motifs from public sources that users can choose from; these are 1) a weighted-sum probability matrix, 2) log-probabilities, and 3) weighted by relative entropy. MotifbreakR can predict effects for novel or previously described variants in public databases, making it suitable for tasks beyond the scope of its original design. Lastly, it can be used to interrogate any genome curated within Bioconductor (currently there are 22).", "biocViews": [ "ChIPSeq", "MotifAnnotation", "Software", "Visualization" ], "Author": "Simon Gert Coetzee [aut, cre] Dennis J. Hazelett [aut]", "Maintainer": "Simon Gert Coetzee ", "VignetteBuilder": "knitr", "BugReports": "https://github.com/Simon-Coetzee/motifbreakR/issues", "source.ver": "src/contrib/motifbreakR_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/motifbreakR_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/motifbreakR_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/motifbreakR_1.4.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/motifbreakR/inst/doc/motifbreakR-vignette.R" ], "htmlDocs": [ "vignettes/motifbreakR/inst/doc/motifbreakR-vignette.html" ], "htmlTitles": [ "motifbreakR: an Introduction" ] }, "MotifDb": { "Package": "MotifDb", "Version": "1.16.1", "Depends": [ "R (>= 2.15.0)", "methods", "BiocGenerics", "S4Vectors", "IRanges", "Biostrings" ], "Imports": [ "rtracklayer" ], "Suggests": [ "RUnit", "seqLogo", "MotIV" ], "License": "Artistic-2.0 | file LICENSE", "License_is_FOSS": "no", "License_restricts_use": "yes", "MD5sum": "96376396f929770a263a868d772ca417", "NeedsCompilation": "no", "Title": "An Annotated Collection of Protein-DNA Binding Sequence Motifs", "Description": "More than 2000 annotated position frequency matrices from nine public sources, for multiple organisms.", "biocViews": [ "MotifAnnotation", "Software" ], "Author": "Paul Shannon", "Maintainer": "Paul Shannon ", "source.ver": "src/contrib/MotifDb_1.16.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MotifDb_1.16.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MotifDb_1.16.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MotifDb_1.16.1.tgz", "vignettes": [ "vignettes/MotifDb/inst/doc/MotifDb.pdf" ], "vignetteTitles": [ "%%MotifDb Overview" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/MotifDb/inst/doc/MotifDb.R" ], "dependsOnMe": [ "motifbreakR" ], "importsMe": [ "rTRMui" ], "suggestsMe": [ "DiffLogo", "MMDiff2", "motifStack", "profileScoreDist", "PWMEnrich", "rTRM", "vtpnet" ] }, "motifRG": { "Package": "motifRG", "Version": "1.18.0", "Depends": [ "R (>= 2.15)", "Biostrings (>= 2.26)", "IRanges", "seqLogo", "parallel", "methods", "grid", "graphics", "BSgenome", "XVector", "BSgenome.Hsapiens.UCSC.hg19" ], "Imports": [ "Biostrings", "IRanges", "seqLogo", "parallel", "methods", "grid", "graphics", "XVector" ], "License": "Artistic-2.0", "MD5sum": "2f1dab8afccdc3077109dcb514945f3b", "NeedsCompilation": "no", "Title": "A package for discriminative motif discovery, designed for high throughput sequencing dataset", "Description": "Tools for discriminative motif discovery using regression methods", "biocViews": [ "MotifDiscovery", "Software", "Transcription" ], "Author": "Zizhen Yao", "Maintainer": "Zizhen Yao ", "source.ver": "src/contrib/motifRG_1.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/motifRG_1.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/motifRG_1.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/motifRG_1.18.0.tgz", "vignettes": [ "vignettes/motifRG/inst/doc/motifRG.pdf" ], "vignetteTitles": [ "motifRG: regression-based discriminative motif discovery" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/motifRG/inst/doc/motifRG.R" ], "dependsOnMe": [ "RCAS" ] }, "motifStack": { "Package": "motifStack", "Version": "1.18.0", "Depends": [ "R (>= 2.15.1)", "methods", "grImport", "grid", "MotIV", "ade4", "Biostrings" ], "Imports": [ "XML", "scales" ], "Suggests": [ "RUnit", "BiocGenerics", "MotifDb", "RColorBrewer", "BiocStyle", "knitr" ], "License": "GPL (>= 2)", "MD5sum": "fb52e98375eb1312dde0addcc160f9cd", "NeedsCompilation": "no", "Title": "Plot stacked logos for single or multiple DNA, RNA and amino acid sequence", "Description": "The motifStack package is designed for graphic representation of multiple motifs with different similarity scores. It works with both DNA/RNA sequence motif and amino acid sequence motif. In addition, it provides the flexibility for users to customize the graphic parameters such as the font type and symbol colors.", "biocViews": [ "Alignment", "ChIPSeq", "ChIPchip", "DataImport", "Microarray", "MotifAnnotation", "SequenceMatching", "Sequencing", "Software", "Visualization" ], "Author": "Jianhong Ou, Michael Brodsky, Scot Wolfe and Lihua Julie Zhu", "Maintainer": "Jianhong Ou ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/motifStack_1.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/motifStack_1.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/motifStack_1.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/motifStack_1.18.0.tgz", "vignettes": [ "vignettes/motifStack/inst/doc/motifStack.pdf" ], "vignetteTitles": [ "motifStack Vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/motifStack/inst/doc/motifStack_HTML.R", "vignettes/motifStack/inst/doc/motifStack.R" ], "htmlDocs": [ "vignettes/motifStack/inst/doc/motifStack_HTML.html" ], "htmlTitles": [ "motifStack Vignette" ], "dependsOnMe": [ "dagLogo" ], "importsMe": [ "LowMACA", "motifbreakR" ], "suggestsMe": [ "ChIPpeakAnno" ] }, "MotIV": { "Package": "MotIV", "Version": "1.30.0", "Depends": [ "R (>= 2.10)", "BiocGenerics (>= 0.1.0)" ], "Imports": [ "graphics", "grid", "methods", "S4Vectors", "IRanges (>= 1.13.5)", "Biostrings (>= 1.24.0)", "lattice", "rGADEM", "utils" ], "Suggests": [ "rtracklayer" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "19da23b2900e7e9b334084a7bd78c17c", "NeedsCompilation": "yes", "Title": "Motif Identification and Validation", "Description": "This package makes use of STAMP for comparing a set of motifs to a given database (e.g. JASPAR). It can also be used to visualize motifs, motif distributions, modules and filter motifs.", "biocViews": [ "ChIPSeq", "ChIPchip", "GenomicSequence", "Microarray", "MotifAnnotation", "Software" ], "Author": "Eloi Mercier, Raphael Gottardo", "Maintainer": "Eloi Mercier , Raphael Gottardo ", "SystemRequirements": "GNU Scientific Library >= 1.6 (http://www.gnu.org/software/gsl/)", "source.ver": "src/contrib/MotIV_1.30.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MotIV_1.30.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MotIV_1.30.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MotIV_1.30.0.tgz", "vignettes": [ "vignettes/MotIV/inst/doc/MotIV.pdf" ], "vignetteTitles": [ "The MotIV users guide" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MotIV/inst/doc/MotIV.R" ], "dependsOnMe": [ "motifStack" ], "suggestsMe": [ "MotifDb" ] }, "MPFE": { "Package": "MPFE", "Version": "1.10.0", "License": "GPL (>= 3)", "MD5sum": "1b795cc05ca344cb18d8ac2df0f760be", "NeedsCompilation": "no", "Title": "Estimation of the amplicon methylation pattern distribution from bisulphite sequencing data", "Description": "Estimate distribution of methylation patterns from a table of counts from a bisulphite sequencing experiment given a non-conversion rate and read error rate.", "biocViews": [ "DNAMethylation", "HighThroughputSequencingData", "MethylSeq", "Software" ], "Author": "Peijie Lin, Sylvain Foret, Conrad Burden", "Maintainer": "Conrad Burden ", "source.ver": "src/contrib/MPFE_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MPFE_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MPFE_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MPFE_1.10.0.tgz", "vignettes": [ "vignettes/MPFE/inst/doc/MPFE.pdf" ], "vignetteTitles": [ "MPFE" ], "hasREADME": true, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MPFE/inst/doc/MPFE.R" ] }, "mQTL.NMR": { "Package": "mQTL.NMR", "Version": "1.8.0", "Depends": [ "R (>= 2.15.0)" ], "Imports": [ "qtl", "GenABEL", "MASS", "outliers", "graphics", "stats", "utils" ], "Suggests": [ "BiocStyle" ], "License": "Artistic-2.0", "MD5sum": "589c3e1693656fab52c360dc18f9986c", "NeedsCompilation": "yes", "Title": "Metabolomic Quantitative Trait Locus Mapping for 1H NMR data", "Description": "mQTL.NMR provides a complete mQTL analysis pipeline for 1H NMR data. Distinctive features include normalisation using most-used approaches, peak alignment using RSPA approach, dimensionality reduction using SRV and binning approaches, and mQTL analysis for animal and human cohorts.", "biocViews": [ "Cheminformatics", "Genetics", "Metabolomics", "SNP", "Software" ], "Author": "Lyamine Hedjazi and Jean-Baptiste Cazier", "Maintainer": "Lyamine Hedjazi ", "URL": "http://www.ican-institute.org/tools/", "source.ver": "src/contrib/mQTL.NMR_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/mQTL.NMR_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/mQTL.NMR_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/mQTL.NMR_1.8.0.tgz", "vignettes": [ "vignettes/mQTL.NMR/inst/doc/FAQ.pdf", "vignettes/mQTL.NMR/inst/doc/mQTLUse.pdf" ], "vignetteTitles": [ "Frequently Asked Questions", "How to use the mQTL.NMR package" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/mQTL.NMR/inst/doc/FAQ.R", "vignettes/mQTL.NMR/inst/doc/mQTLUse.R" ] }, "msa": { "Package": "msa", "Version": "1.6.0", "Depends": [ "R (>= 3.1.0)", "methods", "Biostrings (>= 2.30.0)" ], "Imports": [ "Rcpp (>= 0.11.1)", "BiocGenerics", "IRanges (>= 1.20.0)", "S4Vectors", "tools" ], "LinkingTo": [ "Rcpp" ], "Suggests": [ "Biobase", "knitr", "seqinr", "ape", "phangorn" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "204b75a17af6d47f00949ebee7e59bac", "NeedsCompilation": "yes", "Title": "Multiple Sequence Alignment", "Description": "The 'msa' package provides a unified R/Bioconductor interface to the multiple sequence alignment algorithms ClustalW, ClustalOmega, and Muscle. All three algorithms are integrated in the package, therefore, they do not depend on any external software tools and are available for all major platforms. The multiple sequence alignment algorithms are complemented by a function for pretty-printing multiple sequence alignments using the LaTeX package TeXshade.", "biocViews": [ "Alignment", "MultipleComparison", "MultipleSequenceAlignment", "Sequencing", "Software" ], "Author": "Enrico Bonatesta, Christoph Horejs-Kainrath, Ulrich Bodenhofer", "Maintainer": "Ulrich Bodenhofer ", "URL": "http://www.bioinf.jku.at/software/msa/", "SystemRequirements": "GNU make", "VignetteBuilder": "knitr", "source.ver": "src/contrib/msa_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/msa_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/msa_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/msa_1.6.0.tgz", "vignettes": [ "vignettes/msa/inst/doc/msa.pdf" ], "vignetteTitles": [ "msa - An R Package for Multiple Sequence Alignment" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/msa/inst/doc/msa.R" ], "importsMe": [ "odseq" ] }, "MSGFgui": { "Package": "MSGFgui", "Version": "1.8.0", "Depends": [ "mzR", "xlsx" ], "Imports": [ "shiny", "mzID (>= 1.2)", "MSGFplus", "shinyFiles (>= 0.4.0)", "tools" ], "Suggests": [ "knitr", "testthat" ], "License": "GPL (>= 2)", "MD5sum": "18c27296ba0ccfe557683439db749292", "NeedsCompilation": "no", "Title": "A shiny GUI for MSGFplus", "Description": "This package makes it possible to perform analyses using the MSGFplus package in a GUI environment. Furthermore it enables the user to investigate the results using interactive plots, summary statistics and filtering. Lastly it exposes the current results to another R session so the user can seamlessly integrate the gui into other workflows.", "biocViews": [ "GUI", "MassSpectrometry", "Proteomics", "Software", "Visualization" ], "Author": "Thomas Lin Pedersen", "Maintainer": "Thomas Lin Pedersen ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/MSGFgui_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MSGFgui_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MSGFgui_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MSGFgui_1.8.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MSGFgui/inst/doc/Using_MSGFgui.R" ], "htmlDocs": [ "vignettes/MSGFgui/inst/doc/Using_MSGFgui.html" ], "htmlTitles": [ "Using MSGFgui" ], "suggestsMe": [ "RforProteomics" ] }, "MSGFplus": { "Package": "MSGFplus", "Version": "1.8.0", "Depends": [ "methods" ], "Imports": [ "mzID" ], "Suggests": [ "gWidgets", "knitr", "testthat" ], "License": "GPL (>= 2)", "MD5sum": "a83a3a6788149aee6c95da78921c87c2", "NeedsCompilation": "no", "Title": "An interface between R and MS-GF+", "Description": "This package contains function to perform peptide identification using MS-GF+", "biocViews": [ "MassSpectrometry", "Proteomics", "Software" ], "Author": "Thomas Lin Pedersen", "Maintainer": "Thomas Lin Pedersen ", "SystemRequirements": "Java (>= 1.7)", "VignetteBuilder": "knitr", "source.ver": "src/contrib/MSGFplus_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MSGFplus_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MSGFplus_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MSGFplus_1.8.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MSGFplus/inst/doc/Using_MSGFplus.R" ], "htmlDocs": [ "vignettes/MSGFplus/inst/doc/Using_MSGFplus.html" ], "htmlTitles": [ "Using MSGFgui" ], "importsMe": [ "MSGFgui" ], "suggestsMe": [ "RforProteomics" ] }, "msmsEDA": { "Package": "msmsEDA", "Version": "1.12.0", "Depends": [ "R (>= 3.0.1)", "MSnbase" ], "Imports": [ "MASS", "gplots", "RColorBrewer" ], "License": "GPL-2", "MD5sum": "ee9d44031a61a44e2ceb5bc9c8cbb0a1", "NeedsCompilation": "no", "Title": "Exploratory Data Analysis of LC-MS/MS data by spectral counts", "Description": "Exploratory data analysis to assess the quality of a set of LC-MS/MS experiments, and visualize de influence of the involved factors.", "biocViews": [ "MassSpectrometry", "Proteomics", "Software" ], "Author": "Josep Gregori, Alex Sanchez, and Josep Villanueva", "Maintainer": "Josep Gregori ", "source.ver": "src/contrib/msmsEDA_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/msmsEDA_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/msmsEDA_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/msmsEDA_1.12.0.tgz", "vignettes": [ "vignettes/msmsEDA/inst/doc/msmsData-Vignette.pdf" ], "vignetteTitles": [ "msmsEDA: Batch effects detection in LC-MSMS experiments" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/msmsEDA/inst/doc/msmsData-Vignette.R" ], "dependsOnMe": [ "msmsTests" ], "suggestsMe": [ "Harman", "RforProteomics" ] }, "msmsTests": { "Package": "msmsTests", "Version": "1.12.0", "Depends": [ "R (>= 3.0.1)", "MSnbase", "msmsEDA" ], "Imports": [ "edgeR", "qvalue" ], "License": "GPL-2", "MD5sum": "0a347937dcb34a8d0186ccd49bab31eb", "NeedsCompilation": "no", "Title": "LC-MS/MS Differential Expression Tests", "Description": "Statistical tests for label-free LC-MS/MS data by spectral counts, to discover differentially expressed proteins between two biological conditions. Three tests are available: Poisson GLM regression, quasi-likelihood GLM regression, and the negative binomial of the edgeR package.The three models admit blocking factors to control for nuissance variables.To assure a good level of reproducibility a post-test filter is available, where we may set the minimum effect size considered biologicaly relevant, and the minimum expression of the most abundant condition.", "biocViews": [ "MassSpectrometry", "Proteomics", "Software" ], "Author": "Josep Gregori, Alex Sanchez, and Josep Villanueva", "Maintainer": "Josep Gregori i Font ", "source.ver": "src/contrib/msmsTests_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/msmsTests_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/msmsTests_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/msmsTests_1.12.0.tgz", "vignettes": [ "vignettes/msmsTests/inst/doc/msmsTests-Vignette.pdf", "vignettes/msmsTests/inst/doc/msmsTests-Vignette2.pdf" ], "vignetteTitles": [ "msmsTests: post test filters to improve reproducibility", "msmsTests: controlling batch effects by blocking" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/msmsTests/inst/doc/msmsTests-Vignette.R", "vignettes/msmsTests/inst/doc/msmsTests-Vignette2.R" ], "suggestsMe": [ "MSnID", "RforProteomics" ] }, "MSnbase": { "Package": "MSnbase", "Version": "2.0.2", "Depends": [ "R (>= 3.1)", "methods", "BiocGenerics (>= 0.7.1)", "Biobase (>= 2.15.2)", "mzR (>= 2.7.6)", "BiocParallel", "ProtGenerics (>= 1.5.1)" ], "Imports": [ "plyr", "IRanges", "preprocessCore", "vsn", "grid", "reshape2", "stats4", "affy", "impute", "pcaMethods", "mzID (>= 1.5.2)", "MALDIquant (>= 1.12)", "digest", "lattice", "ggplot2", "S4Vectors", "XML", "Rcpp" ], "LinkingTo": [ "Rcpp" ], "Suggests": [ "testthat", "pryr", "gridExtra", "microbenchmark", "zoo", "knitr (>= 1.1.0)", "rols", "Rdisop", "pRoloc", "pRolocdata (>= 1.7.1)", "msdata (>= 0.12.2)", "roxygen2", "rgl", "rpx", "AnnotationHub", "BiocStyle", "rmarkdown", "imputeLCMD", "norm", "gplots", "shiny" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "48077adae90435849f2965a460edde35", "NeedsCompilation": "yes", "Title": "Base Functions and Classes for MS-based Proteomics", "Description": "Basic plotting, data manipulation and processing of MS-based Proteomics data.", "biocViews": [ "DataImport", "Infrastructure", "MassSpectrometry", "Proteomics", "QualityControl", "Software" ], "Author": "Laurent Gatto with contributions from Guangchuang Yu, Samuel Wieczorek, Vasile-Cosmin Lazar, Vladislav Petyuk, Thomas Naake, Richie Cotton, Martina Fisher, Johannes Rainer and Sebastian Gibb.", "Maintainer": "Laurent Gatto ", "URL": "https://github.com/lgatto/MSnbase", "VignetteBuilder": "knitr", "BugReports": "https://github.com/lgatto/MSnbase/issues", "source.ver": "src/contrib/MSnbase_2.0.2.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MSnbase_2.0.2.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MSnbase_2.0.2.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MSnbase_2.0.2.tgz", "vignettes": [ "vignettes/MSnbase/inst/doc/MSnbase-demo.pdf", "vignettes/MSnbase/inst/doc/MSnbase-development.pdf", "vignettes/MSnbase/inst/doc/MSnbase-io.pdf" ], "vignetteTitles": [ "Base Functions and Classes for MS-based Proteomics", "MSnbase development", "MSnbase IO capabilities" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MSnbase/inst/doc/benchmarking.R", "vignettes/MSnbase/inst/doc/MSnbase-demo.R", "vignettes/MSnbase/inst/doc/MSnbase-development.R", "vignettes/MSnbase/inst/doc/MSnbase-io.R" ], "htmlDocs": [ "vignettes/MSnbase/inst/doc/benchmarking.html" ], "htmlTitles": [ "MSnbase benchmarking" ], "dependsOnMe": [ "msmsEDA", "msmsTests", "ProCoNA", "pRoloc", "pRolocdata", "pRolocGUI", "proteoQC", "RforProteomics", "synapter" ], "importsMe": [ "DAPAR", "DAPARdata", "MSnID", "MSstats", "Pbase", "ProteomicsAnnotationHubData", "RMassBank" ], "suggestsMe": [ "AnnotationHub", "biobroom", "BiocGenerics", "isobar", "qcmetrics", "readat", "rpx" ] }, "MSnID": { "Package": "MSnID", "Version": "1.8.0", "Depends": [ "R (>= 2.10)", "Rcpp" ], "Imports": [ "MSnbase (>= 1.12.1)", "mzID (>= 1.3.5)", "R.cache", "foreach", "doParallel", "parallel", "methods", "iterators", "data.table", "Biobase", "ProtGenerics", "reshape2", "dplyr", "mzR" ], "Suggests": [ "BiocStyle", "msmsTests", "ggplot2", "RUnit", "BiocGenerics" ], "License": "Artistic-2.0", "MD5sum": "ee98cf361322eefba6e20d462ca419ea", "NeedsCompilation": "no", "Title": "Utilities for Exploration and Assessment of Confidence of LC-MSn Proteomics Identifications", "Description": "Extracts MS/MS ID data from mzIdentML (leveraging mzID package) or text files. After collating the search results from multiple datasets it assesses their identification quality and optimize filtering criteria to achieve the maximum number of identifications while not exceeding a specified false discovery rate. Also contains a number of utilities to explore the MS/MS results and assess missed and irregular enzymatic cleavages, mass measurement accuracy, etc.", "biocViews": [ "MassSpectrometry", "Proteomics", "Software" ], "Author": "Vlad Petyuk with contributions from Laurent Gatto", "Maintainer": "Vlad Petyuk ", "source.ver": "src/contrib/MSnID_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MSnID_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MSnID_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MSnID_1.8.0.tgz", "vignettes": [ "vignettes/MSnID/inst/doc/msnid_vignette.pdf" ], "vignetteTitles": [ "MSnID Package for Handling MS/MS Identifications" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MSnID/inst/doc/msnid_vignette.R" ], "suggestsMe": [ "RforProteomics" ] }, "msPurity": { "Package": "msPurity", "Version": "1.0.0", "Depends": [ "Rcpp" ], "Imports": [ "plyr", "foreach", "parallel", "doSNOW", "stringr", "mzR", "reshape2", "fastcluster", "ggplot2", "sapa" ], "Suggests": [ "testthat", "xcms", "BiocStyle", "knitr", "rmarkdown", "msPurityData" ], "License": "GPL (>= 2)", "MD5sum": "e954cb89bbc62f65500cfe6cdf483193", "NeedsCompilation": "no", "Title": "Automated Evaluation of Precursor Ion Purity for Mass Spectrometry Based Fragmentation in Metabolomics", "Description": "Assess the contribution of the targeted precursor in fragmentation acquired or anticipated isolation windows using a metric called \"precursor purity\". Also provides simple processing steps (averaging, filtering, blank subtraction, etc) for DI-MS data. Works for both LC-MS(/MS) and DI-MS(/MS) data.", "biocViews": [ "MassSpectrometry", "Metabolomics", "Software" ], "Author": "Thomas N. Lawson, Ralf Weber, Martin Jones, Mark Viant, Warwick Dunn", "Maintainer": "Thomas N. Lawson ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/msPurity_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/msPurity_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/msPurity_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/msPurity_1.0.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/msPurity/inst/doc/msPurity-vignette.R" ], "htmlDocs": [ "vignettes/msPurity/inst/doc/msPurity-vignette.html" ], "htmlTitles": [ "msPurity" ] }, "MSstats": { "Package": "MSstats", "Version": "3.6.0", "Depends": [ "R (>= 3.2)" ], "Imports": [ "Rcpp", "lme4", "marray", "limma", "gplots", "ggplot2", "methods", "grid", "ggrepel", "preprocessCore", "data.table", "MSnbase", "reshape", "reshape2", "survival", "minpack.lm", "utils" ], "Suggests": [ "knitr", "rmarkdown" ], "License": "Artistic-2.0", "MD5sum": "41e260d885ec79a2df74b6268a23cc19", "NeedsCompilation": "no", "Title": "Protein Significance Analysis in DDA, SRM and DIA for Label-free or Label-based Proteomics Experiments", "Description": "A set of tools for statistical relative protein significance analysis in DDA, SRM and DIA experiments.", "Author": "Meena Choi [aut, cre], Cyril Galitzine [aut], Tsung-Heng Tsai [aut], Olga Vitek [aut]", "Maintainer": "Meena Choi ", "URL": "http://msstats.org", "VignetteBuilder": "knitr", "BugReports": "https://groups.google.com/forum/#!forum/msstats", "source.ver": "src/contrib/MSstats_3.6.0.tar.gz", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MSstats_3.6.0.tgz", "vignettes": [ "vignettes/MSstats/inst/doc/MSstats-manual.pdf" ], "vignetteTitles": [ "MSstats-manual.pdf" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MSstats/inst/doc/MSstats.R" ], "htmlDocs": [ "vignettes/MSstats/inst/doc/MSstats.html" ], "htmlTitles": [ "Vignette Title" ], "biocViews": [ "Software" ] }, "Mulcom": { "Package": "Mulcom", "Version": "1.24.0", "Depends": [ "R (>= 2.10)", "fields", "Biobase" ], "Imports": [ "graphics", "grDevices", "stats", "methods" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "091b500f721508faf1687b9e58ae91f7", "NeedsCompilation": "yes", "Title": "Calculates Mulcom test", "Description": "Identification of differentially expressed genes and false discovery rate (FDR) calculation by Multiple Comparison test", "biocViews": [ "DifferentialExpression", "GeneExpression", "Microarray", "MultipleComparison", "Software", "StatisticalMethod" ], "Author": "Claudio Isella", "Maintainer": "Claudio Isella ", "source.ver": "src/contrib/Mulcom_1.24.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Mulcom_1.24.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Mulcom_1.24.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Mulcom_1.24.0.tgz", "vignettes": [ "vignettes/Mulcom/inst/doc/MulcomVignette.pdf" ], "vignetteTitles": [ "Mulcom Manual" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Mulcom/inst/doc/MulcomVignette.R" ], "dependsOnMe": [ "prot2D" ] }, "MultiAssayExperiment": { "Package": "MultiAssayExperiment", "Version": "1.0.1", "Depends": [ "R (>= 3.3.0)" ], "Imports": [ "methods", "GenomicRanges (>= 1.25.93)", "BiocGenerics", "SummarizedExperiment (>= 1.3.81)", "S4Vectors", "IRanges", "Biobase", "shinydashboard", "shiny", "utils" ], "Suggests": [ "BiocStyle", "testthat", "knitr", "GenomicFiles", "HDF5Array", "rmarkdown" ], "License": "Artistic-2.0", "MD5sum": "f60f0cf5f277ba895554b515a52e089a", "NeedsCompilation": "no", "Title": "Create Classes and Functions for Managing Multiple Assays on Sets of Samples", "Description": "Develop an integrative environment where multiple assays are managed and preprocessed for genomic data analysis.", "biocViews": [ "DataRepresentation", "Infrastructure", "Software" ], "Author": "MultiAssay SIG", "Maintainer": "Marcel Ramos ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/MultiAssayExperiment_1.0.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MultiAssayExperiment_1.0.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MultiAssayExperiment_1.0.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MultiAssayExperiment_1.0.1.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/MultiAssayExperiment/inst/doc/MultiAssayExperiment.R", "vignettes/MultiAssayExperiment/inst/doc/pradMAEO-RTCGAToolbox.R", "vignettes/MultiAssayExperiment/inst/doc/UsingHDF5Array.R" ], "htmlDocs": [ "vignettes/MultiAssayExperiment/inst/doc/MultiAssayExperiment.html", "vignettes/MultiAssayExperiment/inst/doc/pradMAEO-RTCGAToolbox.html", "vignettes/MultiAssayExperiment/inst/doc/UsingHDF5Array.html" ], "htmlTitles": [ "Coordinating Analysis of Multi-Assay Experiments", "MultiAssayExperiment: Prostate Cancer Data", "HDF5Array and MultiAssayExperiment" ], "importsMe": [ "GOpro" ], "dependsOnMe": [ "yriMulti" ] }, "multiClust": { "Package": "multiClust", "Version": "1.4.0", "Imports": [ "mclust", "ctc", "survival", "cluster", "dendextend", "amap", "graphics", "grDevices" ], "Suggests": [ "knitr", "gplots", "RUnit", "BiocGenerics", "preprocessCore", "Biobase", "GEOquery" ], "License": "GPL (>= 2)", "MD5sum": "ce5492526ef0b3cd5404ace01c5aa790", "NeedsCompilation": "no", "Title": "multiClust: An R-package for Identifying Biologically Relevant Clusters in Cancer Transcriptome Profiles", "Description": "Clustering is carried out to identify patterns in transcriptomics profiles to determine clinically relevant subgroups of patients. Feature (gene) selection is a critical and an integral part of the process. Currently, there are many feature selection and clustering methods to identify the relevant genes and perform clustering of samples. However, choosing an appropriate methodology is difficult. In addition, extensive feature selection methods have not been supported by the available packages. Hence, we developed an integrative R-package called multiClust that allows researchers to experiment with the choice of combination of methods for gene selection and clustering with ease. Using multiClust, we identified the best performing clustering methodology in the context of clinical outcome. Our observations demonstrate that simple methods such as variance-based ranking perform well on the majority of data sets, provided that the appropriate number of genes is selected. However, different gene ranking and selection methods remain relevant as no methodology works for all studies.", "biocViews": [ "Clustering", "FeatureExtraction", "GeneExpression", "Software", "Survival" ], "Author": "Nathan Lawlor [aut, cre], Peiyong Guan [aut], Alec Fabbri [aut], Krish Karuturi [aut], Joshy George [aut]", "Maintainer": "Nathan Lawlor ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/multiClust_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/multiClust_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/multiClust_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/multiClust_1.4.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/multiClust/inst/doc/multiClust.R" ], "htmlDocs": [ "vignettes/multiClust/inst/doc/multiClust.html" ], "htmlTitles": [ "\"A Guide to multiClust\"" ] }, "MultiDataSet": { "Package": "MultiDataSet", "Version": "1.2.0", "Depends": [ "R (>= 3.3)", "Biobase" ], "Imports": [ "BiocGenerics", "GenomicRanges", "IRanges", "minfi", "S4Vectors", "SummarizedExperiment", "methods", "IlluminaHumanMethylation450kanno.ilmn12.hg19", "utils" ], "Suggests": [ "MEALData", "minfiData", "knitr", "rmarkdown", "testthat", "methylumi", "omicade4", "iClusterPlus", "GEOquery" ], "License": "file LICENSE", "MD5sum": "e00a6d480c9aac826dcd7ba68b247b7b", "NeedsCompilation": "no", "Title": "Implementation of the BRGE's (Bioinformatic Research Group in Epidemiology from Center for Research in Environmental Epidemiology) MultiDataSet and MethylationSet", "Description": "Implementation of the BRGE's (Bioinformatic Research Group in Epidemiology from Center for Research in Environmental Epidemiology) MultiDataSet and MethylationSet. MultiDataSet is designed for integrating multi omics data sets and MethylationSet to contain normalized methylation data. These package contains base classes for MEAL and rexposome packages.", "biocViews": [ "DataRepresentation", "Software" ], "Author": "Carlos Ruiz-Arenas [aut, cre], Carles Hernandez-Ferrer [aut], Juan R. Gonzlez [aut]", "Maintainer": "Carlos Ruiz-Arenas ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/MultiDataSet_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MultiDataSet_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MultiDataSet_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MultiDataSet_1.2.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/MultiDataSet/inst/doc/MultiDataSet.R" ], "htmlDocs": [ "vignettes/MultiDataSet/inst/doc/MultiDataSet.html" ], "htmlTitles": [ "Introduction to MultiDataSet" ], "dependsOnMe": [ "MEAL" ] }, "MultiMed": { "Package": "MultiMed", "Version": "1.8.0", "Depends": [ "R (>= 3.1.0)" ], "Suggests": [ "RUnit", "BiocGenerics" ], "License": "GPL (>= 2) + file LICENSE", "MD5sum": "6ec5e807c156adb17e079959a7b21af6", "NeedsCompilation": "no", "Title": "Testing multiple biological mediators simultaneously", "Description": "Implements permutation method with joint correction for testing multiple mediators", "biocViews": [ "MultipleComparison", "Software", "StatisticalMethod" ], "Author": "Simina M. Boca, Joshua N. Sampson", "Maintainer": "Simina M. Boca ", "source.ver": "src/contrib/MultiMed_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MultiMed_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MultiMed_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MultiMed_1.8.0.tgz", "vignettes": [ "vignettes/MultiMed/inst/doc/MultiMed.pdf" ], "vignetteTitles": [ "MultiMedTutorial" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/MultiMed/inst/doc/MultiMed.R" ] }, "multiscan": { "Package": "multiscan", "Version": "1.34.0", "Depends": [ "R (>= 2.3.0)" ], "Imports": [ "Biobase", "utils" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "0713a788854e15b2494ebef85da797bc", "NeedsCompilation": "yes", "Title": "R package for combining multiple scans", "Description": "Estimates gene expressions from several laser scans of the same microarray", "biocViews": [ "Microarray", "Preprocessing", "Software" ], "Author": "Mizanur Khondoker , Chris Glasbey, Bruce Worton.", "Maintainer": "Mizanur Khondoker ", "source.ver": "src/contrib/multiscan_1.34.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/multiscan_1.34.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/multiscan_1.34.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/multiscan_1.34.0.tgz", "vignettes": [ "vignettes/multiscan/inst/doc/multiscan.pdf" ], "vignetteTitles": [ "An R Package for Estimating Gene Expressions using Multiple Scans" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/multiscan/inst/doc/multiscan.R" ] }, "multtest": { "Package": "multtest", "Version": "2.30.0", "Depends": [ "R (>= 2.10)", "methods", "BiocGenerics", "Biobase" ], "Imports": [ "survival", "MASS", "stats4" ], "Suggests": [ "snow" ], "License": "LGPL", "Archs": "i386, x64", "MD5sum": "5b86c1a043a80ee2b95a111b660985b6", "NeedsCompilation": "yes", "Title": "Resampling-based multiple hypothesis testing", "Description": "Non-parametric bootstrap and permutation resampling-based multiple testing procedures (including empirical Bayes methods) for controlling the family-wise error rate (FWER), generalized family-wise error rate (gFWER), tail probability of the proportion of false positives (TPPFP), and false discovery rate (FDR). Several choices of bootstrap-based null distribution are implemented (centered, centered and scaled, quantile-transformed). Single-step and step-wise methods are available. Tests based on a variety of t- and F-statistics (including t-statistics based on regression parameters from linear and survival models as well as those based on correlation parameters) are included. When probing hypotheses with t-statistics, users may also select a potentially faster null distribution which is multivariate normal with mean zero and variance covariance matrix derived from the vector influence function. Results are reported in terms of adjusted p-values, confidence regions and test statistic cutoffs. The procedures are directly applicable to identifying differentially expressed genes in DNA microarray experiments.", "biocViews": [ "DifferentialExpression", "Microarray", "MultipleComparison", "Software" ], "Author": "Katherine S. Pollard, Houston N. Gilbert, Yongchao Ge, Sandra Taylor, Sandrine Dudoit", "Maintainer": "Katherine S. Pollard ", "source.ver": "src/contrib/multtest_2.30.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/multtest_2.30.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/multtest_2.30.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/multtest_2.30.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "dependsOnMe": [ "a4Base", "aCGH", "BicARE", "iPAC", "KCsmart", "LMGene", "PREDA", "rain", "REDseq", "SAGx", "siggenes", "webbioc" ], "importsMe": [ "ABarray", "aCGH", "adSplit", "anota", "ChIPpeakAnno", "GeneSelector", "IsoGeneGUI", "mAPKL", "metabomxtr", "nethet", "OCplus", "phyloseq", "REDseq", "RTopper", "synapter", "webbioc", "xcms" ], "suggestsMe": [ "annaffy", "BiocCaseStudies", "ecolitk", "factDesign", "GeneSelector", "GGtools", "GOstats", "gQTLstats", "GSEAlm", "maigesPack", "MmPalateMiRNA", "oneChannelGUI", "pcot2", "ropls", "topGO" ] }, "muscle": { "Package": "muscle", "Version": "3.16.0", "Depends": [ "Biostrings" ], "License": "Unlimited", "Archs": "i386, x64", "MD5sum": "bfb04caf19a5ef16a3a827b6a6e5e787", "NeedsCompilation": "yes", "Title": "Multiple Sequence Alignment with MUSCLE", "Description": "MUSCLE performs multiple sequence alignments of nucleotide or amino acid sequences.", "biocViews": [ "Alignment", "DataImport", "Genetics", "MultipleSequenceAlignment", "SequenceMatching", "Sequencing", "Software" ], "Author": "Algorithm by Robert C. Edgar. R port by Alex T. Kalinka.", "Maintainer": "Alex T. Kalinka ", "URL": "http://www.drive5.com/muscle/", "source.ver": "src/contrib/muscle_3.16.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/muscle_3.16.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/muscle_3.16.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/muscle_3.16.0.tgz", "vignettes": [ "vignettes/muscle/inst/doc/muscle-vignette.pdf" ], "vignetteTitles": [ "A guide to using muscle" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/muscle/inst/doc/muscle-vignette.R" ] }, "MutationalPatterns": { "Package": "MutationalPatterns", "Version": "1.0.0", "Depends": [ "R (>= 3.3.0)", "NMF (>= 0.20.6)", "GenomicRanges (>= 1.24.0)" ], "Imports": [ "stats", "BiocGenerics (>= 0.18.0)", "VariantAnnotation (>= 1.18.1)", "reshape2 (>= 1.4.1)", "plyr (>= 1.8.3)", "ggplot2 (>= 2.1.0)", "pracma (>= 1.8.8)", "SummarizedExperiment (>= 1.2.2)", "IRanges (>= 2.6.0)", "GenomeInfoDb (>= 1.8.1)", "Biostrings (>= 2.40.0)", "gridExtra (>= 2.2.1)" ], "Suggests": [ "BSgenome (>= 1.40.0)", "BiocStyle (>= 2.0.3)", "biomaRt (>= 2.28.0)", "BSgenome.Hsapiens.UCSC.hg19 (>= 1.4.0)", "TxDb.Hsapiens.UCSC.hg19.knownGene (>= 3.2.2)", "rtracklayer (>= 1.32.2)" ], "License": "MIT + file LICENSE", "MD5sum": "9aa7b140c97dfbb6722a31e98bb64029", "NeedsCompilation": "no", "Title": "Studying patterns in base substitution catalogues", "Description": "An extensive toolset for the characterization and visualization of a wide range of mutational patterns in base substitution data.", "biocViews": [ "Genetics", "Software", "SomaticMutation" ], "Author": "Francis Blokzijl, Roel Janssen, Ruben van Boxtel, Edwin Cuppen", "Maintainer": "Francis Blokzijl , Roel Janssen ", "URL": "https://github.com/CuppenResearch/MutationalPatterns", "source.ver": "src/contrib/MutationalPatterns_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MutationalPatterns_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MutationalPatterns_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MutationalPatterns_1.0.0.tgz", "vignettes": [ "vignettes/MutationalPatterns/inst/doc/MutationalPatterns.pdf" ], "vignetteTitles": [ "Introduction to MutationalPatterns" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/MutationalPatterns/inst/doc/MutationalPatterns.R" ] }, "MVCClass": { "Package": "MVCClass", "Version": "1.48.0", "Depends": [ "R (>= 2.1.0)", "methods" ], "License": "LGPL", "MD5sum": "1b538f84a68d674a5184e4aa51a87b54", "NeedsCompilation": "no", "Title": "Model-View-Controller (MVC) Classes", "Description": "Creates classes used in model-view-controller (MVC) design", "biocViews": [ "GraphAndNetwork", "Infrastructure", "Software", "Visualization" ], "Author": "Elizabeth Whalen", "Maintainer": "Elizabeth Whalen ", "source.ver": "src/contrib/MVCClass_1.48.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/MVCClass_1.48.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/MVCClass_1.48.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/MVCClass_1.48.0.tgz", "vignettes": [ "vignettes/MVCClass/inst/doc/MVCClass.pdf" ], "vignetteTitles": [ "MVCClass" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "dependsOnMe": [ "BioMVCClass" ] }, "mvGST": { "Package": "mvGST", "Version": "1.8.0", "Depends": [ "R(>= 2.10.0)", "GO.db", "Rgraphviz" ], "Imports": [ "gProfileR", "stringr", "topGO", "GOstats", "annotate", "AnnotationDbi", "graph" ], "Suggests": [ "hgu133plus2.db", "org.Hs.eg.db" ], "License": "GPL-3", "MD5sum": "71e2a8b7ce42e7cf5b05a98793c2f0cd", "NeedsCompilation": "no", "Title": "Multivariate and directional gene set testing", "Description": "mvGST provides platform-independent tools to identify GO terms (gene sets) that are differentially active (up or down) in multiple contrasts of interest. Given a matrix of one-sided p-values (rows for genes, columns for contrasts), mvGST uses meta-analytic methods to combine p-values for all genes annotated to each gene set, and then classify each gene set as being significantly more active (1), less active (-1), or not significantly differentially active (0) in each contrast of interest. With multiple contrasts of interest, each gene set is assigned to a profile (across contrasts) of differential activity. Tools are also provided for visualizing (in a GO graph) the gene sets classified to a given profile.", "biocViews": [ "DifferentialExpression", "GO", "GeneSetEnrichment", "GraphAndNetwork", "Microarray", "OneChannel", "Pathways", "RNASeq", "Software" ], "Author": "John R. Stevens and Dennis S. Mecham", "Maintainer": "John R. Stevens ", "source.ver": "src/contrib/mvGST_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/mvGST_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/mvGST_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/mvGST_1.8.0.tgz", "vignettes": [ "vignettes/mvGST/inst/doc/mvGST.pdf" ], "vignetteTitles": [ "mvGST Tutorial Vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/mvGST/inst/doc/mvGST.R" ] }, "mygene": { "Package": "mygene", "Version": "1.10.0", "Depends": [ "R (>= 3.2.1)", "GenomicFeatures" ], "Imports": [ "httr (>= 0.3)", "jsonlite (>= 0.9.7)", "S4Vectors", "Hmisc", "sqldf", "plyr" ], "Suggests": [ "BiocStyle" ], "License": "Artistic-2.0", "MD5sum": "5b157f7c8fe98417f3aa32c3e859a798", "NeedsCompilation": "no", "Title": "Access MyGene.Info_ services", "Description": "MyGene.Info_ provides simple-to-use REST web services to query/retrieve gene annotation data. It's designed with simplicity and performance emphasized. *mygene*, is an easy-to-use R wrapper to access MyGene.Info_ services.", "biocViews": [ "Annotation", "Software" ], "Author": "Adam Mark, Ryan Thompson, Cyrus Afrasiabi, Chunlei Wu", "Maintainer": "Adam Mark, Cyrus Afrasiabi, Chunlei Wu ", "source.ver": "src/contrib/mygene_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/mygene_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/mygene_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/mygene_1.10.0.tgz", "vignettes": [ "vignettes/mygene/inst/doc/mygene.pdf" ], "vignetteTitles": [ "Using mygene.R" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/mygene/inst/doc/mygene.R" ], "importsMe": [ "MetaboSignal" ] }, "myvariant": { "Package": "myvariant", "Version": "1.4.0", "Depends": [ "R (>= 3.2.1)", "VariantAnnotation" ], "Imports": [ "httr", "jsonlite", "S4Vectors", "Hmisc", "plyr", "magrittr", "GenomeInfoDb" ], "Suggests": [ "BiocStyle" ], "License": "Artistic-2.0", "MD5sum": "a28109d92982772ee94eb6da3a32c349", "NeedsCompilation": "no", "Title": "Accesses MyVariant.info variant query and annotation services", "Description": "MyVariant.info is a comprehensive aggregation of variant annotation resources. myvariant is a wrapper for querying MyVariant.info services", "biocViews": [ "Annotation", "GenomicVariation", "Software", "VariantAnnotation" ], "Author": "Adam Mark", "Maintainer": "Adam Mark, Chunlei Wu ", "source.ver": "src/contrib/myvariant_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/myvariant_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/myvariant_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/myvariant_1.4.0.tgz", "vignettes": [ "vignettes/myvariant/inst/doc/myvariant.pdf" ], "vignetteTitles": [ "Using MyVariant.R" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/myvariant/inst/doc/myvariant.R" ] }, "mzID": { "Package": "mzID", "Version": "1.12.0", "Depends": [ "methods" ], "Imports": [ "XML", "plyr", "parallel", "doParallel", "foreach", "iterators", "ProtGenerics" ], "Suggests": [ "knitr", "testthat" ], "License": "GPL (>= 2)", "MD5sum": "1548319d721b5ff7f6cf02dc6fe90f46", "NeedsCompilation": "no", "Title": "An mzIdentML parser for R", "Description": "A parser for mzIdentML files implemented using the XML package. The parser tries to be general and able to handle all types of mzIdentML files with the drawback of having less 'pretty' output than a vendor specific parser. Please contact the maintainer with any problems and supply an mzIdentML file so the problems can be fixed quickly.", "biocViews": [ "DataImport", "MassSpectrometry", "Proteomics", "Software" ], "Author": "Thomas Lin Pedersen, Vladislav A Petyuk with contributions from Laurent Gatto and Sebastian Gibb.", "Maintainer": "Thomas Lin Pedersen ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/mzID_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/mzID_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/mzID_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/mzID_1.12.0.tgz", "vignettes": [ "vignettes/mzID/inst/doc/HOWTO_mzID.pdf" ], "vignetteTitles": [ "Using mzID" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/mzID/inst/doc/HOWTO_mzID.R" ], "importsMe": [ "MSGFgui", "MSGFplus", "MSnbase", "MSnID", "Pbase" ], "suggestsMe": [ "mzR", "RforProteomics" ] }, "mzR": { "Package": "mzR", "Version": "2.8.1", "Depends": [ "Rcpp (>= 0.10.1)", "methods", "utils" ], "Imports": [ "Biobase", "BiocGenerics (>= 0.13.6)", "ProtGenerics" ], "LinkingTo": [ "Rcpp", "zlibbioc" ], "Suggests": [ "msdata (>= 0.3.5)", "RUnit", "mzID", "BiocStyle", "knitr", "XML" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "af4274f5dde013bc5a2302fce2a05b16", "NeedsCompilation": "yes", "Title": "parser for netCDF, mzXML, mzData and mzML and mzIdentML files (mass spectrometry data)", "Description": "mzR provides a unified API to the common file formats and parsers available for mass spectrometry data. It comes with a wrapper for the ISB random access parser for mass spectrometry mzXML, mzData and mzML files. The package contains the original code written by the ISB, and a subset of the proteowizard library for mzML and mzIdentML. The netCDF reading code has previously been used in XCMS.", "biocViews": [ "DataImport", "Infrastructure", "MassSpectrometry", "Metabolomics", "Proteomics", "Software" ], "Author": "Bernd Fischer, Steffen Neumann, Laurent Gatto, Qiang Kou", "Maintainer": "Bernd Fischer , Steffen Neumann , Laurent Gatto , Qiang Kou ", "URL": "https://github.com/sneumann/mzR/", "SystemRequirements": "C++11, GNU make, NetCDF", "VignetteBuilder": "knitr", "BugReports": "https://github.com/sneumann/mzR/issues/", "source.ver": "src/contrib/mzR_2.8.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/mzR_2.8.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/mzR_2.8.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/mzR_2.8.1.tgz", "vignettes": [ "vignettes/mzR/inst/doc/mzR.pdf" ], "vignetteTitles": [ "Accessin raw mass spectrometry and identification data" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/mzR/inst/doc/mzR.R" ], "dependsOnMe": [ "MSGFgui", "MSnbase", "xcms" ], "importsMe": [ "MSnID", "msPurity", "Pbase", "ProteomicsAnnotationHubData", "RMassBank", "SIMAT", "yamss" ], "suggestsMe": [ "AnnotationHub", "msdata", "qcmetrics", "RforProteomics" ] }, "NanoStringDiff": { "Package": "NanoStringDiff", "Version": "1.4.0", "Depends": [ "Biobase" ], "Imports": [ "matrixStats", "methods" ], "Suggests": [ "testthat", "BiocStyle" ], "License": "GPL", "MD5sum": "88dd4de8daa08155f34844fbf58f51e4", "NeedsCompilation": "no", "Title": "Differential Expression Analysis of NanoString nCounter Data", "Description": "This Package utilizes a generalized linear model(GLM) of the negative binomial family to characterize count data and allows for multi-factor design. NanoStrongDiff incorporate size factors, calculated from positive controls and housekeeping controls, and background level, obtained from negative controls, in the model framework so that all the normalization information provided by NanoString nCounter Analyzer is fully utilized.", "biocViews": [ "DifferentialExpression", "Normalization", "Software" ], "Author": "hong wang , chi wang ", "Maintainer": "hong wang ", "source.ver": "src/contrib/NanoStringDiff_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/NanoStringDiff_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/NanoStringDiff_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/NanoStringDiff_1.4.0.tgz", "vignettes": [ "vignettes/NanoStringDiff/inst/doc/NanoStringDiff.pdf" ], "vignetteTitles": [ "NanoStringDiff Vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/NanoStringDiff/inst/doc/NanoStringDiff.R" ] }, "NanoStringQCPro": { "Package": "NanoStringQCPro", "Version": "1.6.0", "Depends": [ "R (>= 3.2)", "methods" ], "Imports": [ "AnnotationDbi (>= 1.26.0)", "org.Hs.eg.db (>= 2.14.0)", "Biobase (>= 2.24.0)", "knitr (>= 1.12)", "NMF (>= 0.20.5)", "RColorBrewer (>= 1.0-5)", "png (>= 0.1-7)" ], "Suggests": [ "roxygen2 (>= 4.0.1)", "testthat", "BiocStyle" ], "License": "Artistic-2.0", "MD5sum": "aab57d0551f829bd8ebca222add98fca", "NeedsCompilation": "no", "Title": "Quality metrics and data processing methods for NanoString mRNA gene expression data", "Description": "NanoStringQCPro provides a set of quality metrics that can be used to assess the quality of NanoString mRNA gene expression data -- i.e. to identify outlier probes and outlier samples. It also provides different background subtraction and normalization approaches for this data. It outputs suggestions for flagging samples/probes and an easily sharable html quality control output.", "biocViews": [ "Microarray", "Normalization", "Preprocessing", "QualityControl", "ReportWriting", "Software", "mRNAMicroarray" ], "Author": "Dorothee Nickles , Thomas Sandmann , Robert Ziman , Richard Bourgon ", "Maintainer": "Robert Ziman ", "source.ver": "src/contrib/NanoStringQCPro_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/NanoStringQCPro_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/NanoStringQCPro_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/NanoStringQCPro_1.6.0.tgz", "vignettes": [ "vignettes/NanoStringQCPro/inst/doc/vignetteNanoStringQCPro.pdf" ], "vignetteTitles": [ "NanoStringQCPro overview" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/NanoStringQCPro/inst/doc/vignetteNanoStringQCPro.R" ] }, "NarrowPeaks": { "Package": "NarrowPeaks", "Version": "1.18.0", "Depends": [ "R (>= 2.10.0)", "splines" ], "Imports": [ "BiocGenerics", "S4Vectors", "IRanges", "GenomicRanges", "GenomeInfoDb", "fda", "CSAR", "ICSNP" ], "Suggests": [ "rtracklayer", "BiocStyle", "GenomicRanges", "CSAR" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "d881870084ec1fcd822a4d44e908597e", "NeedsCompilation": "yes", "Title": "Shape-based Analysis of Variation in ChIP-seq using Functional PCA", "Description": "The package applies a functional version of principal component analysis (FPCA) to: (1) Postprocess data in wiggle track format, commonly produced by generic ChIP-seq peak callers, by applying FPCA over a set of read-enriched regions (ChIP-seq peaks). This is done to study variability of the the peaks, or to shorten their genomic locations accounting for a given proportion of variation among the enrichment-score profiles. (2) Analyse differential variation between multiple ChIP-seq samples with replicates. The function 'narrowpeaksDiff' quantifies differences between the shapes, and uses Hotelling's T2 tests on the functional principal component scores to identify significant differences across conditions. An application of the package for Arabidopsis datasets is described in Mateos, Madrigal, et al. (2015) Genome Biology: 16:31.", "biocViews": [ "ChIPSeq", "Genetics", "Sequencing", "Software", "Transcription", "Visualization" ], "Author": "Pedro Madrigal , Pawel Krajewski ", "Maintainer": "Pedro Madrigal ", "source.ver": "src/contrib/NarrowPeaks_1.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/NarrowPeaks_1.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/NarrowPeaks_1.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/NarrowPeaks_1.18.0.tgz", "vignettes": [ "vignettes/NarrowPeaks/inst/doc/NarrowPeaks.pdf" ], "vignetteTitles": [ "NarrowPeaks Vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/NarrowPeaks/inst/doc/NarrowPeaks.R" ] }, "ncdfFlow": { "Package": "ncdfFlow", "Version": "2.20.2", "Depends": [ "R (>= 2.14.0)", "flowCore(>= 1.37.15)", "RcppArmadillo", "methods", "BH" ], "Imports": [ "Biobase", "BiocGenerics", "flowCore", "flowViz", "zlibbioc" ], "LinkingTo": [ "Rcpp", "RcppArmadillo", "BH" ], "Suggests": [ "testthat", "parallel" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "8d1c9a1a6d0f08c2081f35894ae82b60", "NeedsCompilation": "yes", "Title": "ncdfFlow: A package that provides HDF5 based storage for flow cytometry data.", "Description": "Provides HDF5 storage based methods and functions for manipulation of flow cytometry data.", "biocViews": [ "FlowCytometry", "Software" ], "Author": "Mike Jiang,Greg Finak,N. Gopalakrishnan", "Maintainer": "Mike Jiang ", "SystemRequirements": "hdf5 (>= 1.8.0)", "source.ver": "src/contrib/ncdfFlow_2.20.2.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ncdfFlow_2.20.2.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ncdfFlow_2.20.2.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ncdfFlow_2.20.2.tgz", "vignettes": [ "vignettes/ncdfFlow/inst/doc/ncdfFlow.pdf" ], "vignetteTitles": [ "Basic Functions for Flow Cytometry Data" ], "hasREADME": true, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ncdfFlow/inst/doc/ncdfFlow.R" ], "dependsOnMe": [ "flowStats", "flowWorkspace", "ggcyto", "QUALIFIER" ], "importsMe": [ "CytoML", "openCyto" ], "suggestsMe": [ "COMPASS" ] }, "NCIgraph": { "Package": "NCIgraph", "Version": "1.22.0", "Depends": [ "graph", "R (>= 2.10.0)" ], "Imports": [ "graph", "KEGGgraph", "methods", "RBGL", "RCytoscape", "R.methodsS3" ], "Suggests": [ "Rgraphviz" ], "Enhances": [ "DEGraph" ], "License": "GPL-3", "MD5sum": "e601cb487a84715395f89e886fb45c8c", "NeedsCompilation": "no", "Title": "Pathways from the NCI Pathways Database", "Description": "Provides various methods to load the pathways from the NCI Pathways Database in R graph objects and to re-format them.", "biocViews": [ "GraphAndNetwork", "Pathways", "Software" ], "Author": "Laurent Jacob", "Maintainer": "Laurent Jacob ", "source.ver": "src/contrib/NCIgraph_1.22.0.tar.gz", "vignettes": [ "vignettes/NCIgraph/inst/doc/NCIgraph.pdf" ], "vignetteTitles": [ "NCIgraph: networks from the NCI pathway integrated database as graphNEL objects." ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/NCIgraph/inst/doc/NCIgraph.R" ], "importsMe": [ "DEGraph" ], "suggestsMe": [ "DEGraph" ] }, "nem": { "Package": "nem", "Version": "2.48.0", "Depends": [ "R (>= 3.0)" ], "Imports": [ "boot", "e1071", "graph", "graphics", "grDevices", "methods", "RBGL (>= 1.8.1)", "RColorBrewer", "stats", "utils", "Rgraphviz", "statmod", "plotrix", "limma" ], "Suggests": [ "Biobase (>= 1.10)" ], "Enhances": [ "doMC", "snow", "parallel" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "211076adeab231209e168e3ea98e9d87", "NeedsCompilation": "yes", "Title": "(Dynamic) Nested Effects Models and Deterministic Effects Propagation Networks to reconstruct phenotypic hierarchies", "Description": "The package 'nem' allows to reconstruct features of pathways from the nested structure of perturbation effects. It takes as input (1.) a set of pathway components, which were perturbed, and (2.) phenotypic readout of these perturbations (e.g. gene expression, protein expression). The output is a directed graph representing the phenotypic hierarchy.", "biocViews": [ "Bioinformatics", "GraphsAndNetworks", "Microarray", "NetworkInference", "Pathways", "Software", "SystemsBiology" ], "Author": "Holger Froehlich, Florian Markowetz, Achim Tresch, Theresa Niederberger, Christian Bender, Matthias Maneck, Claudio Lottaz, Tim Beissbarth", "Maintainer": "Holger Froehlich ", "URL": "http://www.bioconductor.org", "source.ver": "src/contrib/nem_2.48.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/nem_2.48.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/nem_2.48.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/nem_2.48.0.tgz", "vignettes": [ "vignettes/nem/inst/doc/markowetz-thesis-2006.pdf", "vignettes/nem/inst/doc/nem.pdf" ], "vignetteTitles": [ "markowetz-thesis-2006.pdf", "Nested Effects Models - An example in Drosophila immune response" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/nem/inst/doc/nem.R" ], "dependsOnMe": [ "lpNet" ], "importsMe": [ "birte" ], "suggestsMe": [ "rBiopaxParser" ] }, "netbenchmark": { "Package": "netbenchmark", "Version": "1.6.0", "Depends": [ "grndata (>= 0.99.3)" ], "Imports": [ "Rcpp (>= 0.11.0)", "minet", "randomForest", "c3net", "PCIT", "GeneNet", "tools", "pracma", "Matrix", "corpcor", "fdrtool" ], "LinkingTo": [ "Rcpp" ], "Suggests": [ "RUnit", "BiocGenerics", "knitr", "graph" ], "License": "CC BY-NC-SA 4.0", "Archs": "i386, x64", "MD5sum": "e2365f1a3b187b27ec013b85dbeebda2", "NeedsCompilation": "yes", "Title": "Benchmarking of several gene network inference methods", "Description": "This package implements a benchmarking of several gene network inference algorithms from gene expression data.", "biocViews": [ "GeneExpression", "GraphAndNetwork", "Microarray", "Network", "NetworkInference", "Software" ], "Author": "Pau Bellot, Catharina Olsen, Patrick Meyer, with contributions from Alexandre Irrthum", "Maintainer": "Pau Bellot ", "URL": "https://imatge.upc.edu/netbenchmark/", "VignetteBuilder": "knitr", "source.ver": "src/contrib/netbenchmark_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/netbenchmark_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/netbenchmark_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/netbenchmark_1.6.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/netbenchmark/inst/doc/netbenchmark.R" ], "htmlDocs": [ "vignettes/netbenchmark/inst/doc/netbenchmark.html" ], "htmlTitles": [ "Netbenchmark" ] }, "netbiov": { "Package": "netbiov", "Version": "1.8.0", "Depends": [ "R (>= 3.1.0)", "igraph (>= 0.7.1)" ], "Suggests": [ "BiocStyle", "RUnit", "BiocGenerics", "Matrix" ], "License": "GPL (>= 2)", "MD5sum": "815385f90799073212b203893c22c786", "NeedsCompilation": "no", "Title": "A package for visualizing complex biological network", "Description": "A package that provides an effective visualization of large biological networks", "biocViews": [ "GraphAndNetwork", "Network", "Software", "Visualization" ], "Author": "Shailesh tripathi and Frank Emmert-Streib", "Maintainer": "Shailesh tripathi ", "URL": "http://www.bio-complexity.com", "source.ver": "src/contrib/netbiov_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/netbiov_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/netbiov_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/netbiov_1.8.0.tgz", "vignettes": [ "vignettes/netbiov/inst/doc/netbiov-intro.pdf" ], "vignetteTitles": [ "netbiov: An R package for visualizing biological networks" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/netbiov/inst/doc/netbiov-intro.R" ] }, "nethet": { "Package": "nethet", "Version": "1.6.0", "Imports": [ "glasso", "mvtnorm", "parcor", "GeneNet", "huge", "CompQuadForm", "ggm", "mclust", "parallel", "GSA", "limma", "multtest", "ICSNP", "glmnet", "network", "ggplot2" ], "Suggests": [ "knitr", "xtable", "BiocStyle" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "2bd48b232c418fc1e4adc0a81977420e", "NeedsCompilation": "yes", "Title": "A bioconductor package for high-dimensional exploration of biological network heterogeneity", "Description": "Package nethet is an implementation of statistical solid methodology enabling the analysis of network heterogeneity from high-dimensional data. It combines several implementations of recent statistical innovations useful for estimation and comparison of networks in a heterogeneous, high-dimensional setting. In particular, we provide code for formal two-sample testing in Gaussian graphical models (differential network and GGM-GSA; Stadler and Mukherjee, 2013, 2014) and make a novel network-based clustering algorithm available (mixed graphical lasso, Stadler and Mukherjee, 2013).", "biocViews": [ "Clustering", "GraphAndNetwork", "Software" ], "Author": "Nicolas Staedler, Frank Dondelinger", "Maintainer": "Nicolas Staedler , Frank Dondelinger ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/nethet_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/nethet_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/nethet_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/nethet_1.6.0.tgz", "vignettes": [ "vignettes/nethet/inst/doc/nethet.pdf" ], "vignetteTitles": [ "nethet" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/nethet/inst/doc/nethet.R" ] }, "NetPathMiner": { "Package": "NetPathMiner", "Version": "1.10.0", "Depends": [ "R (>= 3.0.2)", "igraph (>= 1.0)" ], "Suggests": [ "rBiopaxParser (>= 2.1)", "RCurl", "graph" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "2e9a9f465134f957a666ae8506ff64d0", "NeedsCompilation": "yes", "Title": "NetPathMiner for Biological Network Construction, Path Mining and Visualization", "Description": "NetPathMiner is a general framework for network path mining using genome-scale networks. It constructs networks from KGML, SBML and BioPAX files, providing three network representations, metabolic, reaction and gene representations. NetPathMiner finds active paths and applies machine learning methods to summarize found paths for easy interpretation. It also provides static and interactive visualizations of networks and paths to aid manual investigation.", "biocViews": [ "Classification", "Clustering", "GraphAndNetwork", "Network", "Pathways", "Software" ], "Author": "Ahmed Mohamed , Tim Hancock , Ichigaku Takigawa , Nicolas Wicker ", "Maintainer": "Ahmed Mohamed ", "URL": "https://github.com/ahmohamed/NetPathMiner", "SystemRequirements": "libxml2, libSBML (>= 5.5)", "source.ver": "src/contrib/NetPathMiner_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/NetPathMiner_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/NetPathMiner_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/NetPathMiner_1.10.0.tgz", "vignettes": [ "vignettes/NetPathMiner/inst/doc/NPMVignette.pdf" ], "vignetteTitles": [ "NetPathMiner Vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/NetPathMiner/inst/doc/NPMVignette.R" ] }, "netprioR": { "Package": "netprioR", "Version": "1.0.0", "Depends": [ "methods", "graphics", "R(>= 3.3)" ], "Imports": [ "stats", "Matrix", "dplyr", "doParallel", "foreach", "parallel", "sparseMVN", "ggplot2", "gridExtra", "pROC" ], "Suggests": [ "knitr", "BiocStyle", "pander" ], "License": "GPL-3", "MD5sum": "e61f9cbc5bee818dc86b3355359dd413", "NeedsCompilation": "no", "Title": "A model for network-based prioritisation of genes", "Description": "A model for semi-supervised prioritisation of genes integrating network data, phenotypes and additional prior knowledge about TP and TN gene labels from the literature or experts.", "biocViews": [ "CellBasedAssays", "Network", "Preprocessing", "Software" ], "Author": "Fabian Schmich", "Maintainer": "Fabian Schmich ", "URL": "http://bioconductor.org/packages/netprioR", "VignetteBuilder": "knitr", "source.ver": "src/contrib/netprioR_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/netprioR_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/netprioR_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/netprioR_1.0.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/netprioR/inst/doc/netprioR.R" ], "htmlDocs": [ "vignettes/netprioR/inst/doc/netprioR.html" ], "htmlTitles": [ "netprioR Vignette" ] }, "netresponse": { "Package": "netresponse", "Version": "1.34.0", "Depends": [ "R (>= 2.15.1)", "Rgraphviz", "methods", "minet", "mclust", "reshape2" ], "Imports": [ "dmt", "ggplot2", "graph", "igraph", "parallel", "plyr", "qvalue", "RColorBrewer" ], "License": "GPL (>=2)", "Archs": "i386, x64", "MD5sum": "972f9f024706a81617c85ab7284a935b", "NeedsCompilation": "yes", "Title": "Functional Network Analysis", "Description": "Algorithms for functional network analysis. Includes an implementation of a variational Dirichlet process Gaussian mixture model for nonparametric mixture modeling.", "biocViews": [ "CellBiology", "Clustering", "DifferentialExpression", "GeneExpression", "Genetics", "GraphAndNetwork", "Microarray", "Network", "Software", "Transcription" ], "Author": "Leo Lahti, Olli-Pekka Huovilainen, Antonio Gusmao and Juuso Parkkinen", "Maintainer": "Leo Lahti ", "URL": "https://github.com/antagomir/netresponse", "BugReports": "https://github.com/antagomir/netresponse/issues", "source.ver": "src/contrib/netresponse_1.34.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/netresponse_1.34.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/netresponse_1.34.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/netresponse_1.34.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false }, "NetSAM": { "Package": "NetSAM", "Version": "1.14.0", "Depends": [ "R (>= 2.15.1)", "methods", "igraph (>= 0.6-1)", "seriation (>= 1.0-6)", "graph (>= 1.34.0)" ], "Imports": [ "methods" ], "Suggests": [ "RUnit", "BiocGenerics" ], "License": "LGPL", "MD5sum": "702881ffe6e23baf54938da4441236c2", "NeedsCompilation": "no", "Title": "Network Seriation And Modularization", "Description": "The NetSAM (Network Seriation and Modularization) package takes an edge-list representation of a network as an input, performs network seriation and modularization analysis, and generates as files that can be used as an input for the one-dimensional network visualization tool NetGestalt (http://www.netgestalt.org) or other network analysis.", "biocViews": [ "Network", "Software", "Visualization" ], "Author": "Jing Wang ", "Maintainer": "Bing Zhang ", "source.ver": "src/contrib/NetSAM_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/NetSAM_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/NetSAM_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/NetSAM_1.14.0.tgz", "vignettes": [ "vignettes/NetSAM/inst/doc/NetSAM.pdf" ], "vignetteTitles": [ "NetSAM" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/NetSAM/inst/doc/NetSAM.R" ] }, "networkBMA": { "Package": "networkBMA", "Version": "2.12.0", "Depends": [ "R (>= 2.15.0)", "stats", "utils", "BMA", "Rcpp (>= 0.10.3)", "RcppArmadillo (>= 0.3.810.2)", "RcppEigen (>= 0.3.1.2.1)" ], "LinkingTo": [ "Rcpp", "RcppArmadillo", "RcppEigen", "BH" ], "License": "GPL (>= 2)", "MD5sum": "3cc64ad9398849a6a28c4012c6a63ca3", "NeedsCompilation": "yes", "Title": "Regression-based network inference using Bayesian Model Averaging", "Description": "An extension of Bayesian Model Averaging (BMA) for network construction using time series gene expression data. Includes assessment functions and sample test data.", "biocViews": [ "Bayesian", "GeneExpression", "GeneTarget", "GraphsAndNetwork", "Network", "NetworkInference", "Software" ], "Author": "Chris Fraley, Wm. Chad Young, Ling-Hong Hung, Kaiyuan Shi, Ka Yee Yeung, Adrian Raftery (with contributions from Kenneth Lo)", "Maintainer": "Ka Yee Yeung ", "source.ver": "src/contrib/networkBMA_2.12.0.tar.gz", "vignettes": [ "vignettes/networkBMA/inst/doc/networkBMA.pdf" ], "vignetteTitles": [ "networkBMA" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/networkBMA/inst/doc/networkBMA.R" ], "suggestsMe": [ "DREAM4" ] }, "NGScopy": { "Package": "NGScopy", "Version": "1.8.0", "Depends": [ "R (>= 3.1.0)" ], "Imports": [ "methods", "parallel", "Xmisc (>= 0.2.1)", "rbamtools (>= 2.6.0)", "changepoint (>= 2.1.1)" ], "Suggests": [ "RUnit", "NGScopyData", "GenomicRanges" ], "License": "GPL (>=2)", "MD5sum": "e3aaa4877488b30ce248386f6452d51f", "NeedsCompilation": "no", "Title": "NGScopy: Detection of Copy Number Variations in Next Generation Sequencing sequencing", "Description": "NGScopy provides a quantitative caller for detecting copy number variations in next generation sequencing (NGS), including whole genome sequencing (WGS), whole exome sequencing (WES) and targeted panel sequencing (TPS). The caller can be parallelized by chromosomes to use multiple processors/cores on one computer.", "biocViews": [ "CopyNumberVariation", "DNASeq", "ExomeSeq", "Sequencing", "Software", "TargetedResequencing", "WholeGenome" ], "Author": "Xiaobei Zhao [aut, cre, cph]", "Maintainer": "Xiaobei Zhao ", "source.ver": "src/contrib/NGScopy_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/NGScopy_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/NGScopy_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/NGScopy_1.8.0.tgz", "vignettes": [ "vignettes/NGScopy/inst/doc/NGScopy-vignette.pdf" ], "vignetteTitles": [ "NGScopy: Detection of copy number variations in next generation sequencing (User's Guide)" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/NGScopy/inst/doc/NGScopy-vignette.R" ] }, "nnNorm": { "Package": "nnNorm", "Version": "2.38.0", "Depends": [ "R(>= 2.2.0)", "marray" ], "Imports": [ "graphics", "grDevices", "marray", "methods", "nnet", "stats" ], "License": "LGPL", "MD5sum": "f083aec7899451513af949882fa0d3f5", "NeedsCompilation": "no", "Title": "Spatial and intensity based normalization of cDNA microarray data based on robust neural nets", "Description": "This package allows to detect and correct for spatial and intensity biases with two-channel microarray data. The normalization method implemented in this package is based on robust neural networks fitting.", "biocViews": [ "Microarray", "Preprocessing", "Software", "TwoChannel" ], "Author": "Adi Laurentiu Tarca ", "Maintainer": "Adi Laurentiu Tarca ", "URL": "http://bioinformaticsprb.med.wayne.edu/tarca/", "source.ver": "src/contrib/nnNorm_2.38.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/nnNorm_2.38.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/nnNorm_2.38.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/nnNorm_2.38.0.tgz", "vignettes": [ "vignettes/nnNorm/inst/doc/nnNorm.pdf" ], "vignetteTitles": [ "nnNorm Tutorial" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/nnNorm/inst/doc/nnNorm.R" ] }, "NOISeq": { "Package": "NOISeq", "Version": "2.18.0", "Depends": [ "R (>= 2.13.0)", "methods", "Biobase (>= 2.13.11)", "splines (>= 3.0.1)", "Matrix (>= 1.2)" ], "License": "Artistic-2.0", "MD5sum": "d74de38f0369b58c3e203f29e8a64f3c", "NeedsCompilation": "no", "Title": "Exploratory analysis and differential expression for RNA-seq data", "Description": "Analysis of RNA-seq expression data or other similar kind of data. Exploratory plots to evualuate saturation, count distribution, expression per chromosome, type of detected features, features length, etc. Differential expression between two experimental conditions with no parametric assumptions.", "biocViews": [ "DifferentialExpression", "RNASeq", "Sequencing", "Software", "Visualization" ], "Author": "Sonia Tarazona, Pedro Furio-Tari, Maria Jose Nueda, Alberto Ferrer and Ana Conesa", "Maintainer": "Sonia Tarazona ", "source.ver": "src/contrib/NOISeq_2.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/NOISeq_2.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/NOISeq_2.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/NOISeq_2.18.0.tgz", "vignettes": [ "vignettes/NOISeq/inst/doc/NOISeq.pdf", "vignettes/NOISeq/inst/doc/QCreport.pdf" ], "vignetteTitles": [ "NOISeq User's Guide", "QCreport.pdf" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/NOISeq/inst/doc/NOISeq.R" ], "dependsOnMe": [ "metaSeq" ], "importsMe": [ "CNVPanelizer", "metaseqR" ], "suggestsMe": [ "compcodeR" ] }, "nondetects": { "Package": "nondetects", "Version": "2.4.0", "Depends": [ "R (>= 3.2)", "Biobase (>= 2.22.0)" ], "Imports": [ "limma", "mvtnorm", "utils", "methods", "HTqPCR (>= 1.16.0)" ], "Suggests": [ "BiocStyle (>= 1.0.0)", "RUnit", "BiocGenerics (>= 0.8.0)" ], "License": "GPL-3", "MD5sum": "a0dd707178bca5579400a4a3b0af32d2", "NeedsCompilation": "no", "Title": "Non-detects in qPCR data", "Description": "Methods to model and impute non-detects in the results of qPCR experiments.", "biocViews": [ "AssayDomain", "GeneExpression", "Preprocessing", "Software", "Technology", "WorkflowStep", "qPCR" ], "Author": "Matthew N. McCall , Valeriia Sherina ", "Maintainer": "Valeriia Sherina ", "source.ver": "src/contrib/nondetects_2.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/nondetects_2.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/nondetects_2.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/nondetects_2.4.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false }, "normalize450K": { "Package": "normalize450K", "Version": "1.2.0", "Depends": [ "R (>= 3.3)", "Biobase", "illuminaio", "quadprog" ], "Imports": [ "utils" ], "License": "BSD_2_clause + file LICENSE", "MD5sum": "4a11fd0b3a0feffa237df435400eca1a", "NeedsCompilation": "no", "Title": "Preprocessing of Illumina Infinium 450K data", "Description": "Precise measurements are important for epigenome-wide studies investigating DNA methylation in whole blood samples, where effect sizes are expected to be small in magnitude. The 450K platform is often affected by batch effects and proper preprocessing is recommended. This package provides functions to read and normalize 450K '.idat' files. The normalization corrects for dye bias and biases related to signal intensity and methylation of probes using local regression. No adjustment for probe type bias is performed to avoid the trade-off of precision for accuracy of beta-values.", "biocViews": [ "DNAMethylation", "MethylationArray", "Microarray", "Normalization", "Preprocessing", "Software", "TwoChannel" ], "Author": "Jonathan Alexander Heiss", "Maintainer": "Jonathan Alexander Heiss ", "source.ver": "src/contrib/normalize450K_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/normalize450K_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/normalize450K_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/normalize450K_1.2.0.tgz", "vignettes": [ "vignettes/normalize450K/inst/doc/read_and_normalize450K.pdf" ], "vignetteTitles": [ "Normalization of 450K data" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/normalize450K/inst/doc/read_and_normalize450K.R" ] }, "NormqPCR": { "Package": "NormqPCR", "Version": "1.20.0", "Depends": [ "R(>= 2.14.0)", "stats", "RColorBrewer", "Biobase", "methods", "ReadqPCR", "qpcR" ], "License": "LGPL-3", "MD5sum": "2422b3e8a7da417f13d9532676e24268", "NeedsCompilation": "no", "Title": "Functions for normalisation of RT-qPCR data", "Description": "Functions for the selection of optimal reference genes and the normalisation of real-time quantitative PCR data.", "biocViews": [ "GeneExpression", "MicrotitrePlateAssay", "Software", "qPCR" ], "Author": "Matthias Kohl, James Perkins, Nor Izayu Abdul Rahman", "Maintainer": "James Perkins ", "URL": "www.bioconductor.org/packages/release/bioc/html/NormqPCR.html", "source.ver": "src/contrib/NormqPCR_1.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/NormqPCR_1.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/NormqPCR_1.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/NormqPCR_1.20.0.tgz", "vignettes": [ "vignettes/NormqPCR/inst/doc/NormqPCR.pdf" ], "vignetteTitles": [ "NormqPCR: Functions for normalisation of RT-qPCR data" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/NormqPCR/inst/doc/NormqPCR.R" ] }, "normr": { "Package": "normr", "Version": "1.0.0", "Depends": [ "R (>= 3.3.0)" ], "Imports": [ "methods", "stats", "utils", "grDevices", "parallel", "GenomeInfoDb", "GenomicRanges", "IRanges", "Rcpp (>= 0.11)", "qvalue (>= 2.2)", "bamsignals (>= 1.4)", "rtracklayer (>= 1.32)" ], "LinkingTo": [ "Rcpp" ], "Suggests": [ "BiocStyle", "testthat (>= 1.0)", "knitr", "rmarkdown" ], "Enhances": [ "BiocParallel" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "bb3f586b5a97d3cde4839706d878d355", "NeedsCompilation": "yes", "Title": "Normalization and difference calling in ChIP-seq data", "Description": "Robust normalization and difference calling procedures for ChIP-seq and alike data. Read counts are modeled jointly as a binomial mixture model with a user-specified number of components. A fitted background estimate accounts for the effect of enrichment in certain regions and, therefore, represents an appropriate null hypothesis. This robust background is used to identify significantly enriched or depleted regions.", "biocViews": [ "Alignment", "Bayesian", "ChIPSeq", "Classification", "DataImport", "DifferentialPeakCalling", "FunctionalGenomics", "Genetics", "MultipleComparison", "Normalization", "PeakDetection", "Preprocessing", "RIPSeq", "Software" ], "Author": "Johannes Helmuth [aut, cre], Ho-Ryun Chung [aut]", "Maintainer": "Johannes Helmuth ", "URL": "https://github.com/your-highness/normR", "SystemRequirements": "C++11", "VignetteBuilder": "knitr", "BugReports": "https://github.com/your-highness/normR/issues", "source.ver": "src/contrib/normr_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/normr_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/normr_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/normr_1.0.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/normr/inst/doc/normr.R" ], "htmlDocs": [ "vignettes/normr/inst/doc/normr.html" ], "htmlTitles": [ "Introduction to the normR package" ] }, "npGSEA": { "Package": "npGSEA", "Version": "1.10.0", "Depends": [ "GSEABase (>= 1.24.0)" ], "Imports": [ "Biobase", "methods", "BiocGenerics", "graphics", "stats" ], "Suggests": [ "ALL", "genefilter", "limma", "hgu95av2.db", "ReportingTools", "BiocStyle" ], "License": "Artistic-2.0", "MD5sum": "1bc54a59fa447bb81c9499800da6b45c", "NeedsCompilation": "no", "Title": "Permutation approximation methods for gene set enrichment analysis (non-permutation GSEA)", "Description": "Current gene set enrichment methods rely upon permutations for inference. These approaches are computationally expensive and have minimum achievable p-values based on the number of permutations, not on the actual observed statistics. We have derived three parametric approximations to the permutation distributions of two gene set enrichment test statistics. We are able to reduce the computational burden and granularity issues of permutation testing with our method, which is implemented in this package. npGSEA calculates gene set enrichment statistics and p-values without the computational cost of permutations. It is applicable in settings where one or many gene sets are of interest. There are also built-in plotting functions to help users visualize results.", "biocViews": [ "GeneSetEnrichment", "Microarray", "Pathways", "Software", "StatisticalMethod" ], "Author": "Jessica Larson and Art Owen", "Maintainer": "Jessica Larson ", "source.ver": "src/contrib/npGSEA_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/npGSEA_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/npGSEA_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/npGSEA_1.10.0.tgz", "vignettes": [ "vignettes/npGSEA/inst/doc/npGSEA.pdf" ], "vignetteTitles": [ "Running gene set enrichment analysis with the \"npGSEA\" package" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/npGSEA/inst/doc/npGSEA.R" ] }, "NTW": { "Package": "NTW", "Version": "1.24.0", "Depends": [ "R (>= 2.3.0)" ], "Imports": [ "mvtnorm", "stats", "utils" ], "License": "GPL-2", "MD5sum": "4a957b7450c2c4166ce8de58d61b0745", "NeedsCompilation": "no", "Title": "Predict gene network using an Ordinary Differential Equation (ODE) based method", "Description": "This package predicts the gene-gene interaction network and identifies the direct transcriptional targets of the perturbation using an ODE (Ordinary Differential Equation) based method.", "biocViews": [ "Preprocessing", "Software" ], "Author": "Wei Xiao, Yin Jin, Darong Lai, Xinyi Yang, Yuanhua Liu, Christine Nardini", "Maintainer": "Yuanhua Liu ", "source.ver": "src/contrib/NTW_1.24.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/NTW_1.24.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/NTW_1.24.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/NTW_1.24.0.tgz", "vignettes": [ "vignettes/NTW/inst/doc/NTW.pdf" ], "vignetteTitles": [ "NTW vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/NTW/inst/doc/NTW.R" ] }, "nucleoSim": { "Package": "nucleoSim", "Version": "1.2.0", "Imports": [ "stats", "IRanges", "S4Vectors", "graphics" ], "Suggests": [ "BiocStyle", "BiocGenerics", "knitr", "rmarkdown", "RUnit" ], "License": "Artistic-2.0", "MD5sum": "30881db014ec8bcc16dc816aa51c59c6", "NeedsCompilation": "no", "Title": "Generate synthetic nucleosome maps", "Description": "This package can generate a synthetic map with reads covering the nucleosome regions as well as a synthetic map with forward and reverse reads emulating next-generation sequencing. The user has choice between three different distributions for the read positioning: Normal, Student and Uniform.", "biocViews": [ "Alignment", "Genetics", "Sequencing", "Software", "StatisticalMethod" ], "Author": "Rawane Samb [aut], Astrid Deschênes [cre, aut], Pascal Belleau [aut], Arnaud Droit [aut]", "Maintainer": "Astrid Deschenes ", "URL": "https://github.com/arnauddroitlab/nucleoSim", "VignetteBuilder": "knitr", "BugReports": "https://github.com/arnauddroitlab/nucleoSim/issues", "source.ver": "src/contrib/nucleoSim_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/nucleoSim_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/nucleoSim_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/nucleoSim_1.2.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/nucleoSim/inst/doc/nucleoSim.R" ], "htmlDocs": [ "vignettes/nucleoSim/inst/doc/nucleoSim.html" ], "htmlTitles": [ "Generate synthetic nucleosome maps" ] }, "nucleR": { "Package": "nucleR", "Version": "2.6.0", "Depends": [ "ShortRead" ], "Imports": [ "methods", "BiocGenerics", "S4Vectors (>= 0.9.39)", "IRanges (>= 2.5.27)", "Biobase", "GenomicRanges (>= 1.23.16)", "Rsamtools", "stats", "graphics", "parallel" ], "Suggests": [ "Starr" ], "License": "LGPL (>= 3)", "MD5sum": "d5065004a00f49775237a4041db50e5c", "NeedsCompilation": "no", "Title": "Nucleosome positioning package for R", "Description": "Nucleosome positioning for Tiling Arrays and NGS experiments.", "biocViews": [ "ChIPSeq", "Genetics", "Microarray", "Sequencing", "Software" ], "Author": "Oscar Flores, Ricard Illa", "Maintainer": "Ricard Illa ", "source.ver": "src/contrib/nucleR_2.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/nucleR_2.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/nucleR_2.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/nucleR_2.6.0.tgz", "vignettes": [ "vignettes/nucleR/inst/doc/nucleR.pdf" ], "vignetteTitles": [ "nucleR" ], "hasREADME": true, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/nucleR/inst/doc/nucleR.R" ] }, "nudge": { "Package": "nudge", "Version": "1.40.0", "Imports": [ "stats" ], "License": "GPL-2", "MD5sum": "09a6719e5a95a294725d3c7057edd15a", "NeedsCompilation": "no", "Title": "Normal Uniform Differential Gene Expression detection", "Description": "Package for normalizing microarray data in single and multiple replicate experiments and fitting a normal-uniform mixture to detect differentially expressed genes in the cases where the two samples are being compared directly or indirectly (via a common reference sample)", "biocViews": [ "DifferentialExpression", "Microarray", "Software", "TwoChannel" ], "Author": "N. Dean and A. E. Raftery ", "Maintainer": "N. Dean ", "source.ver": "src/contrib/nudge_1.40.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/nudge_1.40.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/nudge_1.40.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/nudge_1.40.0.tgz", "vignettes": [ "vignettes/nudge/inst/doc/nudge.vignette.pdf" ], "vignetteTitles": [ "nudge Overview" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/nudge/inst/doc/nudge.vignette.R" ] }, "NuPoP": { "Package": "NuPoP", "Version": "1.24.0", "Depends": [ "R (>= 2.10)" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "8ae3986a78c250dfd442961ee0f45d58", "NeedsCompilation": "yes", "Title": "An R package for nucleosome positioning prediction", "Description": "NuPoP is an R package for Nucleosome Positioning Prediction.This package is built upon a duration hidden Markov model proposed in Xi et al, 2010; Wang et al, 2008. The core of the package was written in Fotran. In addition to the R package, a stand-alone Fortran software tool is also available at http://nucleosome.stats.northwestern.edu.", "biocViews": [ "Classification", "Genetics", "Software", "Visualization" ], "Author": "Ji-Ping Wang ; Liqun Xi ", "Maintainer": "Ji-Ping Wang", "source.ver": "src/contrib/NuPoP_1.24.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/NuPoP_1.24.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/NuPoP_1.24.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/NuPoP_1.24.0.tgz", "vignettes": [ "vignettes/NuPoP/inst/doc/NuPoP-intro.pdf" ], "vignetteTitles": [ "An R package for Nucleosome positioning prediction" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/NuPoP/inst/doc/NuPoP-intro.R" ] }, "occugene": { "Package": "occugene", "Version": "1.34.0", "Depends": [ "R (>= 2.0.0)" ], "License": "GPL (>= 2)", "MD5sum": "dcd88a730e874e456818967f18b7771e", "NeedsCompilation": "no", "Title": "Functions for Multinomial Occupancy Distribution", "Description": "Statistical tools for building random mutagenesis libraries for prokaryotes. The package has functions for handling the occupancy distribution for a multinomial and for estimating the number of essential genes in random transposon mutagenesis libraries.", "biocViews": [ "Annotation", "Pathways", "Software" ], "Author": "Oliver Will ", "Maintainer": "Oliver Will ", "source.ver": "src/contrib/occugene_1.34.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/occugene_1.34.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/occugene_1.34.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/occugene_1.34.0.tgz", "vignettes": [ "vignettes/occugene/inst/doc/occugene.pdf" ], "vignetteTitles": [ "occugene" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/occugene/inst/doc/occugene.R" ] }, "OCplus": { "Package": "OCplus", "Version": "1.48.2", "Depends": [ "R (>= 2.1.0)", "akima" ], "Imports": [ "multtest (>= 1.7.3)", "graphics", "grDevices", "stats" ], "License": "LGPL", "MD5sum": "c3c381158ee35512a0a4947f9dd9ff31", "NeedsCompilation": "no", "Title": "Operating characteristics plus sample size and local fdr for microarray experiments", "Description": "This package allows to characterize the operating characteristics of a microarray experiment, i.e. the trade-off between false discovery rate and the power to detect truly regulated genes. The package includes tools both for planned experiments (for sample size assessment) and for already collected data (identification of differentially expressed genes).", "biocViews": [ "DifferentialExpression", "Microarray", "MultipleComparison", "Software" ], "Author": "Yudi Pawitan and Alexander Ploner ", "Maintainer": "Alexander Ploner ", "source.ver": "src/contrib/OCplus_1.48.2.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/OCplus_1.48.2.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/OCplus_1.48.2.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/OCplus_1.48.2.tgz", "vignettes": [ "vignettes/OCplus/inst/doc/OCplus.pdf" ], "vignetteTitles": [ "OCplus Introduction" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/OCplus/inst/doc/OCplus.R" ] }, "odseq": { "Package": "odseq", "Version": "1.2.0", "Depends": [ "R (>= 3.2.3)" ], "Imports": [ "msa (>= 1.2.1)", "kebabs (>= 1.4.1)", "mclust (>= 5.1)" ], "Suggests": [ "knitr(>= 1.11)" ], "License": "MIT + file LICENSE", "MD5sum": "ef7b17e2ae4198437bc263c7af48d2fa", "NeedsCompilation": "no", "Title": "Outlier detection in multiple sequence alignments", "Description": "Performs outlier detection of sequences in a multiple sequence alignment using bootstrap of predefined distance metrics. Outlier sequences can make downstream analyses unreliable or make the alignments less accurate while they are being constructed. This package implements the OD-seq algorithm proposed by Jehl et al (doi 10.1186/s12859-015-0702-1) for aligned sequences and a variant using string kernels for unaligned sequences.", "biocViews": [ "Alignment", "MultipleSequenceAlignment", "Software" ], "Author": "José Jiménez", "Maintainer": "José Jiménez ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/odseq_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/odseq_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/odseq_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/odseq_1.2.0.tgz", "vignettes": [ "vignettes/odseq/inst/doc/vignette.pdf" ], "vignetteTitles": [ "A quick tutorial to outlier detection in MSAs" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/odseq/inst/doc/vignette.R" ] }, "OGSA": { "Package": "OGSA", "Version": "1.4.0", "Depends": [ "R (>= 3.2.0)" ], "Imports": [ "gplots(>= 2.8.0)", "limma(>= 3.18.13)", "Biobase" ], "License": "GPL (== 2)", "MD5sum": "7a3f82125a43ffbaa3fb01ef42574e61", "NeedsCompilation": "no", "Title": "Outlier Gene Set Analysis", "Description": "OGSA provides a global estimate of pathway deregulation in cancer subtypes by integrating the estimates of significance for individual pathway members that have been identified by outlier analysis.", "biocViews": [ "CopyNumberVariation", "GeneExpression", "Microarray", "Software" ], "Author": "Michael F. Ochs ", "Maintainer": "Michael F. Ochs ", "source.ver": "src/contrib/OGSA_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/OGSA_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/OGSA_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/OGSA_1.4.0.tgz", "vignettes": [ "vignettes/OGSA/inst/doc/OGSAUsersManual.pdf" ], "vignetteTitles": [ "OGSA Users Manual" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/OGSA/inst/doc/OGSAUsersManual.R" ] }, "oligo": { "Package": "oligo", "Version": "1.38.0", "Depends": [ "R (>= 3.2.0)", "BiocGenerics (>= 0.13.11)", "oligoClasses (>= 1.29.6)", "Biobase (>= 2.27.3)", "Biostrings (>= 2.35.12)" ], "Imports": [ "affyio (>= 1.35.0)", "affxparser (>= 1.39.4)", "DBI (>= 0.3.1)", "ff", "graphics", "methods", "preprocessCore (>= 1.29.0)", "RSQLite (>= 1.0.0)", "splines", "stats", "stats4", "utils", "zlibbioc" ], "LinkingTo": [ "preprocessCore" ], "Suggests": [ "BSgenome.Hsapiens.UCSC.hg18", "hapmap100kxba", "pd.hg.u95av2", "pd.mapping50k.xba240", "pd.huex.1.0.st.v2", "pd.hg18.60mer.expr", "pd.hugene.1.0.st.v1", "maqcExpression4plex", "genefilter", "limma", "RColorBrewer", "oligoData", "BiocStyle", "knitr", "RUnit", "biomaRt", "AnnotationDbi", "GenomeGraphs", "RCurl", "ACME", "biomaRt", "AnnotationDbi", "GenomeGraphs", "RCurl" ], "Enhances": [ "ff", "doMC", "doMPI" ], "License": "LGPL (>= 2)", "Archs": "i386, x64", "MD5sum": "e5c5c9ec8777a6ec8a232fc63fc7d9b5", "NeedsCompilation": "yes", "Title": "Preprocessing tools for oligonucleotide arrays", "Description": "A package to analyze oligonucleotide arrays (expression/SNP/tiling/exon) at probe-level. It currently supports Affymetrix (CEL files) and NimbleGen arrays (XYS files).", "biocViews": [ "DataImport", "DifferentialExpression", "ExonArray", "GeneExpression", "Microarray", "OneChannel", "Preprocessing", "SNP", "Software", "TwoChannel" ], "Author": "Benilton Carvalho and Rafael Irizarry", "Maintainer": "Benilton Carvalho ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/oligo_1.38.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/oligo_1.38.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/oligo_1.38.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/oligo_1.38.0.tgz", "vignettes": [ "vignettes/oligo/inst/doc/oug.pdf" ], "vignetteTitles": [ "oligo User's Guide" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "dependsOnMe": [ "ITALICS", "oligoData", "pd.081229.hg18.promoter.medip.hx1", "pd.2006.07.18.hg18.refseq.promoter", "pd.2006.07.18.mm8.refseq.promoter", "pd.2006.10.31.rn34.refseq.promoter", "pd.ag", "pd.aragene.1.0.st", "pd.aragene.1.1.st", "pd.atdschip.tiling", "pd.ath1.121501", "pd.barley1", "pd.bovgene.1.0.st", "pd.bovgene.1.1.st", "pd.bovine", "pd.bsubtilis", "pd.cangene.1.0.st", "pd.cangene.1.1.st", "pd.canine", "pd.canine.2", "pd.celegans", "pd.charm.hg18.example", "pd.chicken", "pd.chigene.1.0.st", "pd.chigene.1.1.st", "pd.chogene.2.0.st", "pd.chogene.2.1.st", "pd.citrus", "pd.clariom.d.human", "pd.clariom.s.human", "pd.clariom.s.human.ht", "pd.clariom.s.mouse", "pd.clariom.s.mouse.ht", "pd.clariom.s.rat", "pd.clariom.s.rat.ht", "pd.cotton", "pd.cyngene.1.0.st", "pd.cyngene.1.1.st", "pd.cyrgene.1.0.st", "pd.cyrgene.1.1.st", "pd.cytogenetics.array", "pd.drogene.1.0.st", "pd.drogene.1.1.st", "pd.drosgenome1", "pd.drosophila.2", "pd.e.coli.2", "pd.ecoli", "pd.ecoli.asv2", "pd.elegene.1.0.st", "pd.elegene.1.1.st", "pd.equgene.1.0.st", "pd.equgene.1.1.st", "pd.feinberg.hg18.me.hx1", "pd.feinberg.mm8.me.hx1", "pd.felgene.1.0.st", "pd.felgene.1.1.st", "pd.fingene.1.0.st", "pd.fingene.1.1.st", "pd.genomewidesnp.5", "pd.genomewidesnp.6", "pd.guigene.1.0.st", "pd.guigene.1.1.st", "pd.hc.g110", "pd.hg.focus", "pd.hg.u133.plus.2", "pd.hg.u133a", "pd.hg.u133a.2", "pd.hg.u133a.tag", "pd.hg.u133b", "pd.hg.u219", "pd.hg.u95a", "pd.hg.u95av2", "pd.hg.u95b", "pd.hg.u95c", "pd.hg.u95d", "pd.hg.u95e", "pd.hg18.60mer.expr", "pd.ht.hg.u133.plus.pm", "pd.ht.hg.u133a", "pd.ht.mg.430a", "pd.hta.2.0", "pd.hu6800", "pd.huex.1.0.st.v2", "pd.hugene.1.0.st.v1", "pd.hugene.1.1.st.v1", "pd.hugene.2.0.st", "pd.hugene.2.1.st", "pd.maize", "pd.mapping250k.nsp", "pd.mapping250k.sty", "pd.mapping50k.hind240", "pd.mapping50k.xba240", "pd.margene.1.0.st", "pd.margene.1.1.st", "pd.medgene.1.0.st", "pd.medgene.1.1.st", "pd.medicago", "pd.mg.u74a", "pd.mg.u74av2", "pd.mg.u74b", "pd.mg.u74bv2", "pd.mg.u74c", "pd.mg.u74cv2", "pd.mirna.1.0", "pd.mirna.2.0", "pd.mirna.3.0", "pd.mirna.3.1", "pd.mirna.4.0", "pd.moe430a", "pd.moe430b", "pd.moex.1.0.st.v1", "pd.mogene.1.0.st.v1", "pd.mogene.1.1.st.v1", "pd.mogene.2.0.st", "pd.mogene.2.1.st", "pd.mouse430.2", "pd.mouse430a.2", "pd.mta.1.0", "pd.mu11ksuba", "pd.mu11ksubb", "pd.nugo.hs1a520180", "pd.nugo.mm1a520177", "pd.ovigene.1.0.st", "pd.ovigene.1.1.st", "pd.pae.g1a", "pd.plasmodium.anopheles", "pd.poplar", "pd.porcine", "pd.porgene.1.0.st", "pd.porgene.1.1.st", "pd.rabgene.1.0.st", "pd.rabgene.1.1.st", "pd.rae230a", "pd.rae230b", "pd.raex.1.0.st.v1", "pd.ragene.1.0.st.v1", "pd.ragene.1.1.st.v1", "pd.ragene.2.0.st", "pd.ragene.2.1.st", "pd.rat230.2", "pd.rcngene.1.0.st", "pd.rcngene.1.1.st", "pd.rg.u34a", "pd.rg.u34b", "pd.rg.u34c", "pd.rhegene.1.0.st", "pd.rhegene.1.1.st", "pd.rhesus", "pd.rice", "pd.rjpgene.1.0.st", "pd.rjpgene.1.1.st", "pd.rn.u34", "pd.rta.1.0", "pd.rusgene.1.0.st", "pd.rusgene.1.1.st", "pd.s.aureus", "pd.soybean", "pd.soygene.1.0.st", "pd.soygene.1.1.st", "pd.sugar.cane", "pd.tomato", "pd.u133.x3p", "pd.vitis.vinifera", "pd.wheat", "pd.x.laevis.2", "pd.x.tropicalis", "pd.xenopus.laevis", "pd.yeast.2", "pd.yg.s98", "pd.zebgene.1.0.st", "pd.zebgene.1.1.st", "pd.zebrafish", "pdInfoBuilder", "puma", "pumadata", "SCAN.UPC", "waveTiling" ], "importsMe": [ "ArrayExpress", "charm", "cn.farms", "crossmeta", "frma", "ITALICS" ], "suggestsMe": [ "BiocGenerics", "fastseg", "frmaTools", "hapmap100khind", "hapmap100kxba", "hapmap500knsp", "hapmap500ksty", "hapmapsnp5", "hapmapsnp6", "maqcExpression4plex" ] }, "oligoClasses": { "Package": "oligoClasses", "Version": "1.36.0", "Depends": [ "R (>= 2.14)" ], "Imports": [ "BiocGenerics (>= 0.3.2)", "Biobase (>= 2.17.8)", "methods", "graphics", "IRanges (>= 2.5.17)", "GenomicRanges (>= 1.23.7)", "SummarizedExperiment", "Biostrings (>= 2.23.6)", "affyio (>= 1.23.2)", "ff", "foreach", "BiocInstaller", "utils", "S4Vectors (>= 0.9.25)", "RSQLite" ], "Suggests": [ "hapmapsnp5", "hapmapsnp6", "pd.genomewidesnp.6", "pd.genomewidesnp.5", "pd.mapping50k.hind240", "pd.mapping50k.xba240", "pd.mapping250k.sty", "pd.mapping250k.nsp", "genomewidesnp6Crlmm (>= 1.0.7)", "genomewidesnp5Crlmm (>= 1.0.6)", "RUnit", "human370v1cCrlmm", "SNPchip", "VanillaICE", "crlmm" ], "Enhances": [ "doMC", "doMPI", "doSNOW", "doParallel", "doRedis" ], "License": "GPL (>= 2)", "MD5sum": "306c4d806fb6fbc85474acfe596f14c1", "NeedsCompilation": "no", "Title": "Classes for high-throughput arrays supported by oligo and crlmm", "Description": "This package contains class definitions, validity checks, and initialization methods for classes used by the oligo and crlmm packages.", "biocViews": [ "Infrastructure", "Software" ], "Author": "Benilton Carvalho and Robert Scharpf", "Maintainer": "Benilton Carvalho and Robert Scharpf ", "source.ver": "src/contrib/oligoClasses_1.36.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/oligoClasses_1.36.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/oligoClasses_1.36.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/oligoClasses_1.36.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "dependsOnMe": [ "cn.farms", "crlmm", "mBPCR", "oligo", "pd.081229.hg18.promoter.medip.hx1", "pd.2006.07.18.hg18.refseq.promoter", "pd.2006.07.18.mm8.refseq.promoter", "pd.2006.10.31.rn34.refseq.promoter", "pd.ag", "pd.aragene.1.0.st", "pd.aragene.1.1.st", "pd.atdschip.tiling", "pd.ath1.121501", "pd.barley1", "pd.bovgene.1.0.st", "pd.bovgene.1.1.st", "pd.bovine", "pd.bsubtilis", "pd.cangene.1.0.st", "pd.cangene.1.1.st", "pd.canine", "pd.canine.2", "pd.celegans", "pd.charm.hg18.example", "pd.chicken", "pd.chigene.1.0.st", "pd.chigene.1.1.st", "pd.chogene.2.0.st", "pd.chogene.2.1.st", "pd.citrus", "pd.clariom.d.human", "pd.clariom.s.human", "pd.clariom.s.human.ht", "pd.clariom.s.mouse", "pd.clariom.s.mouse.ht", "pd.clariom.s.rat", "pd.clariom.s.rat.ht", "pd.cotton", "pd.cyngene.1.0.st", "pd.cyngene.1.1.st", "pd.cyrgene.1.0.st", "pd.cyrgene.1.1.st", "pd.cytogenetics.array", "pd.drogene.1.0.st", "pd.drogene.1.1.st", "pd.drosgenome1", "pd.drosophila.2", "pd.e.coli.2", "pd.ecoli", "pd.ecoli.asv2", "pd.elegene.1.0.st", "pd.elegene.1.1.st", "pd.equgene.1.0.st", "pd.equgene.1.1.st", "pd.feinberg.hg18.me.hx1", "pd.feinberg.mm8.me.hx1", "pd.felgene.1.0.st", "pd.felgene.1.1.st", "pd.fingene.1.0.st", "pd.fingene.1.1.st", "pd.genomewidesnp.5", "pd.genomewidesnp.6", "pd.guigene.1.0.st", "pd.guigene.1.1.st", "pd.hc.g110", "pd.hg.focus", "pd.hg.u133.plus.2", "pd.hg.u133a", "pd.hg.u133a.2", "pd.hg.u133a.tag", "pd.hg.u133b", "pd.hg.u219", "pd.hg.u95a", "pd.hg.u95av2", "pd.hg.u95b", "pd.hg.u95c", "pd.hg.u95d", "pd.hg.u95e", "pd.hg18.60mer.expr", "pd.ht.hg.u133.plus.pm", "pd.ht.hg.u133a", "pd.ht.mg.430a", "pd.hta.2.0", "pd.hu6800", "pd.huex.1.0.st.v2", "pd.hugene.1.0.st.v1", "pd.hugene.1.1.st.v1", "pd.hugene.2.0.st", "pd.hugene.2.1.st", "pd.maize", "pd.mapping250k.nsp", "pd.mapping250k.sty", "pd.mapping50k.hind240", "pd.mapping50k.xba240", "pd.margene.1.0.st", "pd.margene.1.1.st", "pd.medgene.1.0.st", "pd.medgene.1.1.st", "pd.medicago", "pd.mg.u74a", "pd.mg.u74av2", "pd.mg.u74b", "pd.mg.u74bv2", "pd.mg.u74c", "pd.mg.u74cv2", "pd.mirna.1.0", "pd.mirna.2.0", "pd.mirna.3.0", "pd.mirna.3.1", "pd.mirna.4.0", "pd.moe430a", "pd.moe430b", "pd.moex.1.0.st.v1", "pd.mogene.1.0.st.v1", "pd.mogene.1.1.st.v1", "pd.mogene.2.0.st", "pd.mogene.2.1.st", "pd.mouse430.2", "pd.mouse430a.2", "pd.mta.1.0", "pd.mu11ksuba", "pd.mu11ksubb", "pd.nugo.hs1a520180", "pd.nugo.mm1a520177", "pd.ovigene.1.0.st", "pd.ovigene.1.1.st", "pd.pae.g1a", "pd.plasmodium.anopheles", "pd.poplar", "pd.porcine", "pd.porgene.1.0.st", "pd.porgene.1.1.st", "pd.rabgene.1.0.st", "pd.rabgene.1.1.st", "pd.rae230a", "pd.rae230b", "pd.raex.1.0.st.v1", "pd.ragene.1.0.st.v1", "pd.ragene.1.1.st.v1", "pd.ragene.2.0.st", "pd.ragene.2.1.st", "pd.rat230.2", "pd.rcngene.1.0.st", "pd.rcngene.1.1.st", "pd.rg.u34a", "pd.rg.u34b", "pd.rg.u34c", "pd.rhegene.1.0.st", "pd.rhegene.1.1.st", "pd.rhesus", "pd.rice", "pd.rjpgene.1.0.st", "pd.rjpgene.1.1.st", "pd.rn.u34", "pd.rta.1.0", "pd.rusgene.1.0.st", "pd.rusgene.1.1.st", "pd.s.aureus", "pd.soybean", "pd.soygene.1.0.st", "pd.soygene.1.1.st", "pd.sugar.cane", "pd.tomato", "pd.u133.x3p", "pd.vitis.vinifera", "pd.wheat", "pd.x.laevis.2", "pd.x.tropicalis", "pd.xenopus.laevis", "pd.yeast.2", "pd.yg.s98", "pd.zebgene.1.0.st", "pd.zebgene.1.1.st", "pd.zebrafish", "puma", "waveTiling" ], "importsMe": [ "affycoretools", "ArrayTV", "charm", "frma", "ITALICS", "MinimumDistance", "pdInfoBuilder", "puma", "SNPchip", "VanillaICE" ], "suggestsMe": [ "BiocGenerics", "CNPBayes", "hapmapsnp6" ] }, "OLIN": { "Package": "OLIN", "Version": "1.52.0", "Depends": [ "R (>= 2.10)", "methods", "locfit", "marray" ], "Imports": [ "graphics", "grDevices", "limma", "marray", "methods", "stats" ], "Suggests": [ "convert" ], "License": "GPL-2", "MD5sum": "91a3ed371c1c76e4d5ff9d87376766af", "NeedsCompilation": "no", "Title": "Optimized local intensity-dependent normalisation of two-color microarrays", "Description": "Functions for normalisation of two-color microarrays by optimised local regression and for detection of artefacts in microarray data", "biocViews": [ "Microarray", "Preprocessing", "QualityControl", "Software", "TwoChannel", "Visualization" ], "Author": "Matthias Futschik ", "Maintainer": "Matthias Futschik ", "URL": "http://olin.sysbiolab.eu", "source.ver": "src/contrib/OLIN_1.52.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/OLIN_1.52.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/OLIN_1.52.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/OLIN_1.52.0.tgz", "vignettes": [ "vignettes/OLIN/inst/doc/OLIN.pdf" ], "vignetteTitles": [ "Introduction to OLIN" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/OLIN/inst/doc/OLIN.R" ], "dependsOnMe": [ "OLINgui" ], "importsMe": [ "OLINgui" ], "suggestsMe": [ "maigesPack" ] }, "OLINgui": { "Package": "OLINgui", "Version": "1.48.0", "Depends": [ "R (>= 2.0.0)", "OLIN (>= 1.4.0)" ], "Imports": [ "graphics", "marray", "OLIN", "tcltk", "tkWidgets", "widgetTools" ], "License": "GPL-2", "MD5sum": "9bd60e2725736b58994d689c4c42ff79", "NeedsCompilation": "no", "Title": "Graphical user interface for OLIN", "Description": "Graphical user interface for the OLIN package", "biocViews": [ "Microarray", "Preprocessing", "QualityControl", "Software", "TwoChannel", "Visualization" ], "Author": "Matthias Futschik ", "Maintainer": "Matthias Futschik ", "URL": "http://olin.sysbiolab.eu", "source.ver": "src/contrib/OLINgui_1.48.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/OLINgui_1.48.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/OLINgui_1.48.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/OLINgui_1.48.0.tgz", "vignettes": [ "vignettes/OLINgui/inst/doc/OLINgui.pdf" ], "vignetteTitles": [ "Introduction to OLINgui" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/OLINgui/inst/doc/OLINgui.R" ] }, "omicade4": { "Package": "omicade4", "Version": "1.14.0", "Depends": [ "R (>= 3.0.0)", "ade4" ], "Imports": [ "made4" ], "Suggests": [ "BiocStyle" ], "License": "GPL-2", "MD5sum": "31d1e0136fd2fe22784a68e923a0b7dd", "NeedsCompilation": "no", "Title": "Multiple co-inertia analysis of omics datasets", "Description": "Multiple co-inertia analysis of omics datasets", "biocViews": [ "Classification", "Clustering", "MultipleComparison", "Software" ], "Author": "Chen Meng, Aedin Culhane, Amin M. Gholami.", "Maintainer": "Chen Meng ", "source.ver": "src/contrib/omicade4_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/omicade4_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/omicade4_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/omicade4_1.14.0.tgz", "vignettes": [ "vignettes/omicade4/inst/doc/omicade4.pdf" ], "vignetteTitles": [ "Using omicade4" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/omicade4/inst/doc/omicade4.R" ], "suggestsMe": [ "MultiDataSet" ] }, "OmicCircos": { "Package": "OmicCircos", "Version": "1.12.0", "Depends": [ "R (>= 2.14.0)", "methods", "GenomicRanges" ], "License": "GPL-2", "MD5sum": "ffc850f142ad5b42d9ac72014da4ccf5", "NeedsCompilation": "no", "Title": "High-quality circular visualization of omics data", "Description": "OmicCircos is an R application and package for generating high-quality circular plots for omics data.", "biocViews": [ "Annotation", "Software", "Statistics", "Visualization" ], "Author": "Ying Hu Chunhua Yan ", "Maintainer": "Ying Hu ", "source.ver": "src/contrib/OmicCircos_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/OmicCircos_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/OmicCircos_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/OmicCircos_1.12.0.tgz", "vignettes": [ "vignettes/OmicCircos/inst/doc/OmicCircos_vignette.pdf" ], "vignetteTitles": [ "OmicCircos vignette" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/OmicCircos/inst/doc/OmicCircos_vignette.R" ] }, "OmicsMarkeR": { "Package": "OmicsMarkeR", "Version": "1.8.1", "Depends": [ "R (>= 3.2.0)" ], "Imports": [ "graphics", "stats", "utils", "plyr (>= 1.8)", "data.table (>= 1.9.4)", "caret (>= 6.0-37)", "DiscriMiner (>= 0.1-29)", "e1071 (>= 1.6-1)", "randomForest (>= 4.6-10)", "gbm (>= 2.1)", "pamr (>= 1.54.1)", "glmnet (>= 1.9-5)", "caTools (>= 1.14)", "foreach (>= 1.4.1)", "permute (>= 0.7-0)", "assertive (>= 0.3-0)", "assertive.base (>= 0.0-1)" ], "Suggests": [ "testthat", "BiocStyle", "knitr" ], "License": "GPL-3", "MD5sum": "5a1599983afe8f368abcce76dffe7f33", "NeedsCompilation": "no", "Title": "Classification and Feature Selection for 'Omics' Datasets", "Description": "Tools for classification and feature selection for 'omics' level datasets. It is a tool to provide multiple multivariate classification and feature selection techniques complete with multiple stability metrics and aggregation techniques. It is primarily designed for analysis of metabolomics datasets but potentially extendable to proteomics and transcriptomics applications.", "biocViews": [ "Classification", "FeatureExtraction", "Metabolomics", "Software" ], "Author": "Charles E. Determan Jr. ", "Maintainer": "Charles E. Determan Jr. ", "URL": "http://github.com/cdeterman/OmicsMarkeR", "VignetteBuilder": "knitr", "BugReports": "http://github.com/cdeterman/OmicsMarkeR/issues/new", "source.ver": "src/contrib/OmicsMarkeR_1.8.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/OmicsMarkeR_1.8.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/OmicsMarkeR_1.8.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/OmicsMarkeR_1.8.1.tgz", "vignettes": [ "vignettes/OmicsMarkeR/inst/doc/OmicsMarkeR.pdf" ], "vignetteTitles": [ "A Short Introduction to the OmicMarkeR Package" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/OmicsMarkeR/inst/doc/OmicsMarkeR.R" ] }, "OncoScore": { "Package": "OncoScore", "Version": "1.2.1", "Depends": [ "R (>= 3.3)" ], "Imports": [ "biomaRt", "grDevices", "graphics", "utils" ], "Suggests": [ "BiocGenerics", "BiocStyle", "testthat" ], "License": "GPL-3", "MD5sum": "b879c00ac1f1274994e0c770d1306efb", "NeedsCompilation": "no", "Title": "A tool to identify potentially oncogenic genes", "Description": "OncoScore is a tool to measure the association of genes to cancer based on citation frequencies in biomedical literature. The score is evaluated from PubMed literature by dynamically updatable web queries.", "biocViews": [ "BiomedicalInformatics", "Software" ], "Author": "Luca De Sano [aut], Carlo Gambacorti Passerini [ctb], Rocco Piazza [ctb], Daniele Ramazzotti [aut, cre], Roberta Spinelli [ctb]", "Maintainer": "Daniele Ramazzotti ", "URL": "https://github.com/danro9685/OncoScore", "BugReports": "https://github.com/danro9685/OncoScore", "source.ver": "src/contrib/OncoScore_1.2.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/OncoScore_1.2.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/OncoScore_1.2.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/OncoScore_1.2.1.tgz", "vignettes": [ "vignettes/OncoScore/inst/doc/vignette.pdf" ], "vignetteTitles": [ "OncoScore" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/OncoScore/inst/doc/vignette.R" ] }, "OncoSimulR": { "Package": "OncoSimulR", "Version": "2.4.0", "Depends": [ "R (>= 3.3.0)" ], "Imports": [ "Rcpp (>= 0.12.4)", "parallel", "data.table", "graph", "Rgraphviz", "gtools", "igraph", "methods", "RColorBrewer", "grDevices", "car", "dplyr", "smatr", "ggplot2", "ggrepel" ], "LinkingTo": [ "Rcpp" ], "Suggests": [ "BiocStyle", "knitr", "Oncotree", "testthat (>= 1.0.0)", "rmarkdown", "bookdown" ], "License": "GPL (>= 3)", "Archs": "i386, x64", "MD5sum": "fa3208c2a5147d17634390e98b9b691d", "NeedsCompilation": "yes", "Title": "Forward Genetic Simulation of Cancer Progression with Epistasis", "Description": "Functions for forward population genetic simulation in asexual populations, with special focus on cancer progression. Fitness can be an arbitrary function of genetic interactions between multiple genes or modules of genes, including epistasis, order restrictions in mutation accumulation, and order effects. Mutation rates can differ between genes, and we can include mutator/antimutator genes (to model mutator phenotypes). Simulations use continuous-time models and can include driver and passenger genes and modules. Also included are functions for: simulating random DAGs of the type found in Oncogenetic Tress, Conjunctive Bayesian Networks, and other tumor progression models; plotting and sampling from single or multiple realizations of the simulations, including single-cell sampling; plotting the parent-child relationships of the clones; generating random fitness landscapes (Rough Mount Fuji, House of Cards, and additive models) and plotting them.", "biocViews": [ "BiologicalQuestion", "Software", "SomaticMutation" ], "Author": "Ramon Diaz-Uriarte [aut, cre], Mark Taylor [ctb]", "Maintainer": "Ramon Diaz-Uriarte ", "URL": "https://github.com/rdiaz02/OncoSimul, https://popmodels.cancercontrol.cancer.gov/gsr/packages/oncosimulr/", "VignetteBuilder": "knitr", "BugReports": "https://github.com/rdiaz02/OncoSimul/issues", "source.ver": "src/contrib/OncoSimulR_2.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/OncoSimulR_2.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/OncoSimulR_2.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/OncoSimulR_2.4.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/OncoSimulR/inst/doc/OncoSimulR.R" ], "htmlDocs": [ "vignettes/OncoSimulR/inst/doc/OncoSimulR.html" ], "htmlTitles": [ "OncoSimulR: forward genetic simulation in asexual populations with arbitrary epistatic interactions and a focus on modeling tumor progression." ] }, "oneChannelGUI": { "Package": "oneChannelGUI", "Version": "1.40.0", "Depends": [ "Biobase", "affylmGUI", "tkrplot", "tkWidgets", "IRanges", "Rsamtools (>= 1.13.1)", "Biostrings", "siggenes", "chimera" ], "Suggests": [ "annotate", "genefilter", "maSigPro", "pamr", "pdmclass", "ChIPpeakAnno", "chipseq", "BSgenome", "Rgraphviz", "affy", "annaffy", "affyPLM", "multtest", "ssize", "sizepower", "RankProd", "org.Hs.eg.db", "org.Mm.eg.db", "org.Rn.eg.db", "edgeR", "metaArray", "MergeMaid", "biomaRt", "GenomeGraphs", "AffyCompatible", "rtracklayer", "Genominator", "EDASeq", "limma", "DESeq", "DEXSeq", "goseq", "hugene10sttranscriptcluster.db", "mogene10sttranscriptcluster.db", "ragene10sttranscriptcluster.db", "GOstats", "AnnotationDbi", "preprocessCore", "baySeq", "HuExExonProbesetLocation", "MoExExonProbesetLocation", "RaExExonProbesetLocation", "snow", "RmiR", "RmiR.Hs.miRNA", "BSgenome.Hsapiens.UCSC.hg19", "R.utils", "cummeRbund", "BSgenome.Mmusculus.UCSC.mm9", "BSgenome.Rnorvegicus.UCSC.rn4", "DESeq2", "GenomicAlignments", "BiocParallel", "KEGG.db", "miRNApath", "miRNAtap", "miRNAtap.db" ], "License": "Artistic-2.0", "MD5sum": "5b80a16c6b0d3be5701614982537de08", "NeedsCompilation": "no", "Title": "A graphical interface designed to facilitate analysis of microarrays and miRNA/RNA-seq data on laptops", "Description": "This package was developed to simplify the use of Bioconductor tools for beginners having limited or no experience in writing R code. This library provides a graphical interface for microarray gene and exon level analysis as well as miRNA/mRNA-seq data analysis", "biocViews": [ "DataImport", "DifferentialExpression", "GUI", "Microarray", "MultipleComparison", "OneChannel", "Preprocessing", "QualityControl", "RNASeq", "Sequencing", "Software", "StatisticalMethod" ], "Author": "Raffale A Calogero, Bioinformatics and Genomics Unit, Molecular Biotechnology Center, Torino (Italy)", "Maintainer": "Raffaele A Calogero ", "URL": "http://www.bioinformatica.unito.it/oneChannelGUI/", "source.ver": "src/contrib/oneChannelGUI_1.40.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/oneChannelGUI_1.40.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/oneChannelGUI_1.40.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/oneChannelGUI_1.40.0.tgz", "vignettes": [ "vignettes/oneChannelGUI/inst/doc/Exon-level.analysis.pdf", "vignettes/oneChannelGUI/inst/doc/gene-level.analysis.pdf", "vignettes/oneChannelGUI/inst/doc/install.pdf", "vignettes/oneChannelGUI/inst/doc/RNAseq.pdf", "vignettes/oneChannelGUI/inst/doc/standAloneFunctions.pdf" ], "vignetteTitles": [ "oneChannelGUI microarray exon-level data analysis overview", "oneChannelGUI microarray gene-level data analysis overview", "oneChannelGUI Installation", "oneChannelGUI miRNA and RNA-seq data analysis overview", "oneChannelGUI Stand Alone Functions" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/oneChannelGUI/inst/doc/install.R" ] }, "ontoCAT": { "Package": "ontoCAT", "Version": "1.26.0", "Depends": [ "rJava", "methods" ], "License": "Apache License 2.0", "MD5sum": "69d92d9b652e11ea1558254dbadb5e62", "NeedsCompilation": "no", "Title": "Ontology traversal and search", "Description": "The ontoCAT R package provides a simple interface to ontologies described in widely used standard formats, stored locally in the filesystem or accessible online.", "biocViews": [ "Classification", "DataRepresentation", "Software" ], "Author": "Natalja Kurbatova, Tomasz Adamusiak, Pavel Kurnosov, Morris Swertz, Misha Kapushevsky", "Maintainer": "Natalja Kurbatova ", "source.ver": "src/contrib/ontoCAT_1.26.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ontoCAT_1.26.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ontoCAT_1.26.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ontoCAT_1.26.0.tgz", "vignettes": [ "vignettes/ontoCAT/inst/doc/ontoCAT.pdf" ], "vignetteTitles": [ "ontoCAT package" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/ontoCAT/inst/doc/ontoCAT.R" ], "suggestsMe": [ "RMassBank" ] }, "openCyto": { "Package": "openCyto", "Version": "1.12.1", "Depends": [ "flowWorkspace(>= 3.17.43)" ], "Imports": [ "methods", "Biobase", "gtools", "flowCore(>= 1.31.17)", "flowViz", "ncdfFlow(>= 2.11.34)", "flowWorkspace", "flowStats(>= 3.29.1)", "flowClust(>= 3.11.4)", "MASS", "clue", "plyr", "RBGL", "graph", "data.table", "ks", "RColorBrewer", "lattice", "rrcov", "R.utils" ], "LinkingTo": [ "Rcpp" ], "Suggests": [ "flowWorkspaceData", "knitr", "testthat", "utils", "tools", "parallel" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "19038794693962e3a065bdb763cdbb90", "NeedsCompilation": "yes", "Title": "Hierarchical Gating Pipeline for flow cytometry data", "Description": "This package is designed to facilitate the automated gating methods in sequential way to mimic the manual gating strategy.", "biocViews": [ "DataImport", "DataRepresentation", "FlowCytometry", "Preprocessing", "Software" ], "Author": "Mike Jiang, John Ramey, Greg Finak, Raphael Gottardo", "Maintainer": "Mike Jiang ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/openCyto_1.12.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/openCyto_1.12.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/openCyto_1.12.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/openCyto_1.12.1.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/openCyto/inst/doc/HowToAutoGating.R", "vignettes/openCyto/inst/doc/HowToWriteCSVTemplate.R", "vignettes/openCyto/inst/doc/openCytoVignette.R" ], "htmlDocs": [ "vignettes/openCyto/inst/doc/HowToAutoGating.html", "vignettes/openCyto/inst/doc/HowToWriteCSVTemplate.html", "vignettes/openCyto/inst/doc/openCytoVignette.html" ], "htmlTitles": [ "How to use different auto gating functions", "How to write a csv gating template", "An Introduction to the openCyto package" ], "importsMe": [ "CytoML" ], "suggestsMe": [ "flowCore", "ggcyto" ] }, "OperaMate": { "Package": "OperaMate", "Version": "1.6.0", "Depends": [ "R (>= 3.2.0)", "stats", "methods", "grDevices" ], "Imports": [ "pheatmap", "grid", "ggplot2", "fBasics", "gProfileR", "gridExtra", "reshape2", "stabledist" ], "Suggests": [ "BiocStyle" ], "License": "GPL (>= 3)", "MD5sum": "605a838103e2ebaa68df28c8ba83dc21", "NeedsCompilation": "no", "Title": "An R package of Data Importing, Processing and Analysis for Opera High Content Screening System", "Description": "OperaMate is a flexible R package dealing with the data generated by PerkinElmer's Opera High Content Screening System. The functions include the data importing, normalization and quality control, hit detection and function analysis.", "biocViews": [ "CellBasedAssays", "Normalization", "Preprocessing", "QualityControl", "Software" ], "Author": "Chenglin Liu", "Maintainer": "Chenglin Liu ", "source.ver": "src/contrib/OperaMate_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/OperaMate_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/OperaMate_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/OperaMate_1.6.0.tgz", "vignettes": [ "vignettes/OperaMate/inst/doc/OperaMate-manual.pdf", "vignettes/OperaMate/inst/doc/OperaMate-vignette.pdf" ], "vignetteTitles": [ "OperaMate-manual.pdf", "An introduction to OperaMate" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/OperaMate/inst/doc/OperaMate-vignette.R" ] }, "oposSOM": { "Package": "oposSOM", "Version": "1.12.0", "Depends": [ "R (>= 3.0)", "igraph (>= 1.0.0)" ], "Imports": [ "som", "fastICA", "scatterplot3d", "pixmap", "fdrtool", "ape", "KernSmooth", "biomaRt", "Biobase" ], "License": "GPL (>=2)", "MD5sum": "1bbea93fa6f84990bf82c41eddf7e047", "NeedsCompilation": "no", "Title": "Comprehensive analysis of transciptome data", "Description": "This package translates microarray expression data into metadata of reduced dimension. It provides various sample-centered and group-centered visualizations, sample similarity analyses and functional enrichment analyses. The underlying SOM algorithm combines feature clustering, multidimensional scaling and dimension reduction, along with strong visualization capabilities. It enables extraction and description of functional expression modules inherent in the data.", "biocViews": [ "DataRepresentation", "DifferentialExpression", "GeneExpression", "GeneSetEnrichment", "Software", "Visualization" ], "Author": "Henry Loeffler-Wirth and Martin Kalcher ", "Maintainer": "Henry Loeffler-Wirth ", "URL": "http://som.izbi.uni-leipzig.de", "source.ver": "src/contrib/oposSOM_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/oposSOM_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/oposSOM_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/oposSOM_1.12.0.tgz", "vignettes": [ "vignettes/oposSOM/inst/doc/Vignette.pdf" ], "vignetteTitles": [ "The oposSOM users guide" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/oposSOM/inst/doc/Vignette.R" ] }, "oppar": { "Package": "oppar", "Version": "1.2.0", "Depends": [ "R (>= 3.3)" ], "Imports": [ "Biobase", "methods", "GSEABase", "GSVA" ], "Suggests": [ "knitr", "rmarkdown", "limma", "org.Hs.eg.db", "GO.db", "snow", "parallel" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "9f99a7a3d2550306ff4303239e8434e3", "NeedsCompilation": "yes", "Title": "Outlier profile and pathway analysis in R", "Description": "The R implementation of mCOPA package published by Wang et al. (2012). Oppar provides methods for Cancer Outlier profile Analysis. Although initially developed to detect outlier genes in cancer studies, methods presented in oppar can be used for outlier profile analysis in general. In addition, tools are provided for gene set enrichment and pathway analysis.", "biocViews": [ "GeneExpression", "GeneSetEnrichment", "Pathways", "Software", "SystemsBiology" ], "Author": "Chenwei Wang [aut], Alperen Taciroglu [aut], Stefan R Maetschke [aut], Colleen C Nelson [aut], Mark Ragan [aut], Melissa Davis [aut], Soroor Hediyeh zadeh [cre], Momeneh Foroutan [ctr]", "Maintainer": "Soroor Hediyeh zadeh ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/oppar_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/oppar_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/oppar_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/oppar_1.2.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/oppar/inst/doc/oppar.R" ], "htmlDocs": [ "vignettes/oppar/inst/doc/oppar.html" ], "htmlTitles": [ "OPPAR: Outlier Profile and Pathway Analysis in R" ] }, "OrderedList": { "Package": "OrderedList", "Version": "1.46.0", "Depends": [ "R (>= 2.1.0)", "Biobase (>= 1.5.12)", "twilight (>= 1.9.2)", "methods" ], "Imports": [ "Biobase", "graphics", "methods", "stats", "twilight" ], "License": "GPL (>= 2)", "MD5sum": "8b89f476835e033e98935f1516f8fa3a", "NeedsCompilation": "no", "Title": "Similarities of Ordered Gene Lists", "Description": "Detection of similarities between ordered lists of genes. Thereby, either simple lists can be compared or gene expression data can be used to deduce the lists. Significance of similarities is evaluated by shuffling lists or by resampling in microarray data, respectively.", "biocViews": [ "DifferentialExpression", "Microarray", "MultipleComparison", "Software" ], "Author": "Xinan Yang, Stefanie Scheid, Claudio Lottaz", "Maintainer": "Claudio Lottaz ", "URL": "http://compdiag.molgen.mpg.de/software/index.shtml", "source.ver": "src/contrib/OrderedList_1.46.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/OrderedList_1.46.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/OrderedList_1.46.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/OrderedList_1.46.0.tgz", "vignettes": [ "vignettes/OrderedList/inst/doc/tr_2006_01.pdf" ], "vignetteTitles": [ "Similarities of Ordered Gene Lists" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/OrderedList/inst/doc/tr_2006_01.R" ] }, "OrganismDbi": { "Package": "OrganismDbi", "Version": "1.16.0", "Depends": [ "R (>= 2.14.0)", "methods", "BiocGenerics (>= 0.15.10)", "AnnotationDbi (>= 1.33.15)", "GenomicFeatures (>= 1.23.31)" ], "Imports": [ "Biobase", "BiocInstaller", "GenomicRanges", "graph", "IRanges", "RBGL", "RSQLite", "S4Vectors (>= 0.9.25)", "stats" ], "Suggests": [ "Homo.sapiens", "Rattus.norvegicus", "BSgenome.Hsapiens.UCSC.hg19", "AnnotationHub", "FDb.UCSC.tRNAs", "rtracklayer", "biomaRt", "RUnit" ], "License": "Artistic-2.0", "MD5sum": "56c816b5526cf923170b83c8334b28fc", "NeedsCompilation": "no", "Title": "Software to enable the smooth interfacing of different database packages", "Description": "The package enables a simple unified interface to several annotation packages each of which has its own schema by taking advantage of the fact that each of these packages implements a select methods.", "biocViews": [ "Annotation", "Infrastructure", "Software" ], "Author": "Marc Carlson, Herve Pages, Martin Morgan, Valerie Obenchain", "Maintainer": "Biocore Data Team ", "source.ver": "src/contrib/OrganismDbi_1.16.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/OrganismDbi_1.16.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/OrganismDbi_1.16.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/OrganismDbi_1.16.0.tgz", "vignettes": [ "vignettes/OrganismDbi/inst/doc/OrganismDbi.pdf" ], "vignetteTitles": [ "OrganismDbi: A meta framework for Annotation Packages" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/OrganismDbi/inst/doc/OrganismDbi.R" ], "importsMe": [ "AnnotationHubData", "epivizrData", "ggbio" ], "suggestsMe": [ "ChIPpeakAnno", "epivizrStandalone" ], "dependsOnMe": [ "Homo.sapiens", "Mus.musculus", "Rattus.norvegicus" ] }, "OSAT": { "Package": "OSAT", "Version": "1.22.0", "Depends": [ "methods", "stats" ], "Suggests": [ "xtable", "Biobase" ], "License": "Artistic-2.0", "MD5sum": "32d68aad8ac54c742b747fbe1ed6fd8b", "NeedsCompilation": "no", "Title": "OSAT: Optimal Sample Assignment Tool", "Description": "A sizable genomics study such as microarray often involves the use of multiple batches (groups) of experiment due to practical complication. To minimize batch effects, a careful experiment design should ensure the even distribution of biological groups and confounding factors across batches. OSAT (Optimal Sample Assignment Tool) is developed to facilitate the allocation of collected samples to different batches. With minimum steps, it produces setup that optimizes the even distribution of samples in groups of biological interest into different batches, reducing the confounding or correlation between batches and the biological variables of interest. It can also optimize the even distribution of confounding factors across batches. Our tool can handle challenging instances where incomplete and unbalanced sample collections are involved as well as ideal balanced RCBD. OSAT provides a number of predefined layout for some of the most commonly used genomics platform. Related paper can be find at http://www.biomedcentral.com/1471-2164/13/689 .", "biocViews": [ "DataRepresentation", "ExperimentalDesign", "QualityControl", "Software", "Visualization" ], "Author": "Li Yan", "Maintainer": "Li Yan ", "URL": "http://www.biomedcentral.com/1471-2164/13/689", "source.ver": "src/contrib/OSAT_1.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/OSAT_1.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/OSAT_1.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/OSAT_1.22.0.tgz", "vignettes": [ "vignettes/OSAT/inst/doc/OSAT.pdf" ], "vignetteTitles": [ "An introduction to OSAT" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/OSAT/inst/doc/OSAT.R" ] }, "Oscope": { "Package": "Oscope", "Version": "1.4.0", "Depends": [ "EBSeq", "cluster", "testthat", "BiocParallel" ], "Suggests": [ "BiocStyle" ], "License": "Artistic-2.0", "MD5sum": "677fae951b5630250496fa60847a8acd", "NeedsCompilation": "no", "Title": "Oscope - A statistical pipeline for identifying oscillatory genes in unsynchronized single cell RNA-seq", "Description": "Oscope is a statistical pipeline developed to identifying and recovering the base cycle profiles of oscillating genes in an unsynchronized single cell RNA-seq experiment. The Oscope pipeline includes three modules: a sine model module to search for candidate oscillator pairs; a K-medoids clustering module to cluster candidate oscillators into groups; and an extended nearest insertion module to recover the base cycle order for each oscillator group.", "biocViews": [ "GeneExpression", "RNASeq", "Sequencing", "Software", "StatisticalMethod" ], "Author": "Ning Leng", "Maintainer": "Ning Leng ", "source.ver": "src/contrib/Oscope_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Oscope_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Oscope_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Oscope_1.4.0.tgz", "vignettes": [ "vignettes/Oscope/inst/doc/Oscope_vignette.pdf" ], "vignetteTitles": [ "Oscope_vigette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Oscope/inst/doc/Oscope_vignette.R" ] }, "OTUbase": { "Package": "OTUbase", "Version": "1.24.0", "Depends": [ "R (>= 2.9.0)", "methods", "S4Vectors", "IRanges", "ShortRead (>= 1.23.15)", "Biobase", "vegan" ], "Imports": [ "Biostrings" ], "License": "Artistic-2.0", "MD5sum": "91181dc3b3d58b2beaa0aa9b46c1d203", "NeedsCompilation": "no", "Title": "Provides structure and functions for the analysis of OTU data", "Description": "Provides a platform for Operational Taxonomic Unit based analysis", "biocViews": [ "DataImport", "Sequencing", "Software" ], "Author": "Daniel Beck, Matt Settles, and James A. Foster", "Maintainer": "Daniel Beck ", "source.ver": "src/contrib/OTUbase_1.24.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/OTUbase_1.24.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/OTUbase_1.24.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/OTUbase_1.24.0.tgz", "vignettes": [ "vignettes/OTUbase/inst/doc/Introduction_to_OTUbase.pdf" ], "vignetteTitles": [ "An introduction to OTUbase" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/OTUbase/inst/doc/Introduction_to_OTUbase.R" ], "dependsOnMe": [ "mcaGUI" ] }, "OutlierD": { "Package": "OutlierD", "Version": "1.38.0", "Depends": [ "R (>= 2.3.0)", "Biobase", "quantreg" ], "License": "GPL (>= 2)", "MD5sum": "7a00b158c4c454d97c7d56d14e5a25e2", "NeedsCompilation": "no", "Title": "Outlier detection using quantile regression on the M-A scatterplots of high-throughput data", "Description": "This package detects outliers using quantile regression on the M-A scatterplots of high-throughput data.", "biocViews": [ "Microarray", "Software" ], "Author": "HyungJun Cho ", "Maintainer": "Sukwoo Kim ", "URL": "http://www.korea.ac.kr/~stat2242/", "source.ver": "src/contrib/OutlierD_1.38.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/OutlierD_1.38.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/OutlierD_1.38.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/OutlierD_1.38.0.tgz", "vignettes": [ "vignettes/OutlierD/inst/doc/OutlierD.pdf" ], "vignetteTitles": [ "Overview" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/OutlierD/inst/doc/OutlierD.R" ] }, "PAA": { "Package": "PAA", "Version": "1.8.0", "Depends": [ "R (>= 3.2.0)", "Rcpp (>= 0.11.6)" ], "Imports": [ "e1071", "gplots", "gtools", "limma", "MASS", "mRMRe", "randomForest", "ROCR", "sva" ], "LinkingTo": [ "Rcpp" ], "Suggests": [ "BiocStyle", "RUnit", "BiocGenerics", "vsn" ], "License": "BSD_3_clause + file LICENSE", "Archs": "i386, x64", "MD5sum": "54ce624153f265a0c2c2d51d048d5e17", "NeedsCompilation": "yes", "Title": "PAA (Protein Array Analyzer)", "Description": "PAA imports single color (protein) microarray data that has been saved in gpr file format - esp. ProtoArray data. After preprocessing (background correction, batch filtering, normalization) univariate feature preselection is performed (e.g., using the \"minimum M statistic\" approach - hereinafter referred to as \"mMs\"). Subsequently, a multivariate feature selection is conducted to discover biomarker candidates. Therefore, either a frequency-based backwards elimination aproach or ensemble feature selection can be used. PAA provides a complete toolbox of analysis tools including several different plots for results examination and evaluation.", "biocViews": [ "Classification", "Microarray", "OneChannel", "Proteomics", "Software" ], "Author": "Michael Turewicz [aut, cre], Martin Eisenacher [ctb, cre]", "Maintainer": "Michael Turewicz , Martin Eisenacher ", "URL": "http://www.ruhr-uni-bochum.de/mpc/software/PAA/", "SystemRequirements": "C++ software package Random Jungle", "source.ver": "src/contrib/PAA_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/PAA_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/PAA_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/PAA_1.8.0.tgz", "vignettes": [ "vignettes/PAA/inst/doc/PAA_1.7.1.pdf", "vignettes/PAA/inst/doc/PAA_vignette.pdf" ], "vignetteTitles": [ "PAA_1.7.1.pdf", "PAA tutorial" ], "hasREADME": true, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/PAA/inst/doc/PAA_vignette.R" ] }, "PADOG": { "Package": "PADOG", "Version": "1.16.0", "Depends": [ "R (>= 3.0.0)", "KEGGdzPathwaysGEO", "methods", "Biobase" ], "Imports": [ "limma", "AnnotationDbi", "GSA", "foreach", "doRNG", "hgu133plus2.db", "hgu133a.db", "KEGG.db", "nlme" ], "Suggests": [ "doParallel", "parallel" ], "License": "GPL (>= 2)", "MD5sum": "c345375fb3fc69c949d5856f10ab5ade", "NeedsCompilation": "no", "Title": "Pathway Analysis with Down-weighting of Overlapping Genes (PADOG)", "Description": "This package implements a general purpose gene set analysis method called PADOG that downplays the importance of genes that apear often accross the sets of genes to be analyzed. The package provides also a benchmark for gene set analysis methods in terms of sensitivity and ranking using 24 public datasets from KEGGdzPathwaysGEO package.", "biocViews": [ "Microarray", "OneChannel", "Software", "TwoChannel" ], "Author": "Adi Laurentiu Tarca ; Zhonghui Xu ", "Maintainer": "Adi Laurentiu Tarca ", "source.ver": "src/contrib/PADOG_1.16.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/PADOG_1.16.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/PADOG_1.16.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/PADOG_1.16.0.tgz", "vignettes": [ "vignettes/PADOG/inst/doc/PADOG.pdf" ], "vignetteTitles": [ "PADOG" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/PADOG/inst/doc/PADOG.R" ], "importsMe": [ "EGSEA" ] }, "paircompviz": { "Package": "paircompviz", "Version": "1.12.0", "Depends": [ "R (>= 2.10)", "Rgraphviz" ], "Imports": [ "Rgraphviz" ], "Suggests": [ "multcomp", "reshape", "rpart", "plyr", "xtable" ], "License": "GPL (>=3.0)", "MD5sum": "dac32e61b14dfa4ab867143552cbda3e", "NeedsCompilation": "no", "Title": "Multiple comparison test visualization", "Description": "This package provides visualization of the results from the multiple (i.e. pairwise) comparison tests such as pairwise.t.test, pairwise.prop.test or pairwise.wilcox.test. The groups being compared are visualized as nodes in Hasse diagram. Such approach enables very clear and vivid depiction of which group is significantly greater than which others, especially if comparing a large number of groups.", "biocViews": [ "GraphAndNetwork", "Software" ], "Author": "Michal Burda", "Maintainer": "Michal Burda ", "source.ver": "src/contrib/paircompviz_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/paircompviz_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/paircompviz_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/paircompviz_1.12.0.tgz", "vignettes": [ "vignettes/paircompviz/inst/doc/vignette.pdf" ], "vignetteTitles": [ "Using paircompviz" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/paircompviz/inst/doc/vignette.R" ] }, "pandaR": { "Package": "pandaR", "Version": "1.6.0", "Depends": [ "R (>= 3.0.0)", "methods", "Biobase", "BiocGenerics" ], "Imports": [ "matrixStats", "igraph", "ggplot2", "grid", "reshape", "plyr", "RUnit", "hexbin" ], "Suggests": [ "rmarkdown" ], "License": "GPL-2", "MD5sum": "eab545fbb991e200fb3298802d2352da", "NeedsCompilation": "no", "Title": "PANDA Algorithm", "Description": "Runs PANDA, an algorithm for discovering novel network structure by combining information from multiple complementary data sources.", "biocViews": [ "GeneExpression", "GeneRegulation", "GraphAndNetwork", "Microarray", "Network", "NetworkInference", "Software", "StatisticalMethod", "Transcription" ], "Author": "Dan Schlauch, Joseph N. Paulson, Albert Young, John Quackenbush, Kimberly Glass", "Maintainer": "Joseph N. Paulson , Dan Schlauch ", "VignetteBuilder": "rmarkdown", "source.ver": "src/contrib/pandaR_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/pandaR_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/pandaR_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/pandaR_1.6.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false }, "PAnnBuilder": { "Package": "PAnnBuilder", "Version": "1.38.0", "Depends": [ "R (>= 2.7.0)", "methods", "utils", "RSQLite", "Biobase (>= 1.17.0)", "AnnotationDbi (>= 1.3.12)" ], "Imports": [ "methods", "utils", "Biobase", "DBI", "RSQLite", "AnnotationDbi" ], "Suggests": [ "org.Hs.ipi.db" ], "License": "LGPL (>= 2.0)", "MD5sum": "a1ac929cd54e0c51eb47ef711a4e42e5", "NeedsCompilation": "no", "Title": "Protein annotation data package builder", "Description": "Processing annotation data from public data repositories and building protein-centric annotation data packages.", "biocViews": [ "Annotation", "Proteomics", "Software" ], "Author": "Li Hong lihong@sibs.ac.cn", "Maintainer": "Li Hong ", "URL": "http://www.biosino.org/PAnnBuilder", "source.ver": "src/contrib/PAnnBuilder_1.38.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/PAnnBuilder_1.38.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/PAnnBuilder_1.38.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/PAnnBuilder_1.38.0.tgz", "vignettes": [ "vignettes/PAnnBuilder/inst/doc/PAnnBuilder.pdf" ], "vignetteTitles": [ "Using the PAnnBuilder Package" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/PAnnBuilder/inst/doc/PAnnBuilder.R" ], "dependsOnMe": [ "org.Hs.ipi.db" ], "importsMe": [ "org.Hs.ipi.db" ] }, "panp": { "Package": "panp", "Version": "1.44.0", "Depends": [ "R (>= 2.10)", "affy (>= 1.23.4)", "Biobase (>= 2.5.5)" ], "Imports": [ "Biobase", "methods", "stats", "utils" ], "Suggests": [ "gcrma" ], "License": "GPL (>= 2)", "MD5sum": "db365d15dde61939384c18f19f60fa58", "NeedsCompilation": "no", "Title": "Presence-Absence Calls from Negative Strand Matching Probesets", "Description": "A function to make gene presence/absence calls based on distance from negative strand matching probesets (NSMP) which are derived from Affymetrix annotation. PANP is applied after gene expression values are created, and therefore can be used after any preprocessing method such as MAS5 or GCRMA, or PM-only methods like RMA. NSMP sets have been established for the HGU133A and HGU133-Plus-2.0 chipsets to date.", "biocViews": [ "Infrastructure", "Software" ], "Author": "Peter Warren", "Maintainer": "Peter Warren ", "source.ver": "src/contrib/panp_1.44.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/panp_1.44.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/panp_1.44.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/panp_1.44.0.tgz", "vignettes": [ "vignettes/panp/inst/doc/panp.pdf" ], "vignetteTitles": [ "gene presence/absence calls" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/panp/inst/doc/panp.R" ] }, "PANR": { "Package": "PANR", "Version": "1.20.0", "Depends": [ "R (>= 2.14)", "igraph" ], "Imports": [ "graphics", "grDevices", "MASS", "methods", "pvclust", "stats", "utils", "RedeR" ], "Suggests": [ "snow" ], "License": "Artistic-2.0", "MD5sum": "2fb333f9ec4e736e1e1448d1afb1560e", "NeedsCompilation": "no", "Title": "Posterior association networks and functional modules inferred from rich phenotypes of gene perturbations", "Description": "This package provides S4 classes and methods for inferring functional gene networks with edges encoding posterior beliefs of gene association types and nodes encoding perturbation effects.", "biocViews": [ "CellBasedAssays", "Clustering", "GraphAndNetwork", "NetworkInference", "Software", "Visualization" ], "Author": "Xin Wang ", "Maintainer": "Xin Wang ", "source.ver": "src/contrib/PANR_1.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/PANR_1.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/PANR_1.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/PANR_1.20.0.tgz", "vignettes": [ "vignettes/PANR/inst/doc/PANR-Vignette.pdf" ], "vignetteTitles": [ "Main vignette:Posterior association network and enriched functional gene modules inferred from rich phenotypes of gene perturbations" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/PANR/inst/doc/PANR-Vignette.R" ], "suggestsMe": [ "RedeR" ], "importsMe": [ "Mulder2012" ] }, "PanVizGenerator": { "Package": "PanVizGenerator", "Version": "1.2.0", "Depends": [ "methods" ], "Imports": [ "shiny", "tools", "jsonlite", "pcaMethods", "FindMyFriends", "igraph", "stats", "utils" ], "Suggests": [ "BiocStyle", "knitr", "rmarkdown", "testthat", "digest" ], "License": "GPL (>= 2)", "MD5sum": "c7b125493013e88170cbb7d1bb1420d6", "NeedsCompilation": "no", "Title": "Generate PanViz visualisations from your pangenome", "Description": "PanViz is a JavaScript based visualisation tool for functionaly annotated pangenomes. PanVizGenerator is a companion for PanViz that facilitates the necessary data preprocessing step necessary to create a working PanViz visualization. The output is fully self-contained so the recipient of the visualization does not need R or PanVizGenerator installed.", "biocViews": [ "ComparativeGenomics", "GUI", "Software", "Visualization" ], "Author": "Thomas Lin Pedersen", "Maintainer": "Thomas Lin Pedersen ", "URL": "https://github.com/thomasp85/PanVizGenerator", "VignetteBuilder": "knitr", "BugReports": "https://github.com/thomasp85/PanVizGenerator/issues", "source.ver": "src/contrib/PanVizGenerator_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/PanVizGenerator_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/PanVizGenerator_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/PanVizGenerator_1.2.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/PanVizGenerator/inst/doc/panviz_howto.R" ], "htmlDocs": [ "vignettes/PanVizGenerator/inst/doc/panviz_howto.html" ], "htmlTitles": [ "Creating PanViz visualizations with PanVizGenerator" ] }, "PAPi": { "Package": "PAPi", "Version": "1.14.0", "Depends": [ "R (>= 2.15.2)", "svDialogs", "KEGGREST" ], "License": "GPL(>= 2)", "MD5sum": "4e7bc9701fd574ce06479bbb29a47871", "NeedsCompilation": "no", "Title": "Predict metabolic pathway activity based on metabolomics data", "Description": "The Pathway Activity Profiling - PAPi - is an R package for predicting the activity of metabolic pathways based solely on a metabolomics data set containing a list of metabolites identified and their respective abundances in different biological samples. PAPi generates hypothesis that improves the final biological interpretation. See Aggio, R.B.M; Ruggiero, K. and Villas-Boas, S.G. (2010) - Pathway Activity Profiling (PAPi): from metabolite profile to metabolic pathway activity. Bioinformatics.", "biocViews": [ "MassSpectrometry", "Metabolomics", "Software" ], "Author": "Raphael Aggio", "Maintainer": "Raphael Aggio ", "source.ver": "src/contrib/PAPi_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/PAPi_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/PAPi_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/PAPi_1.14.0.tgz", "vignettes": [ "vignettes/PAPi/inst/doc/PAPi.pdf", "vignettes/PAPi/inst/doc/PAPiPackage.pdf" ], "vignetteTitles": [ "PAPi.pdf", "Applying PAPi" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/PAPi/inst/doc/PAPiPackage.R" ] }, "parglms": { "Package": "parglms", "Version": "1.6.0", "Depends": [ "methods" ], "Imports": [ "BiocGenerics", "BatchJobs", "foreach", "doParallel" ], "Suggests": [ "RUnit", "sandwich", "MASS" ], "License": "Artistic-2.0", "MD5sum": "51898ed6f74a55c8120cf939007bca5f", "NeedsCompilation": "no", "Title": "support for parallelized estimation of GLMs/GEEs", "Description": "support for parallelized estimation of GLMs/GEEs, catering for dispersed data", "Author": "VJ Carey ", "Maintainer": "VJ Carey ", "source.ver": "src/contrib/parglms_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/parglms_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/parglms_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/parglms_1.6.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "biocViews": [ "Software" ] }, "parody": { "Package": "parody", "Version": "1.32.0", "Depends": [ "R (>= 2.5.0)", "methods", "tools", "utils" ], "License": "Artistic-2.0", "MD5sum": "4d00d845e4c1ec93a7e3e541c603f6b1", "NeedsCompilation": "no", "Title": "Parametric And Resistant Outlier DYtection", "Description": "routines for univariate and multivariate outlier detection with a focus on parametric methods, but support for some methods based on resistant statistics", "biocViews": [ "MultipleComparison", "Software" ], "Author": "VJ Carey ", "Maintainer": "VJ Carey ", "source.ver": "src/contrib/parody_1.32.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/parody_1.32.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/parody_1.32.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/parody_1.32.0.tgz", "vignettes": [ "vignettes/parody/inst/doc/parody.pdf" ], "vignetteTitles": [ "parody: parametric and resistant outlier detection" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/parody/inst/doc/parody.R" ], "dependsOnMe": [ "arrayMvout", "flowQ" ] }, "Path2PPI": { "Package": "Path2PPI", "Version": "1.4.0", "Depends": [ "R (>= 3.2.1)", "igraph (>= 1.0.1)", "methods" ], "Suggests": [ "knitr", "rmarkdown", "RUnit", "BiocGenerics", "BiocStyle" ], "License": "GPL (>= 2)", "MD5sum": "7b32f0f1f4b75278afe5ac51c0805cfa", "NeedsCompilation": "no", "Title": "Prediction of pathway-related protein-protein interaction networks", "Description": "Package to predict protein-protein interaction (PPI) networks in target organisms for which only a view information about PPIs is available. Path2PPI predicts PPI networks based on sets of proteins which can belong to a certain pathway from well-established model organisms. It helps to combine and transfer information of a certain pathway or biological process from several reference organisms to one target organism. Path2PPI only depends on the sequence similarity of the involved proteins.", "biocViews": [ "Network", "NetworkInference", "Pathways", "Proteomics", "Software", "SystemsBiology" ], "Author": "Oliver Philipp [aut, cre], Ina Koch [ctb]", "Maintainer": "Oliver Philipp ", "URL": "http://www.bioinformatik.uni-frankfurt.de/", "VignetteBuilder": "knitr", "source.ver": "src/contrib/Path2PPI_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Path2PPI_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Path2PPI_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Path2PPI_1.4.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Path2PPI/inst/doc/Path2PPI-tutorial.R" ], "htmlDocs": [ "vignettes/Path2PPI/inst/doc/Path2PPI-tutorial.html" ], "htmlTitles": [ "Path2PPI - A brief tutorial" ] }, "pathifier": { "Package": "pathifier", "Version": "1.12.0", "Imports": [ "R.oo", "princurve" ], "License": "Artistic-1.0", "MD5sum": "49ffb4a63eaa6c342f1f750e122c8f5d", "NeedsCompilation": "no", "Title": "Quantify deregulation of pathways in cancer", "Description": "Pathifier is an algorithm that infers pathway deregulation scores for each tumor sample on the basis of expression data. This score is determined, in a context-specific manner, for every particular dataset and type of cancer that is being investigated. The algorithm transforms gene-level information into pathway-level information, generating a compact and biologically relevant representation of each sample.", "biocViews": [ "Network", "Software" ], "Author": "Yotam Drier", "Maintainer": "Assif Yitzhaky ", "source.ver": "src/contrib/pathifier_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/pathifier_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/pathifier_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/pathifier_1.12.0.tgz", "vignettes": [ "vignettes/pathifier/inst/doc/Overview.pdf" ], "vignetteTitles": [ "Quantify deregulation of pathways in cancer" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/pathifier/inst/doc/Overview.R" ] }, "PathNet": { "Package": "PathNet", "Version": "1.14.0", "Depends": [ "R (>= 1.14.0)" ], "Suggests": [ "PathNetData", "RUnit", "BiocGenerics" ], "License": "GPL-3", "MD5sum": "d5015e0ed885989e1252a561858a1121", "NeedsCompilation": "no", "Title": "An R package for pathway analysis using topological information", "Description": "PathNet uses topological information present in pathways and differential expression levels of genes (obtained from microarray experiment) to identify pathways that are 1) significantly enriched and 2) associated with each other in the context of differential expression. The algorithm is described in: PathNet: A tool for pathway analysis using topological information. Dutta B, Wallqvist A, and Reifman J. Source Code for Biology and Medicine 2012 Sep 24;7(1):10.", "biocViews": [ "DifferentialExpression", "KEGG", "MultipleComparison", "Network", "NetworkEnrichment", "Pathways", "Software" ], "Author": "Bhaskar Dutta , Anders Wallqvist , and Jaques Reifman ", "Maintainer": "Jason B. Smith ", "source.ver": "src/contrib/PathNet_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/PathNet_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/PathNet_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/PathNet_1.14.0.tgz", "vignettes": [ "vignettes/PathNet/inst/doc/PathNet.pdf" ], "vignetteTitles": [ "PathNet" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/PathNet/inst/doc/PathNet.R" ] }, "PathoStat": { "Package": "PathoStat", "Version": "1.0.0", "Depends": [ "R (>= 3.3.1)" ], "Imports": [ "MCMCpack", "limma", "corpcor", "rmarkdown", "knitr", "pander", "matrixStats", "reshape2", "scales", "ggplot2", "rentrez", "BatchQC", "DT", "gtools", "tidyr", "plyr", "dplyr", "ape", "phyloseq", "shiny", "grDevices", "stats", "methods", "XML", "graphics", "utils", "alluvial", "BiocStyle" ], "Suggests": [ "testthat" ], "License": "GPL (>= 2)", "MD5sum": "9fe8f20484ea870710157b5e0bf532de", "NeedsCompilation": "no", "Title": "PathoStat Statistical Microbiome Analysis Package", "Description": "The purpose of this package is to perform Statistical Microbiome Analysis on metagenomics results from sequencing data samples. In particular, it supports analyses on the PathoScope generated report files. PathoStat provides various functionalities including Relative Abundance charts, Diversity estimates and plots, tests of Differential Abundance, Time Series visualization, and Core OTU analysis.", "biocViews": [ "GraphAndNetwork", "Metagenomics", "Microarray", "Microbiome", "PatternLogic", "PrincipalComponent", "RNASeq", "Sequencing", "Software", "Visualization" ], "Author": "Solaiappan Manimaran , Matthew Bendall , Sandro Valenzuela Diaz , Eduardo Castro , Tyler Faits , W. Evan Johnson ", "Maintainer": "Solaiappan Manimaran ", "URL": "https://github.com/mani2012/PathoStat", "SystemRequirements": "pandoc (http://pandoc.org/installing.html) for generating reports from markdown files.", "VignetteBuilder": "knitr", "BugReports": "https://github.com/mani2012/PathoStat/issues", "source.ver": "src/contrib/PathoStat_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/PathoStat_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/PathoStat_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/PathoStat_1.0.0.tgz", "vignettes": [ "vignettes/PathoStat/inst/doc/PathoStatUserManual.pdf" ], "vignetteTitles": [ "PathoStatUserManual" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/PathoStat/inst/doc/PathoStatAdvanced.R", "vignettes/PathoStat/inst/doc/PathoStatUserManual.R" ], "htmlDocs": [ "vignettes/PathoStat/inst/doc/PathoStatAdvanced.html", "vignettes/PathoStat/inst/doc/PathoStatIntro.html" ], "htmlTitles": [ "PathoStatAdvanced", "PathoStatIntro" ] }, "pathRender": { "Package": "pathRender", "Version": "1.42.0", "Depends": [ "graph", "Rgraphviz", "RColorBrewer", "cMAP", "AnnotationDbi", "methods", "stats4" ], "Suggests": [ "ALL", "hgu95av2.db" ], "License": "LGPL", "MD5sum": "cdd69b69be2ec05a0840200e6fc771c4", "NeedsCompilation": "no", "Title": "Render molecular pathways", "Description": "build graphs from pathway databases, render them by Rgraphviz.", "biocViews": [ "GraphAndNetwork", "Pathways", "Software", "Visualization" ], "Author": "Li Long ", "Maintainer": "Vince Carey ", "URL": "http://www.bioconductor.org", "source.ver": "src/contrib/pathRender_1.42.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/pathRender_1.42.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/pathRender_1.42.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/pathRender_1.42.0.tgz", "vignettes": [ "vignettes/pathRender/inst/doc/pathRender.pdf", "vignettes/pathRender/inst/doc/plotExG.pdf" ], "vignetteTitles": [ "pathRender overview", "pathway graphs colored by expression map" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/pathRender/inst/doc/pathRender.R", "vignettes/pathRender/inst/doc/plotExG.R" ] }, "pathVar": { "Package": "pathVar", "Version": "1.4.0", "Depends": [ "R (>= 3.3.0)", "methods", "ggplot2", "gridExtra" ], "Imports": [ "EMT", "mclust", "Matching", "data.table", "stats", "grDevices", "graphics", "utils" ], "License": "LGPL (>= 2.0)", "MD5sum": "8338070aa7ed7c751ef930fe3fab6767", "NeedsCompilation": "no", "Title": "Methods to Find Pathways with Significantly Different Variability", "Description": "This package contains the functions to find the pathways that have significantly different variability than a reference gene set. It also finds the categories from this pathway that are significant where each category is a cluster of genes. The genes are separated into clusters by their level of variability.", "biocViews": [ "GeneSetEnrichment", "GeneticVariability", "Pathways", "Software" ], "Author": "Laurence de Torrente, Samuel Zimmerman, Jessica Mar", "Maintainer": "Samuel Zimmerman ", "source.ver": "src/contrib/pathVar_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/pathVar_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/pathVar_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/pathVar_1.4.0.tgz", "vignettes": [ "vignettes/pathVar/inst/doc/pathVar.pdf" ], "vignetteTitles": [ "Tutorial on How to Use the Functions in the \\texttt{PathVar} Package" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/pathVar/inst/doc/pathVar.R" ] }, "pathview": { "Package": "pathview", "Version": "1.14.0", "Depends": [ "R (>= 2.10)", "org.Hs.eg.db" ], "Imports": [ "KEGGgraph", "XML", "Rgraphviz", "graph", "png", "AnnotationDbi", "KEGGREST", "methods", "utils" ], "Suggests": [ "gage", "org.Mm.eg.db", "RUnit", "BiocGenerics" ], "License": "GPL (>=3.0)", "MD5sum": "fc905814ccfd8ef17491c88a857b13b6", "NeedsCompilation": "no", "Title": "a tool set for pathway based data integration and visualization", "Description": "Pathview is a tool set for pathway based data integration and visualization. It maps and renders a wide variety of biological data on relevant pathway graphs. All users need is to supply their data and specify the target pathway. Pathview automatically downloads the pathway graph data, parses the data file, maps user data to the pathway, and render pathway graph with the mapped data. In addition, Pathview also seamlessly integrates with pathway and gene set (enrichment) analysis tools for large-scale and fully automated analysis.", "biocViews": [ "DifferentialExpression", "GeneExpression", "GeneSetEnrichment", "Genetics", "GraphAndNetwork", "Metabolomics", "Microarray", "Pathways", "Proteomics", "RNASeq", "Sequencing", "Software", "SystemsBiology", "Visualization" ], "Author": "Weijun Luo", "Maintainer": "Weijun Luo ", "URL": "http://pathview.uncc.edu/", "source.ver": "src/contrib/pathview_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/pathview_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/pathview_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/pathview_1.14.0.tgz", "vignettes": [ "vignettes/pathview/inst/doc/pathview.pdf" ], "vignetteTitles": [ "Pathview: pathway based data integration and visualization" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/pathview/inst/doc/pathview.R" ], "dependsOnMe": [ "EGSEA", "EnrichmentBrowser" ], "importsMe": [ "CompGO", "TCGAbiolinks" ], "suggestsMe": [ "clusterProfiler", "gage", "gageData" ] }, "paxtoolsr": { "Package": "paxtoolsr", "Version": "1.8.0", "Depends": [ "R (>= 3.2)", "rJava (>= 0.9-4)", "XML" ], "Imports": [ "httr", "igraph", "plyr", "rjson", "R.utils", "data.table" ], "Suggests": [ "testthat", "knitr", "BiocStyle", "rmarkdown", "RColorBrewer", "biomaRt", "estrogen", "affy", "hgu95av2", "hgu95av2cdf", "limma", "foreach", "doSNOW", "parallel" ], "License": "LGPL-3", "MD5sum": "46a3efc59b0b21c22f1a7de5286e1b66", "NeedsCompilation": "no", "Title": "PaxtoolsR: Access Pathways from Multiple Databases through BioPAX and Pathway Commons", "Description": "The package provides a set of R functions for interacting with BioPAX OWL files using Paxtools and the querying Pathway Commons (PC) molecular interaction database that are hosted by the Computational Biology Center at Memorial Sloan-Kettering Cancer Center (MSKCC). Pathway Commons databases include: BIND, BioGRID, CORUM, CTD, DIP, DrugBank, HPRD, HumanCyc, IntAct, KEGG, MirTarBase, Panther, PhosphoSitePlus, Reactome, RECON, TRANSFAC.", "biocViews": [ "GeneSetEnrichment", "GraphAndNetwork", "KEGG", "Network", "NetworkEnrichment", "Pathways", "Reactome", "Software", "SystemsBiology" ], "Author": "Augustin Luna", "Maintainer": "Augustin Luna ", "URL": "https://github.com/BioPAX/paxtoolsr", "SystemRequirements": "Java (>= 1.6)", "VignetteBuilder": "knitr", "source.ver": "src/contrib/paxtoolsr_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/paxtoolsr_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/paxtoolsr_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/paxtoolsr_1.8.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/paxtoolsr/inst/doc/using_paxtoolsr.R" ], "htmlDocs": [ "vignettes/paxtoolsr/inst/doc/using_paxtoolsr.html" ], "htmlTitles": [ "Using PaxtoolsR" ], "suggestsMe": [ "RCy3" ] }, "Pbase": { "Package": "Pbase", "Version": "0.14.0", "Depends": [ "R (>= 2.10)", "methods", "BiocGenerics", "Rcpp", "Gviz" ], "Imports": [ "cleaver (>= 1.3.6)", "Biobase", "Biostrings", "IRanges", "S4Vectors", "mzID", "mzR (>= 1.99.1)", "MSnbase (>= 1.15.5)", "Pviz", "biomaRt", "GenomicRanges", "rtracklayer" ], "Suggests": [ "testthat (>= 0.8)", "ggplot2", "BSgenome.Hsapiens.NCBI.GRCh38", "TxDb.Hsapiens.UCSC.hg38.knownGene", "AnnotationHub", "knitr", "rmarkdown", "BiocStyle" ], "License": "GPL-3", "MD5sum": "53ea5a9082b6154943596ecba646587f", "NeedsCompilation": "no", "Title": "Manipulating and exploring protein and proteomics data", "Description": "A set of classes and functions to investigate and understand protein sequence data in the context of a proteomics experiment.", "biocViews": [ "DataImport", "DataRepresentation", "Infrastructure", "MassSpectrometry", "Proteomics", "Software", "Visualization" ], "Author": "Laurent Gatto [aut], Sebastian Gibb [aut, cre]", "Maintainer": "Sebastian Gibb , Laurent Gatto ", "URL": "https://github.com/ComputationalProteomicsUnit/Pbase", "VignetteBuilder": "knitr", "BugReports": "https://github.com/ComputationalProteomicsUnit/Pbase/issues", "source.ver": "src/contrib/Pbase_0.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Pbase_0.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Pbase_0.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Pbase_0.14.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Pbase/inst/doc/ensucsc.R", "vignettes/Pbase/inst/doc/mapping.R", "vignettes/Pbase/inst/doc/Pbase-data.R" ], "htmlDocs": [ "vignettes/Pbase/inst/doc/ensucsc.html", "vignettes/Pbase/inst/doc/mapping.html", "vignettes/Pbase/inst/doc/Pbase-data.html" ], "htmlTitles": [ "Ensembl and UCSC mapping", "Mapping experimental MS data to genomic coordinates", "Pbase data" ] }, "pbcmc": { "Package": "pbcmc", "Version": "1.2.2", "Depends": [ "R (>= 3.3.0)", "genefu" ], "Imports": [ "Biobase", "BiocGenerics", "BiocParallel (>= 1.3.13)", "parallel", "reshape2", "grid", "utils", "cowplot", "methods", "limma", "ggplot2", "gridExtra", "grDevices", "stats" ], "Suggests": [ "breastCancerUPP", "breastCancerNKI", "breastCancerVDX", "breastCancerTRANSBIG", "breastCancerMAINZ", "breastCancerUNT" ], "License": "GPL (>=2)", "MD5sum": "6f45013332f989dd2e25a15ba762590e", "NeedsCompilation": "no", "Title": "Permutation-Based Confidence for Molecular Classification", "Description": "The pbcmc package characterizes uncertainty assessment on gene expression classifiers, a. k. a. molecular signatures, based on a permutation test. In order to achieve this goal, synthetic simulated subjects are obtained by permutations of gene labels. Then, each synthetic subject is tested against the corresponding subtype classifier to build the null distribution. Thus, classification confidence measurement can be provided for each subject, to assist physician therapy choice. At present, it is only available for PAM50 implementation in genefu package but it can easily be extend to other molecular signatures.", "biocViews": [ "Classification", "Clustering", "DifferentialExpression", "GeneExpression", "KEGG", "Microarray", "MultipleComparison", "Normalization", "OneChannel", "QualityControl", "RNASeq", "Software", "TwoChannel", "mRNAMicroarray" ], "Author": "Cristobal Fresno, German A. Gonzalez, Andrea S. Llera and Elmer A. Fernandez", "Maintainer": "Cristobal Fresno ", "URL": "http://www.bdmg.com.ar/", "source.ver": "src/contrib/pbcmc_1.2.2.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/pbcmc_1.2.2.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/pbcmc_1.2.2.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/pbcmc_1.2.2.tgz", "vignettes": [ "vignettes/pbcmc/inst/doc/pbcmc-vignette.pdf" ], "vignetteTitles": [ "PermutationBased Confidence for Molecular Class" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/pbcmc/inst/doc/pbcmc-vignette.R" ] }, "pcaExplorer": { "Package": "pcaExplorer", "Version": "2.0.0", "Imports": [ "DESeq2", "SummarizedExperiment", "GenomicRanges", "IRanges", "S4Vectors", "genefilter", "ggplot2 (>= 2.0.0)", "d3heatmap", "scales", "NMF", "plyr", "topGO", "limma", "GOstats", "GO.db", "AnnotationDbi", "shiny (>= 0.12.0)", "shinydashboard", "shinyBS", "ggrepel", "DT", "shinyAce", "threejs", "biomaRt", "pheatmap", "knitr", "rmarkdown", "tidyr", "grDevices", "methods" ], "Suggests": [ "testthat", "BiocStyle", "airway", "org.Hs.eg.db" ], "License": "MIT + file LICENSE", "MD5sum": "9d7acdaf5b4b5e02604016edbb5edf23", "NeedsCompilation": "no", "Title": "Interactive Visualization of RNA-seq Data Using a Principal Components Approach", "Description": "This package provides functionality for interactive visualization of RNA-seq datasets based on Principal Components Analysis. The methods provided allow for quick information extraction and effective data exploration. A Shiny application encapsulates the whole analysis.", "biocViews": [ "DimensionReduction", "GUI", "PrincipalComponent", "QualityControl", "RNASeq", "ReportWriting", "Software", "Visualization" ], "Author": "Federico Marini [aut, cre]", "Maintainer": "Federico Marini ", "URL": "https://github.com/federicomarini/pcaExplorer", "VignetteBuilder": "knitr", "BugReports": "https://github.com/federicomarini/pcaExplorer/issues", "source.ver": "src/contrib/pcaExplorer_2.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/pcaExplorer_2.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/pcaExplorer_2.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/pcaExplorer_2.0.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/pcaExplorer/inst/doc/pcaExplorer.R" ], "htmlDocs": [ "vignettes/pcaExplorer/inst/doc/pcaExplorer.html" ], "htmlTitles": [ "pcaExplorer User Guide" ] }, "pcaGoPromoter": { "Package": "pcaGoPromoter", "Version": "1.18.0", "Depends": [ "R (>= 2.14.0)", "ellipse", "Biostrings" ], "Imports": [ "AnnotationDbi" ], "Suggests": [ "Rgraphviz", "GO.db", "hgu133plus2.db", "mouse4302.db", "rat2302.db", "hugene10sttranscriptcluster.db", "mogene10sttranscriptcluster.db", "pcaGoPromoter.Hs.hg19", "pcaGoPromoter.Mm.mm9", "pcaGoPromoter.Rn.rn4", "serumStimulation", "parallel" ], "License": "GPL (>= 2)", "MD5sum": "73ab312d5b0fe6b1bd750aeec6bb67d5", "NeedsCompilation": "no", "Title": "pcaGoPromoter is used to analyze DNA micro array data", "Description": "This package contains functions to ease the analyses of DNA micro arrays. It utilizes principal component analysis as the initial multivariate analysis, followed by functional interpretation of the principal component dimensions with overrepresentation analysis for GO terms and regulatory interpretations using overrepresentation analysis of predicted transcription factor binding sites with the primo algorithm.", "biocViews": [ "GO", "GeneExpression", "Microarray", "Software", "Visualization" ], "Author": "Morten Hansen, Jorgen Olsen", "Maintainer": "Morten Hansen ", "source.ver": "src/contrib/pcaGoPromoter_1.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/pcaGoPromoter_1.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/pcaGoPromoter_1.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/pcaGoPromoter_1.18.0.tgz", "vignettes": [ "vignettes/pcaGoPromoter/inst/doc/pcaGoPromoter.pdf" ], "vignetteTitles": [ "pcaGoPromoter" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/pcaGoPromoter/inst/doc/pcaGoPromoter.R" ] }, "pcaMethods": { "Package": "pcaMethods", "Version": "1.66.0", "Depends": [ "Biobase", "methods" ], "Imports": [ "BiocGenerics", "Rcpp (>= 0.11.3)", "MASS" ], "LinkingTo": [ "Rcpp" ], "Suggests": [ "matrixStats", "lattice", "ggplot2" ], "License": "GPL (>= 3)", "Archs": "i386, x64", "MD5sum": "9667690b43d6c9cda9fc171bf138c322", "NeedsCompilation": "yes", "Title": "A collection of PCA methods", "Description": "Provides Bayesian PCA, Probabilistic PCA, Nipals PCA, Inverse Non-Linear PCA and the conventional SVD PCA. A cluster based method for missing value estimation is included for comparison. BPCA, PPCA and NipalsPCA may be used to perform PCA on incomplete data as well as for accurate missing value estimation. A set of methods for printing and plotting the results is also provided. All PCA methods make use of the same data structure (pcaRes) to provide a common interface to the PCA results. Initiated at the Max-Planck Institute for Molecular Plant Physiology, Golm, Germany.", "biocViews": [ "Bayesian", "Software" ], "Author": "Wolfram Stacklies, Henning Redestig, Kevin Wright", "Maintainer": "Henning Redestig ", "URL": "https://github.com/hredestig/pcamethods", "SystemRequirements": "Rcpp", "BugReports": "https://github.com/hredestig/pcamethods/issues", "source.ver": "src/contrib/pcaMethods_1.66.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/pcaMethods_1.66.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/pcaMethods_1.66.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/pcaMethods_1.66.0.tgz", "vignettes": [ "vignettes/pcaMethods/inst/doc/missingValues.pdf", "vignettes/pcaMethods/inst/doc/outliers.pdf", "vignettes/pcaMethods/inst/doc/pcaMethods.pdf" ], "vignetteTitles": [ "Missing value imputation", "Data with outliers", "Introduction" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/pcaMethods/inst/doc/missingValues.R", "vignettes/pcaMethods/inst/doc/outliers.R", "vignettes/pcaMethods/inst/doc/pcaMethods.R" ], "dependsOnMe": [ "DeconRNASeq" ], "importsMe": [ "CompGO", "DAPAR", "MSnbase", "PanVizGenerator", "scde", "SomaticSignatures" ], "suggestsMe": [ "mtbls2" ] }, "PCAN": { "Package": "PCAN", "Version": "1.2.1", "Depends": [ "R (>= 3.3)", "BiocParallel" ], "Imports": [ "grDevices", "stats" ], "Suggests": [ "BiocStyle", "knitr", "rmarkdown", "reactome.db", "STRINGdb" ], "License": "CC BY-NC-ND 4.0", "MD5sum": "34195cd634bdcc2761ba1d16eacd69cd", "NeedsCompilation": "no", "Title": "Phenotype Consensus ANalysis (PCAN)", "Description": "Phenotypes comparison based on a pathway consensus approach. Assess the relationship between candidate genes and a set of phenotypes based on additional genes related to the candidate (e.g. Pathways or network neighbors).", "biocViews": [ "Annotation", "FunctionalPrediction", "Genetics", "Network", "Pathways", "Sequencing", "Software", "VariantAnnotation" ], "Author": "Matthew Page and Patrice Godard", "Maintainer": "Matthew Page and Patrice Godard ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/PCAN_1.2.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/PCAN_1.2.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/PCAN_1.2.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/PCAN_1.2.1.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/PCAN/inst/doc/PCAN.R" ], "htmlDocs": [ "vignettes/PCAN/inst/doc/PCAN.html" ], "htmlTitles": [ "Assessing gene relevance for a set of phenotypes" ] }, "pcot2": { "Package": "pcot2", "Version": "1.42.0", "Depends": [ "R (>= 2.0.0)", "grDevices", "Biobase", "amap" ], "Suggests": [ "multtest", "hu6800.db", "KEGG.db", "mvtnorm" ], "License": "GPL (>= 2)", "MD5sum": "17d1990503b89346e8db299e8b23fc22", "NeedsCompilation": "no", "Title": "Principal Coordinates and Hotelling's T-Square method", "Description": "PCOT2 is a permutation-based method for investigating changes in the activity of multi-gene networks. It utilizes inter-gene correlation information to detect significant alterations in gene network activities. Currently it can be applied to two-sample comparisons.", "biocViews": [ "DifferentialExpression", "GeneExpression", "KEGG", "Microarray", "Network", "Software" ], "Author": "Sarah Song, Mik Black", "Maintainer": "Sarah Song ", "source.ver": "src/contrib/pcot2_1.42.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/pcot2_1.42.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/pcot2_1.42.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/pcot2_1.42.0.tgz", "vignettes": [ "vignettes/pcot2/inst/doc/pcot2.pdf" ], "vignetteTitles": [ "PCOT2 Vignette" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/pcot2/inst/doc/pcot2.R" ] }, "PCpheno": { "Package": "PCpheno", "Version": "1.36.0", "Depends": [ "R (>= 2.10)", "Category", "ScISI (>= 1.3.0)", "SLGI", "ppiStats", "ppiData", "annotate (>= 1.17.4)" ], "Imports": [ "AnnotationDbi", "Biobase", "Category", "GO.db", "graph", "graphics", "GSEABase", "KEGG.db", "methods", "ScISI", "stats", "stats4" ], "Suggests": [ "KEGG.db", "GO.db", "org.Sc.sgd.db" ], "License": "Artistic-2.0", "MD5sum": "3be6cde384aa23fe731833611e0cc12e", "NeedsCompilation": "no", "Title": "Phenotypes and cellular organizational units", "Description": "Tools to integrate, annotate, and link phenotypes to cellular organizational units such as protein complexes and pathways.", "biocViews": [ "GraphAndNetwork", "Network", "Proteomics", "Software" ], "Author": "Nolwenn Le Meur and Robert Gentleman", "Maintainer": "Nolwenn Le Meur ", "source.ver": "src/contrib/PCpheno_1.36.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/PCpheno_1.36.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/PCpheno_1.36.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/PCpheno_1.36.0.tgz", "vignettes": [ "vignettes/PCpheno/inst/doc/PCpheno.pdf" ], "vignetteTitles": [ "PCpheno Vignette" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/PCpheno/inst/doc/PCpheno.R" ] }, "pdInfoBuilder": { "Package": "pdInfoBuilder", "Version": "1.38.0", "Depends": [ "R (>= 3.2.0)", "methods", "Biobase (>= 2.27.3)", "RSQLite (>= 1.0.0)", "affxparser (>= 1.39.4)", "oligo (>= 1.31.5)" ], "Imports": [ "Biostrings (>= 2.35.12)", "BiocGenerics (>= 0.13.11)", "DBI (>= 0.3.1)", "IRanges (>= 2.1.43)", "oligoClasses (>= 1.29.6)", "S4Vectors (>= 0.5.22)" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "8ea4b76fca1ddd05f6a9531b8e03b0c7", "NeedsCompilation": "yes", "Title": "Platform Design Information Package Builder", "Description": "Builds platform design information packages. These consist of a SQLite database containing feature-level data such as x, y position on chip and featureSet ID. The database also incorporates featureSet-level annotation data. The products of this packages are used by the oligo pkg.", "biocViews": [ "Annotation", "Infrastructure", "Software" ], "Author": "Seth Falcon, Vince Carey, Matt Settles, Kristof de Beuf, Benilton Carvalho", "Maintainer": "Benilton Carvalho ", "source.ver": "src/contrib/pdInfoBuilder_1.38.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/pdInfoBuilder_1.38.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/pdInfoBuilder_1.38.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/pdInfoBuilder_1.38.0.tgz", "vignettes": [ "vignettes/pdInfoBuilder/inst/doc/BuildingPDInfoPkgs.pdf", "vignettes/pdInfoBuilder/inst/doc/howto-AffymetrixMapping.pdf" ], "vignetteTitles": [ "Building Annotation Packages with pdInfoBuilder for Use with the oligo Package", "PDInfo Package Building Affymetrix Mapping Chips" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/pdInfoBuilder/inst/doc/howto-AffymetrixMapping.R" ], "suggestsMe": [ "maqcExpression4plex" ] }, "pdmclass": { "Package": "pdmclass", "Version": "1.46.0", "Depends": [ "Biobase (>= 1.4.22)", "R (>= 1.9.0)", "fibroEset", "mda" ], "License": "Artistic-2.0", "MD5sum": "bb36974366c54708bf205d3ddcb60e75", "NeedsCompilation": "no", "Title": "Classification of Microarray Samples using Penalized Discriminant Methods", "Description": "This package can be used to classify microarray data using one of three penalized regression methods; partial least squares, principal components regression, or ridge regression.", "biocViews": [ "Classification", "Software" ], "Author": "James W. MacDonald, Debashis Ghosh, based in part on pls code of Mike Denham", "Maintainer": "James W. MacDonald ", "source.ver": "src/contrib/pdmclass_1.46.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/pdmclass_1.46.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/pdmclass_1.46.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/pdmclass_1.46.0.tgz", "vignettes": [ "vignettes/pdmclass/inst/doc/pdmclass.pdf" ], "vignetteTitles": [ "pdmclass Overview" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/pdmclass/inst/doc/pdmclass.R" ], "suggestsMe": [ "oneChannelGUI" ] }, "PECA": { "Package": "PECA", "Version": "1.10.0", "Depends": [ "R (>= 3.3)" ], "Imports": [ "ROTS", "limma", "affy", "genefilter", "preprocessCore", "aroma.affymetrix", "aroma.core" ], "Suggests": [ "SpikeIn" ], "License": "GPL (>= 2)", "MD5sum": "dc33f865eabf38ec70e84162a6fde333", "NeedsCompilation": "no", "Title": "Probe-level Expression Change Averaging", "Description": "Calculates Probe-level Expression Change Averages (PECA) to identify differential expression in Affymetrix gene expression microarray studies or in proteomic studies using peptide-level mesurements respectively.", "biocViews": [ "DifferentialExpression", "DifferentialSplicing", "ExonArray", "GeneExpression", "Microarray", "Proteomics", "Software" ], "Author": "Tomi Suomi, Jukka Hiissa, Laura L. Elo", "Maintainer": "Tomi Suomi ", "source.ver": "src/contrib/PECA_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/PECA_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/PECA_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/PECA_1.10.0.tgz", "vignettes": [ "vignettes/PECA/inst/doc/PECA.pdf" ], "vignetteTitles": [ "PECA: Probe-level Expression Change Averaging" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/PECA/inst/doc/PECA.R" ] }, "pepStat": { "Package": "pepStat", "Version": "1.8.0", "Depends": [ "R (>= 3.0.0)", "Biobase", "IRanges" ], "Imports": [ "limma", "fields", "GenomicRanges", "ggplot2", "plyr", "tools", "methods", "data.table" ], "Suggests": [ "pepDat", "Pviz", "knitr", "shiny" ], "License": "Artistic-2.0", "MD5sum": "b5624791925b22884287b8501e4ff05c", "NeedsCompilation": "no", "Title": "Statistical analysis of peptide microarrays", "Description": "Statistical analysis of peptide microarrays", "biocViews": [ "Microarray", "Preprocessing", "Software" ], "Author": "Raphael Gottardo, Gregory C Imholte, Renan Sauteraud, Mike Jiang", "Maintainer": "Gregory C Imholte ", "URL": "https://github.com/RGLab/pepStat", "VignetteBuilder": "knitr", "source.ver": "src/contrib/pepStat_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/pepStat_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/pepStat_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/pepStat_1.8.0.tgz", "vignettes": [ "vignettes/pepStat/inst/doc/pepStat.pdf" ], "vignetteTitles": [ "Full peptide microarray analysis" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/pepStat/inst/doc/pepStat.R" ] }, "pepXMLTab": { "Package": "pepXMLTab", "Version": "1.8.0", "Depends": [ "R (>= 3.0.1)" ], "Imports": [ "XML(>= 3.98-1.1)" ], "Suggests": [ "RUnit", "BiocGenerics" ], "License": "Artistic-2.0", "MD5sum": "9a77d9eb50479aae904e420fb057a210", "NeedsCompilation": "no", "Title": "Parsing pepXML files and filter based on peptide FDR.", "Description": "Parsing pepXML files based one XML package. The package tries to handle pepXML files generated from different softwares. The output will be a peptide-spectrum-matching tabular file. The package also provide function to filter the PSMs based on FDR.", "biocViews": [ "MassSpectrometry", "Proteomics", "Software" ], "Author": "Xiaojing Wang", "Maintainer": "Xiaojing Wang ", "source.ver": "src/contrib/pepXMLTab_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/pepXMLTab_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/pepXMLTab_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/pepXMLTab_1.8.0.tgz", "vignettes": [ "vignettes/pepXMLTab/inst/doc/pepXMLTab.pdf" ], "vignetteTitles": [ "Introduction to pepXMLTab" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/pepXMLTab/inst/doc/pepXMLTab.R" ] }, "PGA": { "Package": "PGA", "Version": "1.4.0", "Depends": [ "R (>= 3.0.1)", "IRanges", "GenomicRanges", "Biostrings (>= 2.26.3)", "data.table", "rTANDEM" ], "Imports": [ "S4Vectors (>= 0.9.25)", "Rsamtools (>= 1.10.2)", "GenomicFeatures (>= 1.19.8)", "biomaRt (>= 2.17.1)", "stringr", "RCurl", "Nozzle.R1", "VariantAnnotation (>= 1.7.28)", "rtracklayer", "RSQLite", "ggplot2", "AnnotationDbi", "customProDB (>= 1.7.0)", "pheatmap" ], "Suggests": [ "BSgenome.Hsapiens.UCSC.hg19", "RUnit", "BiocGenerics", "BiocStyle", "knitr", "R.utils" ], "License": "GPL-2", "MD5sum": "61632d04bb70cbcc5896b1a519655453", "NeedsCompilation": "no", "Title": "An package for identification of novel peptides by customized database derived from RNA-Seq", "Description": "This package provides functions for construction of customized protein databases based on RNA-Seq data with/without genome guided, database searching, post-processing and report generation. This kind of customized protein database includes both the reference database (such as Refseq or ENSEMBL) and the novel peptide sequences form RNA-Seq data.", "biocViews": [ "MassSpectrometry", "Proteomics", "RNASeq", "ReportWriting", "Sequencing", "Software" ], "Author": "Shaohang Xu, Bo Wen", "Maintainer": "Bo Wen , Shaohang Xu ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/PGA_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/PGA_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/PGA_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/PGA_1.4.0.tgz", "vignettes": [ "vignettes/PGA/inst/doc/PGA.pdf" ], "vignetteTitles": [ "PGA tutorial" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/PGA/inst/doc/PGA.R" ] }, "PGSEA": { "Package": "PGSEA", "Version": "1.48.0", "Depends": [ "R (>= 2.10)", "GO.db", "KEGG.db", "AnnotationDbi", "annaffy", "methods", "Biobase (>= 2.5.5)" ], "Suggests": [ "GSEABase", "GEOquery", "org.Hs.eg.db", "hgu95av2.db", "limma" ], "License": "GPL-2", "MD5sum": "ceef171413c103c5a0db022fc49d5c03", "NeedsCompilation": "no", "Title": "Parametric Gene Set Enrichment Analysis", "Description": "Parametric Analysis of Gene Set Enrichment", "biocViews": [ "Microarray", "Software" ], "Author": "Kyle Furge and Karl Dykema ", "Maintainer": "Karl Dykema ", "source.ver": "src/contrib/PGSEA_1.48.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/PGSEA_1.48.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/PGSEA_1.48.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/PGSEA_1.48.0.tgz", "vignettes": [ "vignettes/PGSEA/inst/doc/PGSEA.pdf", "vignettes/PGSEA/inst/doc/PGSEA2.pdf" ], "vignetteTitles": [ "HOWTO: PGSEA", "HOWTO: PGSEA Example Workflow" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/PGSEA/inst/doc/PGSEA.R", "vignettes/PGSEA/inst/doc/PGSEA2.R" ], "dependsOnMe": [ "GeneExpressionSignature" ], "suggestsMe": [ "gskb" ] }, "PharmacoGx": { "Package": "PharmacoGx", "Version": "1.4.3", "Depends": [ "R (>= 3.3)" ], "Imports": [ "Biobase", "piano", "magicaxis", "RColorBrewer", "parallel", "caTools", "methods", "downloader", "stats", "utils", "graphics", "grDevices", "lsa" ], "Suggests": [ "xtable" ], "License": "Artistic-2.0", "MD5sum": "9e79c63ea7e7f0ac582379f5629e5655", "NeedsCompilation": "no", "Title": "Analysis of Large-Scale Pharmacogenomic Data", "Description": "Contains a set of functions to perform large-scale analysis of pharmacogenomic data.", "biocViews": [ "Classification", "GeneExpression", "Pharmacogenetics", "Pharmacogenomics", "Software" ], "Author": "Petr Smirnov, Zhaleh Safikhani, Mark Freeman, Benjamin Haibe-Kains", "Maintainer": "Benjamin Haibe-Kains ", "BugReports": "https://github.com/bhklab/PharmacoGx/issues", "source.ver": "src/contrib/PharmacoGx_1.4.3.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/PharmacoGx_1.4.3.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/PharmacoGx_1.4.3.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/PharmacoGx_1.4.3.tgz", "vignettes": [ "vignettes/PharmacoGx/inst/doc/CreatingPharmacoSet.pdf", "vignettes/PharmacoGx/inst/doc/PharmacoGx.pdf" ], "vignetteTitles": [ "Creating a PharmacoSet object", "PharmacoGx: an R package for analysis of large pharmacogenomic datasets" ], "hasREADME": true, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/PharmacoGx/inst/doc/CreatingPharmacoSet.R", "vignettes/PharmacoGx/inst/doc/PharmacoGx.R" ] }, "phenoDist": { "Package": "phenoDist", "Version": "1.22.0", "Depends": [ "R (>= 2.9.0)", "imageHTS", "e1071" ], "Suggests": [ "GOstats", "MASS" ], "License": "LGPL-2.1", "MD5sum": "c3a421f54a98d02e01306227e72cb79f", "NeedsCompilation": "no", "Title": "Phenotypic distance measures", "Description": "PhenoDist is designed for measuring phenotypic distance in image-based high-throughput screening, in order to identify strong phenotypes and to group treatments into functional clusters.", "biocViews": [ "CellBasedAssays", "Software" ], "Author": "Xian Zhang, Gregoire Pau, Wolfgang Huber, Michael Boutros", "Maintainer": "Xian Zhang ", "URL": "http://www.dkfz.de/signaling, http://www.embl.de/research/units/genome_biology/huber/", "source.ver": "src/contrib/phenoDist_1.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/phenoDist_1.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/phenoDist_1.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/phenoDist_1.22.0.tgz", "vignettes": [ "vignettes/phenoDist/inst/doc/phenoDist.pdf" ], "vignetteTitles": [ "Introduction to phenoDist" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/phenoDist/inst/doc/phenoDist.R" ] }, "phenoTest": { "Package": "phenoTest", "Version": "1.23.1", "Depends": [ "R (>= 2.12.0)", "Biobase", "methods", "annotate", "Heatplus", "BMA", "ggplot2" ], "Imports": [ "survival", "limma", "Hmisc", "gplots", "Category", "AnnotationDbi", "hopach", "biomaRt", "GSEABase", "genefilter", "xtable", "annotate", "mgcv", "SNPchip", "hgu133a.db", "HTSanalyzeR", "ellipse" ], "Suggests": [ "GSEABase", "KEGG.db", "GO.db" ], "Enhances": [ "parallel", "org.Ce.eg.db", "org.Mm.eg.db", "org.Rn.eg.db", "org.Hs.eg.db", "org.Dm.eg.db" ], "License": "GPL (>=2)", "MD5sum": "afdc03e516f4ba27d1b78f5fa000fc0e", "NeedsCompilation": "no", "Title": "Tools to test association between gene expression and phenotype in a way that is efficient, structured, fast and scalable. We also provide tools to do GSEA (Gene set enrichment analysis) and copy number variation.", "Description": "Tools to test correlation between gene expression and phenotype in a way that is efficient, structured, fast and scalable. GSEA is also provided.", "biocViews": [ "Classification", "Clustering", "DifferentialExpression", "Microarray", "MultipleComparison", "Software" ], "Author": "Evarist Planet", "Maintainer": "Evarist Planet ", "source.ver": "src/contrib/phenoTest_1.23.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/phenoTest_1.23.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/phenoTest_1.23.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/phenoTest_1.23.1.tgz", "vignettes": [ "vignettes/phenoTest/inst/doc/phenoTest.pdf" ], "vignetteTitles": [ "Manual for the phenoTest library" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/phenoTest/inst/doc/phenoTest.R" ], "importsMe": [ "canceR" ] }, "PhenStat": { "Package": "PhenStat", "Version": "2.8.0", "Depends": [ "R (>= 2.3.0)" ], "Imports": [ "methods", "car", "nlme", "nortest", "MASS", "logistf" ], "Suggests": [ "RUnit", "BiocGenerics" ], "License": "file LICENSE", "MD5sum": "d4ccfbb0ba958bbdcac4544f61d56bd5", "NeedsCompilation": "no", "Title": "Statistical analysis of phenotypic data", "Description": "Package contains methods for statistical analysis of phenotypic data.", "Author": "Natalja Kurbatova, Natasha Karp, Jeremy Mason", "Maintainer": "Jeremy Mason ", "source.ver": "src/contrib/PhenStat_2.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/PhenStat_2.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/PhenStat_2.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/PhenStat_2.8.0.tgz", "vignettes": [ "vignettes/PhenStat/inst/doc/PhenStat.pdf", "vignettes/PhenStat/inst/doc/PhenStatUsersGuide.pdf" ], "vignetteTitles": [ "PhenStat Vignette", "PhenStatUsersGuide.pdf" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/PhenStat/inst/doc/PhenStat.R" ], "biocViews": [ "Software" ] }, "philr": { "Package": "philr", "Version": "1.0.0", "Imports": [ "ape", "phangorn", "tidyr", "ggplot2", "ggtree" ], "Suggests": [ "testthat", "knitr", "rmarkdown", "BiocStyle", "phyloseq", "glmnet", "dplyr" ], "License": "GPL-3", "MD5sum": "9dc4564b613c254061e8257e9733f0a3", "NeedsCompilation": "no", "Title": "Phylogenetic partitioning based ILR transform for metagenomics data", "Description": "PhILR is short for Phylogenetic Isometric Log-Ratio Transform. This package provides functions for the analysis of compositional data (e.g., data representing proportions of different variables/parts). Specifically this package allows analysis of compositional data where the parts can be related through a phylogenetic tree (as is common in microbiota survey data) and makes available the Isometric Log Ratio transform built from the phylogenetic tree and utilizing a weighted reference measure.", "biocViews": [ "Metagenomics", "Microbiome", "Sequencing", "Software" ], "Author": "Justin Silverman", "Maintainer": "Justin Silverman ", "URL": "https://github.com/jsilve24/philr", "VignetteBuilder": "knitr", "BugReports": "https://github.com/jsilve24/philr/issues", "source.ver": "src/contrib/philr_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/philr_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/philr_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/philr_1.0.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/philr/inst/doc/philr-intro.R" ], "htmlDocs": [ "vignettes/philr/inst/doc/philr-intro.html" ], "htmlTitles": [ "Introduction to PhILR" ] }, "phyloseq": { "Package": "phyloseq", "Version": "1.19.1", "Depends": [ "R (>= 3.3.0)" ], "Imports": [ "BiocGenerics (>= 0.18.0)", "ade4 (>= 1.7.4)", "ape (>= 3.4)", "biomformat (>= 1.0.0)", "Biostrings (>= 2.40.0)", "cluster (>= 2.0.4)", "data.table (>= 1.9.6)", "foreach (>= 1.4.3)", "ggplot2 (>= 2.1.0)", "igraph (>= 1.0.1)", "methods (>= 3.3.0)", "multtest (>= 2.28.0)", "plyr (>= 1.8.3)", "reshape2 (>= 1.4.1)", "scales (>= 0.4.0)", "vegan (>= 2.3.5)", "Biobase" ], "Suggests": [ "BiocStyle (>= 2.0.0)", "DESeq2 (>= 1.12.0)", "genefilter (>= 1.54)", "testthat (>= 1.0.2)", "knitr (>= 1.13)", "metagenomeSeq (>= 1.14)", "rmarkdown (>= 0.9.6)" ], "Enhances": [ "doParallel (>= 1.0.10)" ], "License": "AGPL-3", "MD5sum": "5bb158f1bbeeaae4ca3e2cb1ca08fbfd", "NeedsCompilation": "no", "Title": "Handling and analysis of high-throughput microbiome census data", "Description": "phyloseq provides a set of classes and tools to facilitate the import, storage, analysis, and graphical display of microbiome census data.", "biocViews": [ "Classification", "Clustering", "GeneticVariability", "Metagenomics", "Microbiome", "MultipleComparison", "Sequencing", "Software" ], "Author": "Paul J. McMurdie , Susan Holmes , with contributions from Gregory Jordan and Scott Chamberlain", "Maintainer": "Paul J. McMurdie ", "URL": "http://dx.plos.org/10.1371/journal.pone.0061217", "VignetteBuilder": "knitr", "BugReports": "https://github.com/joey711/phyloseq/issues", "source.ver": "src/contrib/phyloseq_1.19.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/phyloseq_1.19.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/phyloseq_1.19.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/phyloseq_1.19.1.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/phyloseq/inst/doc/phyloseq-analysis.R", "vignettes/phyloseq/inst/doc/phyloseq-basics.R", "vignettes/phyloseq/inst/doc/phyloseq-FAQ.R", "vignettes/phyloseq/inst/doc/phyloseq-mixture-models.R" ], "htmlDocs": [ "vignettes/phyloseq/inst/doc/phyloseq-analysis.html", "vignettes/phyloseq/inst/doc/phyloseq-basics.html", "vignettes/phyloseq/inst/doc/phyloseq-FAQ.html", "vignettes/phyloseq/inst/doc/phyloseq-mixture-models.html" ], "htmlTitles": [ "analysis vignette", "phyloseq basics vignette", "phyloseq Frequently Asked Questions (FAQ)", "phyloseq and DESeq2 on Colorectal Cancer Data" ], "dependsOnMe": [ "curatedMetagenomicData", "RPA" ], "importsMe": [ "PathoStat" ], "suggestsMe": [ "philr" ] }, "Pi": { "Package": "Pi", "Version": "1.2.1", "Depends": [ "XGR", "igraph", "dnet", "ggplot2", "graphics", "stats" ], "Imports": [ "Matrix", "MASS", "ggbio", "GenomicRanges", "GenomeInfoDb", "supraHex", "scales", "grDevices", "ggrepel", "ROCR", "randomForest" ], "Suggests": [ "foreach", "doParallel", "BiocStyle", "knitr", "rmarkdown", "png", "GGally", "gridExtra", "fgsea", "Gviz" ], "License": "GPL-3", "MD5sum": "2f385cbb161e8c5738165935d88c8596", "NeedsCompilation": "no", "Title": "Leveraging Genetic Evidence to Prioritise Drug Targets at the Gene, Pathway and Network Level", "Description": "Priority index or Pi is developed as a genomic-led target prioritisation system, with the focus on leveraging human genetic data to prioritise potential drug targets at the gene, pathway and network level. The long term goal is to use such information to enhance early-stage target validation. Based on evidence of disease association from genome-wide association studies (GWAS), this prioritisation system is able to generate evidence to support identification of the specific modulated genes (seed genes) that are responsible for the genetic association signal by utilising knowledge of linkage disequilibrium (co-inherited genetic variants), distance of associated variants from the gene, evidence of independent genetic association with gene expression in disease-relevant tissues, cell types and states, and evidence of physical interactions between disease-associated genetic variants and gene promoters based on genome-wide capture HiC-generated promoter interactomes in primary blood cell types. Seed genes are scored in an integrative way, quantifying the genetic influence. Scored seed genes are subsequently used as baits to rank seed genes plus additional (non-seed) genes; this is achieved by iteratively exploring the global connectivity of a gene interaction network. Genes with the highest priority are further used to identify/prioritise pathways that are significantly enriched with highly prioritised genes. Prioritised genes are also used to identify a gene network interconnecting highly prioritised genes and a minimal number of less prioritised genes (which act as linkers bringing together highly prioritised genes).", "biocViews": [ "GeneExpression", "GeneTarget", "Genetics", "GenomeWideAssociation", "GraphAndNetwork", "HiC", "LinkageDisequilibrium", "Network", "Pathways", "Software" ], "Author": "Hai Fang, the ULTRA-DD Consortium, Julian C Knight", "Maintainer": "Hai Fang ", "URL": "http://pi314.r-forge.r-project.org", "VignetteBuilder": "knitr", "BugReports": "https://github.com/hfang-bristol/Pi/issues", "source.ver": "src/contrib/Pi_1.2.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Pi_1.2.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Pi_1.2.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Pi_1.2.1.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Pi/inst/doc/Pi_vignettes.R" ], "htmlDocs": [ "vignettes/Pi/inst/doc/Pi_vignettes.html" ], "htmlTitles": [ "Pi User Manual (R/Bioconductor package)" ] }, "piano": { "Package": "piano", "Version": "1.14.5", "Depends": [ "R (>= 2.14.0)" ], "Imports": [ "BiocGenerics", "Biobase", "gplots", "igraph", "relations", "marray", "fgsea" ], "Suggests": [ "yeast2.db", "rsbml", "plotrix", "limma", "affy", "plier", "affyPLM", "gtools", "biomaRt", "snowfall", "AnnotationDbi" ], "License": "GPL (>=2)", "MD5sum": "b37c89e39ba51747590ee29b17849cbf", "NeedsCompilation": "no", "Title": "Platform for integrative analysis of omics data", "Description": "Piano performs gene set analysis using various statistical methods, from different gene level statistics and a wide range of gene-set collections. Furthermore, the Piano package contains functions for combining the results of multiple runs of gene set analyses.", "biocViews": [ "DifferentialExpression", "GeneExpression", "GeneSetEnrichment", "Microarray", "Pathways", "Preprocessing", "QualityControl", "Software", "Visualization" ], "Author": "Leif Varemo and Intawat Nookaew ", "Maintainer": "Leif Varemo ", "URL": "http://www.sysbio.se/piano", "BugReports": "https://github.com/varemo/piano/issues", "source.ver": "src/contrib/piano_1.14.5.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/piano_1.14.5.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/piano_1.14.5.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/piano_1.14.5.tgz", "vignettes": [ "vignettes/piano/inst/doc/piano-vignette.pdf" ], "vignetteTitles": [ "Piano - Platform for Integrative Analysis of Omics data" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/piano/inst/doc/piano-vignette.R" ], "importsMe": [ "PharmacoGx" ] }, "pickgene": { "Package": "pickgene", "Version": "1.46.0", "Imports": [ "graphics", "grDevices", "MASS", "stats", "utils" ], "License": "GPL (>= 2)", "MD5sum": "1f63bf4d9ecedb0404960af25171a28e", "NeedsCompilation": "no", "Title": "Adaptive Gene Picking for Microarray Expression Data Analysis", "Description": "Functions to Analyze Microarray (Gene Expression) Data.", "biocViews": [ "DifferentialExpression", "Microarray", "Software" ], "Author": "Brian S. Yandell ", "Maintainer": "Brian S. Yandell ", "URL": "http://www.stat.wisc.edu/~yandell/statgen", "source.ver": "src/contrib/pickgene_1.46.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/pickgene_1.46.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/pickgene_1.46.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/pickgene_1.46.0.tgz", "vignettes": [ "vignettes/pickgene/inst/doc/pickgene.pdf" ], "vignetteTitles": [ "Adaptive Gene Picking for Microarray Expression Data Analysis" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false }, "PICS": { "Package": "PICS", "Version": "2.18.0", "Depends": [ "R (>= 2.14.0)", "BiocGenerics (>= 0.1.3)" ], "Imports": [ "methods", "stats4", "IRanges", "GenomicRanges", "graphics", "grDevices", "stats", "Rsamtools", "GenomicAlignments", "S4Vectors" ], "Suggests": [ "ShortRead", "rtracklayer", "parallel" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "a9e89d61c911cce929a1bb9af6ee48cc", "NeedsCompilation": "yes", "Title": "Probabilistic inference of ChIP-seq", "Description": "Probabilistic inference of ChIP-Seq using an empirical Bayes mixture model approach.", "biocViews": [ "ChIPSeq", "Clustering", "Sequencing", "Software", "Visualization" ], "Author": "Xuekui Zhang , Raphael Gottardo ", "Maintainer": "Renan Sauteraud ", "SystemRequirements": "GSL (GNU Scientific Library)", "source.ver": "src/contrib/PICS_2.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/PICS_2.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/PICS_2.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/PICS_2.18.0.tgz", "vignettes": [ "vignettes/PICS/inst/doc/PICS.pdf" ], "vignetteTitles": [ "The PICS users guide" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/PICS/inst/doc/PICS.R" ], "importsMe": [ "PING" ] }, "Pigengene": { "Package": "Pigengene", "Version": "1.0.0", "Depends": [ "R (>= 3.3.0)", "graph" ], "Imports": [ "bnlearn", "C50", "MASS", "matrixStats", "partykit", "Rgraphviz", "WGCNA", "GO.db", "impute", "preprocessCore", "grDevices", "graphics", "stats", "utils", "parallel", "pheatmap (>= 1.0.8)" ], "Suggests": [ "org.Hs.eg.db", "org.Mm.eg.db", "biomaRt", "knitr", "BiocStyle", "AnnotationDbi", "energy" ], "License": "GPL (>=2)", "MD5sum": "16db224e9ed35abbc2e71a2ecd2948ae", "NeedsCompilation": "no", "Title": "Infers biological signatures from gene expression data", "Description": "Pigengene package provides an efficient way to infer biological signatures from gene expression profiles. The signatures are independent from the underlying platform, e.g., the input can be microarray or RNA Seq data. It can even infer the signatures using data from one platform, and evaluate them on the other. Pigengene identifies the modules (clusters) of highly coexpressed genes using coexpression network analysis, summarizes the biological information of each module in an eigengene, learns a Bayesian network that models the probabilistic dependencies between modules, and builds a decision tree based on the expression of eigengenes.", "biocViews": [ "BiomedicalInformatics", "Classification", "Clustering", "DecisionTree", "DimensionReduction", "GeneExpression", "GraphAndNetwork", "Microarray", "Network", "NetworkInference", "Normalization", "PrincipalComponent", "RNASeq", "Software", "SystemsBiology", "Transcriptomics" ], "Author": "Habil Zare, Amir Foroushani, and Rupesh Agrahari", "Maintainer": "Habil Zare ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/Pigengene_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Pigengene_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Pigengene_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Pigengene_1.0.0.tgz", "vignettes": [ "vignettes/Pigengene/inst/doc/Pigengene_inference.pdf" ], "vignetteTitles": [ "Pigengene: Computing and using eigengenes" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Pigengene/inst/doc/Pigengene_inference.R" ] }, "PING": { "Package": "PING", "Version": "2.18.0", "Depends": [ "R(>= 2.15.0)", "chipseq", "IRanges", "GenomicRanges" ], "Imports": [ "methods", "PICS", "graphics", "grDevices", "stats", "Gviz", "fda", "BSgenome", "stats4", "BiocGenerics", "IRanges", "S4Vectors" ], "Suggests": [ "parallel", "ShortRead", "rtracklayer" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "722ebb1db63b9d95e195c6a4b773abe0", "NeedsCompilation": "yes", "Title": "Probabilistic inference for Nucleosome Positioning with MNase-based or Sonicated Short-read Data", "Description": "Probabilistic inference of ChIP-Seq using an empirical Bayes mixture model approach.", "biocViews": [ "Clustering", "Sequencing", "Software", "StatisticalMethod", "Visualization" ], "Author": "Xuekui Zhang , Raphael Gottardo , Sangsoon Woo ", "Maintainer": "Renan Sauteraud ", "source.ver": "src/contrib/PING_2.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/PING_2.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/PING_2.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/PING_2.18.0.tgz", "vignettes": [ "vignettes/PING/inst/doc/PING-PE.pdf", "vignettes/PING/inst/doc/PING.pdf" ], "vignetteTitles": [ "Using PING with paired-end sequencing data", "The PING users guide" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/PING/inst/doc/PING-PE.R", "vignettes/PING/inst/doc/PING.R" ] }, "pint": { "Package": "pint", "Version": "1.24.0", "Depends": [ "mvtnorm", "methods", "graphics", "Matrix", "dmt" ], "License": "BSD_2_clause + file LICENSE", "MD5sum": "dcd0cd52f60231b19c4e4cbf2f33f99c", "NeedsCompilation": "no", "Title": "Pairwise INTegration of functional genomics data", "Description": "Pairwise data integration for functional genomics, including tools for DNA/RNA/miRNA dependency screens.", "biocViews": [ "DifferentialExpression", "GeneExpression", "Genetics", "Microarray", "Software", "aCGH" ], "Author": "Olli-Pekka Huovilainen and Leo Lahti ", "Maintainer": "Olli-Pekka Huovilainen ", "URL": "https://github.com/antagomir/pint", "BugReports": "https://github.com/antagomir/pint/issues", "source.ver": "src/contrib/pint_1.24.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/pint_1.24.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/pint_1.24.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/pint_1.24.0.tgz", "vignettes": [ "vignettes/pint/inst/doc/depsearch.pdf" ], "vignetteTitles": [ "pint" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/pint/inst/doc/depsearch.R" ] }, "pkgDepTools": { "Package": "pkgDepTools", "Version": "1.40.0", "Depends": [ "methods", "graph", "RBGL" ], "Imports": [ "graph", "RBGL" ], "Suggests": [ "Biobase", "Rgraphviz", "RCurl", "BiocInstaller" ], "License": "GPL-2", "MD5sum": "61931171f9a3dbd32973fc415e9af5b1", "NeedsCompilation": "no", "Title": "Package Dependency Tools", "Description": "This package provides tools for computing and analyzing dependency relationships among R packages. It provides tools for building a graph-based representation of the dependencies among all packages in a list of CRAN-style package repositories. There are also utilities for computing installation order of a given package. If the RCurl package is available, an estimate of the download size required to install a given package and its dependencies can be obtained.", "biocViews": [ "GraphAndNetwork", "Infrastructure", "Software" ], "Author": "Seth Falcon", "Maintainer": "Seth Falcon ", "source.ver": "src/contrib/pkgDepTools_1.40.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/pkgDepTools_1.40.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/pkgDepTools_1.40.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/pkgDepTools_1.40.0.tgz", "vignettes": [ "vignettes/pkgDepTools/inst/doc/pkgDepTools.pdf" ], "vignetteTitles": [ "How to Use pkgDepTools" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/pkgDepTools/inst/doc/pkgDepTools.R" ] }, "plateCore": { "Package": "plateCore", "Version": "1.32.0", "Depends": [ "R (>= 2.10)", "flowCore", "flowViz", "lattice", "latticeExtra" ], "Imports": [ "Biobase", "flowCore", "graphics", "grDevices", "lattice", "MASS", "methods", "robustbase", "stats", "utils", "flowStats" ], "Suggests": [ "gplots" ], "License": "Artistic-2.0", "MD5sum": "5ab7a0f594f51185f03741a0c6a44d63", "NeedsCompilation": "no", "Title": "Statistical tools and data structures for plate-based flow cytometry", "Description": "Provides basic S4 data structures and routines for analyzing plate based flow cytometry data.", "biocViews": [ "CellBasedAssays", "FlowCytometry", "Infrastructure", "Software" ], "Author": "Errol Strain, Florian Hahne, and Perry Haaland", "Maintainer": "Errol Strain ", "URL": "http://www.bioconductor.org", "source.ver": "src/contrib/plateCore_1.32.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/plateCore_1.32.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/plateCore_1.32.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/plateCore_1.32.0.tgz", "vignettes": [ "vignettes/plateCore/inst/doc/plateCoreVig.pdf" ], "vignetteTitles": [ "An R Package for Analysis of High Throughput Flow Cytometry Data" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/plateCore/inst/doc/plateCoreVig.R" ] }, "plethy": { "Package": "plethy", "Version": "1.12.1", "Depends": [ "R (>= 3.1.0)", "methods", "DBI (>= 0.5-1)", "RSQLite (>= 1.1)", "BiocGenerics", "S4Vectors" ], "Imports": [ "Streamer", "IRanges", "reshape2", "plyr", "RColorBrewer", "ggplot2", "Biobase" ], "Suggests": [ "RUnit", "BiocStyle" ], "License": "GPL-3", "MD5sum": "73160d4476f8513039ffd1a27df95e95", "NeedsCompilation": "no", "Title": "R framework for exploration and analysis of respirometry data", "Description": "This package provides the infrastructure and tools to import, query and perform basic analysis of whole body plethysmography and metabolism data. Currently support is limited to data derived from Buxco respirometry instruments as exported by their FinePointe software.", "biocViews": [ "DataImport", "DataRepresentation", "Infastructure", "Software", "TimeCourse", "biocViews" ], "Author": "Daniel Bottomly [aut, cre], Marty Ferris [ctb], Beth Wilmot [aut], Shannon McWeeney [aut]", "Maintainer": "Daniel Bottomly ", "source.ver": "src/contrib/plethy_1.12.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/plethy_1.12.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/plethy_1.12.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/plethy_1.12.1.tgz", "vignettes": [ "vignettes/plethy/inst/doc/plethy.pdf" ], "vignetteTitles": [ "plethy" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/plethy/inst/doc/plethy.R" ] }, "plgem": { "Package": "plgem", "Version": "1.46.0", "Depends": [ "R (>= 2.10)" ], "Imports": [ "utils", "Biobase (>= 2.5.5)", "MASS" ], "License": "GPL-2", "MD5sum": "d99e7b8e2be2268c4c094a8481994248", "NeedsCompilation": "no", "Title": "Detect differential expression in microarray and proteomics datasets with the Power Law Global Error Model (PLGEM)", "Description": "The Power Law Global Error Model (PLGEM) has been shown to faithfully model the variance-versus-mean dependence that exists in a variety of genome-wide datasets, including microarray and proteomics data. The use of PLGEM has been shown to improve the detection of differentially expressed genes or proteins in these datasets.", "biocViews": [ "DifferentialExpression", "GeneExpression", "MassSpectrometry", "Microarray", "Proteomics", "Software" ], "Author": "Mattia Pelizzola and Norman Pavelka ", "Maintainer": "Norman Pavelka ", "URL": "http://www.genopolis.it", "source.ver": "src/contrib/plgem_1.46.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/plgem_1.46.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/plgem_1.46.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/plgem_1.46.0.tgz", "vignettes": [ "vignettes/plgem/inst/doc/plgem.pdf" ], "vignetteTitles": [ "An introduction to PLGEM" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/plgem/inst/doc/plgem.R" ] }, "plier": { "Package": "plier", "Version": "1.44.0", "Depends": [ "R (>= 2.0)", "methods" ], "Imports": [ "affy", "Biobase", "methods" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "46f970f4a815369de3447be693451093", "NeedsCompilation": "yes", "Title": "Implements the Affymetrix PLIER algorithm", "Description": "The PLIER (Probe Logarithmic Error Intensity Estimate) method produces an improved signal by accounting for experimentally observed patterns in probe behavior and handling error at the appropriately at low and high signal values.", "biocViews": [ "Software" ], "Author": "Affymetrix Inc., Crispin J Miller, PICR", "Maintainer": "Crispin Miller ", "source.ver": "src/contrib/plier_1.44.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/plier_1.44.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/plier_1.44.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/plier_1.44.0.tgz", "hasREADME": true, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "suggestsMe": [ "piano" ] }, "PLPE": { "Package": "PLPE", "Version": "1.34.0", "Depends": [ "R (>= 2.6.2)", "Biobase (>= 2.5.5)", "LPE", "MASS", "methods" ], "License": "GPL (>= 2)", "MD5sum": "5e676f41d9f90a2ebd7d7e06074d26ad", "NeedsCompilation": "no", "Title": "Local Pooled Error Test for Differential Expression with Paired High-throughput Data", "Description": "This package performs tests for paired high-throughput data.", "biocViews": [ "DifferentialExpression", "Microarray", "Proteomics", "Software" ], "Author": "HyungJun Cho and Jae K. Lee ", "Maintainer": "Soo-heang Eo ", "URL": "http://www.korea.ac.kr/~stat2242/", "source.ver": "src/contrib/PLPE_1.34.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/PLPE_1.34.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/PLPE_1.34.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/PLPE_1.34.0.tgz", "vignettes": [ "vignettes/PLPE/inst/doc/PLPE.pdf" ], "vignetteTitles": [ "PLPE Overview" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/PLPE/inst/doc/PLPE.R" ] }, "plrs": { "Package": "plrs", "Version": "1.14.0", "Depends": [ "R (>= 2.10)", "Biobase" ], "Imports": [ "BiocGenerics", "CGHbase", "graphics", "grDevices", "ic.infer", "marray", "methods", "quadprog", "Rcsdp", "stats", "stats4", "utils" ], "Suggests": [ "mvtnorm", "methods" ], "License": "GPL (>=2.0)", "MD5sum": "843c8e751ed3a2db2ca6e106a8234ad8", "NeedsCompilation": "no", "Title": "Piecewise Linear Regression Splines (PLRS) for the association between DNA copy number and gene expression", "Description": "The present package implements a flexible framework for modeling the relationship between DNA copy number and gene expression data using Piecewise Linear Regression Splines (PLRS).", "biocViews": [ "Regression", "Software" ], "Author": "Gwenael G.R. Leday", "Maintainer": "Gwenael G.R. Leday to ", "source.ver": "src/contrib/plrs_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/plrs_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/plrs_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/plrs_1.14.0.tgz", "vignettes": [ "vignettes/plrs/inst/doc/plrs_vignette.pdf" ], "vignetteTitles": [ "plrs" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/plrs/inst/doc/plrs_vignette.R" ] }, "plw": { "Package": "plw", "Version": "1.34.0", "Depends": [ "R (>= 2.10)", "affy (>= 1.23.4)" ], "Imports": [ "MASS", "affy", "graphics", "splines", "stats" ], "Suggests": [ "limma" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "d6dc7c2aa320db11005ee2f2b3c03f9f", "NeedsCompilation": "yes", "Title": "Probe level Locally moderated Weighted t-tests.", "Description": "Probe level Locally moderated Weighted median-t (PLW) and Locally Moderated Weighted-t (LMW).", "biocViews": [ "DifferentialExpression", "Microarray", "OneChannel", "Software", "TwoChannel" ], "Author": "Magnus Astrand", "Maintainer": "Magnus Astrand ", "source.ver": "src/contrib/plw_1.34.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/plw_1.34.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/plw_1.34.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/plw_1.34.0.tgz", "vignettes": [ "vignettes/plw/inst/doc/HowToPLW.pdf" ], "vignetteTitles": [ "HowTo plw" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/plw/inst/doc/HowToPLW.R" ] }, "pmm": { "Package": "pmm", "Version": "1.6.0", "Depends": [ "R (>= 2.10)" ], "Imports": [ "lme4", "splines" ], "License": "GPL-3", "MD5sum": "6c10b4be42be312b89c1b563525af2c3", "NeedsCompilation": "no", "Title": "Parallel Mixed Model", "Description": "The Parallel Mixed Model (PMM) approach is suitable for hit selection and cross-comparison of RNAi screens generated in experiments that are performed in parallel under several conditions. For example, we could think of the measurements or readouts from cells under RNAi knock-down, which are infected with several pathogens or which are grown from different cell lines.", "biocViews": [ "Regression", "Software", "SystemsBiology" ], "Author": "Anna Drewek", "Maintainer": "Anna Drewek ", "source.ver": "src/contrib/pmm_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/pmm_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/pmm_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/pmm_1.6.0.tgz", "vignettes": [ "vignettes/pmm/inst/doc/pmm-package.pdf" ], "vignetteTitles": [ "User manual for R-Package PMM" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/pmm/inst/doc/pmm-package.R" ] }, "podkat": { "Package": "podkat", "Version": "1.6.1", "Depends": [ "R (>= 3.2.0)", "methods", "Rsamtools", "GenomicRanges" ], "Imports": [ "Rcpp (>= 0.11.1)", "parallel", "stats", "graphics", "grDevices", "utils", "Biobase", "BiocGenerics", "Matrix", "GenomeInfoDb", "IRanges", "Biostrings", "BSgenome (>= 1.32.0)" ], "LinkingTo": [ "Rcpp", "Rsamtools" ], "Suggests": [ "BSgenome.Hsapiens.UCSC.hg38.masked", "TxDb.Hsapiens.UCSC.hg38.knownGene", "BSgenome.Mmusculus.UCSC.mm10.masked", "GWASTools (>= 1.13.24)", "VariantAnnotation", "SummarizedExperiment", "knitr" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "8ed332d10bf0e214f007218e23de094c", "NeedsCompilation": "yes", "Title": "Position-Dependent Kernel Association Test", "Description": "This package provides an association test that is capable of dealing with very rare and even private variants. This is accomplished by a kernel-based approach that takes the positions of the variants into account. The test can be used for pre-processed matrix data, but also directly for variant data stored in VCF files. Association testing can be performed whole-genome, whole-exome, or restricted to pre-defined regions of interest. The test is complemented by tools for analyzing and visualizing the results.", "biocViews": [ "Annotation", "DataImport", "Genetics", "Sequencing", "Software", "VariantAnnotation", "WholeGenome" ], "Author": "Ulrich Bodenhofer", "Maintainer": "Ulrich Bodenhofer ", "URL": "http://www.bioinf.jku.at/software/podkat/", "VignetteBuilder": "knitr", "source.ver": "src/contrib/podkat_1.6.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/podkat_1.6.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/podkat_1.6.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/podkat_1.6.1.tgz", "vignettes": [ "vignettes/podkat/inst/doc/podkat.pdf" ], "vignetteTitles": [ "PODKAT - An R Package for Association Testing Involving Rare and Private Variants" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/podkat/inst/doc/podkat.R" ] }, "polyester": { "Package": "polyester", "Version": "1.10.1", "Depends": [ "R (>= 3.0.0)" ], "Imports": [ "Biostrings (>= 2.32.0)", "IRanges", "S4Vectors", "logspline", "limma", "zlibbioc" ], "Suggests": [ "knitr", "ballgown" ], "License": "Artistic-2.0", "MD5sum": "22e2005512a110d95d96302016001c25", "NeedsCompilation": "no", "Title": "Simulate RNA-seq reads", "Description": "This package can be used to simulate RNA-seq reads from differential expression experiments with replicates. The reads can then be aligned and used to perform comparisons of methods for differential expression.", "biocViews": [ "DifferentialExpression", "Sequencing", "Software" ], "Author": "Alyssa C. Frazee, Andrew E. Jaffe, Rory Kirchner, Jeffrey T. Leek", "Maintainer": "Jack Fu , Jeff Leek ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/polyester_1.10.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/polyester_1.10.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/polyester_1.10.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/polyester_1.10.1.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/polyester/inst/doc/polyester.R" ], "htmlDocs": [ "vignettes/polyester/inst/doc/polyester.html" ], "htmlTitles": [ "The Polyester package for simulating RNA-seq reads" ] }, "Polyfit": { "Package": "Polyfit", "Version": "1.8.0", "Depends": [ "DESeq" ], "Suggests": [ "BiocStyle" ], "License": "GPL (>= 3)", "MD5sum": "76897427a0356e85f57e740ff000bfe1", "NeedsCompilation": "no", "Title": "Add-on to DESeq to improve p-values and q-values", "Description": "Polyfit is an add-on to the packages DESeq which ensures the p-value distribution is uniform over the interval [0, 1] for data satisfying the null hypothesis of no differential expression, and uses an adpated Storey-Tibshiran method to calculate q-values.", "biocViews": [ "DifferentialExpression", "GeneExpression", "RNASeq", "Sequencing", "Software" ], "Author": "Conrad Burden", "Maintainer": "Conrad Burden ", "source.ver": "src/contrib/Polyfit_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Polyfit_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Polyfit_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Polyfit_1.8.0.tgz", "vignettes": [ "vignettes/Polyfit/inst/doc/polyfit.pdf" ], "vignetteTitles": [ "Polyfit" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Polyfit/inst/doc/polyfit.R" ] }, "ppiStats": { "Package": "ppiStats", "Version": "1.40.0", "Depends": [ "ScISI (>= 1.13.2)", "lattice", "ppiData (>= 0.1.19)" ], "Imports": [ "Biobase", "Category", "graph", "graphics", "grDevices", "lattice", "methods", "RColorBrewer", "stats" ], "Suggests": [ "yeastExpData", "xtable" ], "License": "Artistic-2.0", "MD5sum": "1f2875df8544ed6e0df06a77808c999d", "NeedsCompilation": "no", "Title": "Protein-Protein Interaction Statistical Package", "Description": "Tools for the analysis of protein interaction data.", "biocViews": [ "GraphAndNetwork", "Network", "NetworkInference", "Proteomics", "Software" ], "Author": "T. Chiang and D. Scholtens with contributions from W. Huber and L. Wang", "Maintainer": "Bioconductor Package Maintainer ", "source.ver": "src/contrib/ppiStats_1.40.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ppiStats_1.40.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ppiStats_1.40.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ppiStats_1.40.0.tgz", "vignettes": [ "vignettes/ppiStats/inst/doc/ppiStats.pdf" ], "vignetteTitles": [ "ppiStats" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ppiStats/inst/doc/ppiStats.R" ], "dependsOnMe": [ "PCpheno" ], "suggestsMe": [ "BiocCaseStudies", "ppiData", "RpsiXML" ] }, "pqsfinder": { "Package": "pqsfinder", "Version": "1.2.3", "Depends": [ "Biostrings" ], "Imports": [ "Rcpp (>= 0.12.3)", "GenomicRanges", "IRanges", "S4Vectors", "methods" ], "LinkingTo": [ "Rcpp", "BH (>= 1.62.0)" ], "Suggests": [ "BiocStyle", "knitr", "Gviz", "rtracklayer", "biomaRt", "BSgenome.Hsapiens.UCSC.hg38" ], "License": "BSD_2_clause + file LICENSE", "Archs": "i386, x64", "MD5sum": "b8223c55a6ae8850440c03c0c3a2cb58", "NeedsCompilation": "yes", "Title": "Identification of potential quadruplex forming sequences", "Description": "The main functionality of the this package is to detect DNA sequence patterns that are likely to fold into an intramolecular G-quadruplex (G4). Unlike many other approaches, this package is able to detect sequences responsible for G4s folded from imperfect G-runs containing bulges or mismatches and as such is more sensitive than competing algorithms.", "biocViews": [ "GeneRegulation", "MotifDiscovery", "SequenceMatching", "Software" ], "Author": "Jiri Hon, Matej Lexa and Tomas Martinek", "Maintainer": "Jiri Hon ", "SystemRequirements": "GNU make", "VignetteBuilder": "knitr", "source.ver": "src/contrib/pqsfinder_1.2.3.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/pqsfinder_1.2.3.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/pqsfinder_1.2.3.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/pqsfinder_1.2.3.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/pqsfinder/inst/doc/pqsfinder.R" ], "htmlDocs": [ "vignettes/pqsfinder/inst/doc/pqsfinder.html" ], "htmlTitles": [ "pqsfinder: User Guide" ] }, "prada": { "Package": "prada", "Version": "1.50.0", "Depends": [ "R (>= 2.10)", "Biobase", "RColorBrewer", "grid", "methods", "rrcov" ], "Imports": [ "Biobase", "BiocGenerics", "graphics", "grDevices", "grid", "MASS", "methods", "RColorBrewer", "rrcov", "stats4", "utils" ], "Suggests": [ "cellHTS2", "tcltk" ], "License": "LGPL", "Archs": "i386, x64", "MD5sum": "93ffa121f9f35bba9f7556c42c3a02ce", "NeedsCompilation": "yes", "Title": "Data analysis for cell-based functional assays", "Description": "Tools for analysing and navigating data from high-throughput phenotyping experiments based on cellular assays and fluorescent detection (flow cytometry (FACS), high-content screening microscopy).", "biocViews": [ "CellBasedAssays", "Software", "Visualization" ], "Author": "Florian Hahne , Wolfgang Huber , Markus Ruschhaupt, Joern Toedling , Joseph Barry ", "Maintainer": "Florian Hahne ", "source.ver": "src/contrib/prada_1.50.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/prada_1.50.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/prada_1.50.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/prada_1.50.0.tgz", "vignettes": [ "vignettes/prada/inst/doc/norm2.pdf", "vignettes/prada/inst/doc/prada2cellHTS.pdf" ], "vignetteTitles": [ "Removal of contaminants from FACS data", "Combining prada output and cellHTS2" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/prada/inst/doc/norm2.R", "vignettes/prada/inst/doc/prada2cellHTS.R" ], "dependsOnMe": [ "domainsignatures", "facsDorit", "RNAither" ], "importsMe": [ "cellHTS2" ] }, "prebs": { "Package": "prebs", "Version": "1.14.0", "Depends": [ "R (>= 2.14.0)", "GenomicAlignments", "affy", "RPA" ], "Imports": [ "parallel", "methods", "stats", "GenomicRanges (>= 1.13.3)", "IRanges", "Biobase", "GenomeInfoDb", "S4Vectors" ], "Suggests": [ "prebsdata", "hgu133plus2cdf", "hgu133plus2probe" ], "License": "Artistic-2.0", "MD5sum": "01512cd5c7eec27c870012ba0c2fbd9e", "NeedsCompilation": "no", "Title": "Probe region expression estimation for RNA-seq data for improved microarray comparability", "Description": "The prebs package aims at making RNA-sequencing (RNA-seq) data more comparable to microarray data. The comparability is achieved by summarizing sequencing-based expressions of probe regions using a modified version of RMA algorithm. The pipeline takes mapped reads in BAM format as an input and produces either gene expressions or original microarray probe set expressions as an output.", "biocViews": [ "GeneExpression", "Microarray", "Preprocessing", "RNASeq", "Sequencing", "Software" ], "Author": "Karolis Uziela and Antti Honkela", "Maintainer": "Karolis Uziela ", "source.ver": "src/contrib/prebs_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/prebs_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/prebs_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/prebs_1.14.0.tgz", "vignettes": [ "vignettes/prebs/inst/doc/prebs.pdf" ], "vignetteTitles": [ "prebs User Guide" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/prebs/inst/doc/prebs.R" ] }, "PREDA": { "Package": "PREDA", "Version": "1.20.0", "Depends": [ "R (>= 2.9.0)", "Biobase", "lokern (>= 1.0.9)", "multtest", "stats", "methods", "annotate" ], "Suggests": [ "quantsmooth", "qvalue", "samr", "limma", "caTools", "affy", "PREDAsampledata" ], "Enhances": [ "Rmpi", "rsprng" ], "License": "GPL-2", "MD5sum": "97e07380fe989e0545cb8c0d56c6c908", "NeedsCompilation": "no", "Title": "Position RElated Data Anlysis", "Description": "Package for the position related analysis of quantitative functional genomics data.", "biocViews": [ "CopyNumberVariation", "GeneExpression", "Genetics", "Software" ], "Author": "Francesco Ferrari ", "Maintainer": "Francesco Ferrari ", "source.ver": "src/contrib/PREDA_1.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/PREDA_1.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/PREDA_1.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/PREDA_1.20.0.tgz", "vignettes": [ "vignettes/PREDA/inst/doc/PREDAclasses.pdf", "vignettes/PREDA/inst/doc/PREDAtutorial.pdf" ], "vignetteTitles": [ "PREDA S4-classes", "PREDA tutorial" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/PREDA/inst/doc/PREDAtutorial.R" ], "dependsOnMe": [ "PREDAsampledata" ] }, "predictionet": { "Package": "predictionet", "Version": "1.20.0", "Depends": [ "igraph", "catnet" ], "Imports": [ "penalized", "RBGL", "MASS" ], "Suggests": [ "network", "minet", "knitr" ], "License": "Artistic-2.0", "MD5sum": "56cb8706cdcea59b0bc7e2d29aa78303", "NeedsCompilation": "yes", "Title": "Inference for predictive networks designed for (but not limited to) genomic data", "Description": "This package contains a set of functions related to network inference combining genomic data and prior information extracted from biomedical literature and structured biological databases. The main function is able to generate networks using Bayesian or regression-based inference methods; while the former is limited to < 100 of variables, the latter may infer networks with hundreds of variables. Several statistics at the edge and node levels have been implemented (edge stability, predictive ability of each node, ...) in order to help the user to focus on high quality subnetworks. Ultimately, this package is used in the 'Predictive Networks' web application developed by the Dana-Farber Cancer Institute in collaboration with Entagen.", "biocViews": [ "GraphAndNetwork", "NetworkInference", "Software" ], "Author": "Benjamin Haibe-Kains, Catharina Olsen, Gianluca Bontempi, John Quackenbush", "Maintainer": "Benjamin Haibe-Kains , Catharina Olsen ", "URL": "http://compbio.dfci.harvard.edu, http://www.ulb.ac.be/di/mlg", "source.ver": "src/contrib/predictionet_1.20.0.tar.gz", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/predictionet_1.20.0.tgz", "vignettes": [ "vignettes/predictionet/inst/doc/predictionet.pdf" ], "vignetteTitles": [ "predictionet" ], "hasREADME": true, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/predictionet/inst/doc/predictionet.R" ] }, "preprocessCore": { "Package": "preprocessCore", "Version": "1.36.0", "Imports": [ "stats" ], "License": "LGPL (>= 2)", "Archs": "i386, x64", "MD5sum": "e3a70a55cc19fe3a2d03cce03e542cd5", "NeedsCompilation": "yes", "Title": "A collection of pre-processing functions", "Description": "A library of core preprocessing routines", "biocViews": [ "Infrastructure", "Software" ], "Author": "Benjamin Milo Bolstad ", "Maintainer": "Benjamin Milo Bolstad ", "URL": "https://github.com/bmbolstad/preprocessCore", "source.ver": "src/contrib/preprocessCore_1.36.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/preprocessCore_1.36.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/preprocessCore_1.36.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/preprocessCore_1.36.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "dependsOnMe": [ "affyPLM", "AgiMicroRna", "cqn", "crlmm", "RefPlus" ], "importsMe": [ "affy", "ChAMP", "charm", "cn.farms", "DAPAR", "EMDomics", "ENmix", "ExiMiR", "frma", "frmaTools", "iCheck", "InPAS", "INSPEcT", "lumi", "MADSEQ", "MBCB", "MEDIPS", "minfi", "MSnbase", "MSstats", "oligo", "PECA", "Pigengene", "soGGi", "waveTiling", "yarn" ], "suggestsMe": [ "multiClust", "oneChannelGUI" ] }, "Prize": { "Package": "Prize", "Version": "1.5.1", "Imports": [ "diagram", "stringr", "ggplot2", "reshape2", "grDevices", "matrixcalc", "stats", "gplots", "methods", "utils", "graphics" ], "Suggests": [ "RUnit", "BiocGenerics" ], "License": "Artistic-2.0", "MD5sum": "c0948c4b701108051fdc254f1db2f983", "NeedsCompilation": "no", "Title": "Prize: an R package for prioritization estimation based on analytic hierarchy process", "Description": "The high throughput studies often produce large amounts of numerous genes and proteins of interest. While it is difficult to study and validate all of them. Analytic Hierarchy Process (AHP) offers a novel approach to narrowing down long lists of candidates by prioritizing them based on how well they meet the research goal. AHP is a mathematical technique for organizing and analyzing complex decisions where multiple criteria are involved. The technique structures problems into a hierarchy of elements, and helps to specify numerical weights representing the relative importance of each element. Numerical weight or priority derived from each element allows users to find alternatives that best suit their goal and their understanding of the problem.", "biocViews": [ "CellBiology", "GeneExpression", "MultipleComparison", "RNASeq", "Software" ], "Author": "Daryanaz Dargahi ", "Maintainer": "Daryanaz Dargahi ", "source.ver": "src/contrib/Prize_1.5.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Prize_1.5.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Prize_1.5.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Prize_1.5.1.tgz", "vignettes": [ "vignettes/Prize/inst/doc/Prize.pdf" ], "vignetteTitles": [ "Prize: an R package for prioritization estimation based on analytic hierarchy process" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Prize/inst/doc/Prize.R" ] }, "proBAMr": { "Package": "proBAMr", "Version": "1.8.0", "Depends": [ "R (>= 3.0.1)", "IRanges", "AnnotationDbi" ], "Imports": [ "GenomicRanges", "Biostrings", "GenomicFeatures", "rtracklayer" ], "Suggests": [ "RUnit", "BiocGenerics" ], "License": "Artistic-2.0", "MD5sum": "5b9cc37d4789fab36d00046ae06b13e2", "NeedsCompilation": "no", "Title": "Generating SAM file for PSMs in shotgun proteomics data", "Description": "Mapping PSMs back to genome. The package builds SAM file from shotgun proteomics data The package also provides function to prepare annotation from GTF file.", "biocViews": [ "MassSpectrometry", "Proteomics", "Software", "Visualization" ], "Author": "Xiaojing Wang", "Maintainer": "Xiaojing Wang ", "source.ver": "src/contrib/proBAMr_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/proBAMr_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/proBAMr_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/proBAMr_1.8.0.tgz", "vignettes": [ "vignettes/proBAMr/inst/doc/proBAMr.pdf" ], "vignetteTitles": [ "Introduction to proBAMr" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/proBAMr/inst/doc/proBAMr.R" ] }, "PROcess": { "Package": "PROcess", "Version": "1.50.0", "Depends": [ "Icens" ], "Imports": [ "graphics", "grDevices", "Icens", "stats", "utils" ], "License": "Artistic-2.0", "MD5sum": "11da68b25b84e6997d1a0f178aeb9037", "NeedsCompilation": "no", "Title": "Ciphergen SELDI-TOF Processing", "Description": "A package for processing protein mass spectrometry data.", "biocViews": [ "MassSpectrometry", "Proteomics", "Software" ], "Author": "Xiaochun Li", "Maintainer": "Xiaochun Li ", "source.ver": "src/contrib/PROcess_1.50.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/PROcess_1.50.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/PROcess_1.50.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/PROcess_1.50.0.tgz", "vignettes": [ "vignettes/PROcess/inst/doc/howtoprocess.pdf" ], "vignetteTitles": [ "HOWTO PROcess" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/PROcess/inst/doc/howtoprocess.R" ] }, "procoil": { "Package": "procoil", "Version": "2.2.0", "Depends": [ "R (>= 3.3.0)", "kebabs" ], "Imports": [ "methods", "stats", "graphics", "S4Vectors", "Biostrings", "utils" ], "Suggests": [ "knitr" ], "License": "GPL (>= 2)", "MD5sum": "6d10a3b95c22bf375415796f4be30360", "NeedsCompilation": "no", "Title": "Prediction of Oligomerization of Coiled Coil Proteins", "Description": "The package allows for predicting whether a coiled coil sequence (amino acid sequence plus heptad register) is more likely to form a dimer or more likely to form a trimer. Additionally to the prediction itself, a prediction profile is computed which allows for determining the strengths to which the individual residues are indicative for either class. Prediction profiles can also be visualized as curves or heatmaps.", "biocViews": [ "Classification", "Proteomics", "Software", "SupportVectorMachine" ], "Author": "Ulrich Bodenhofer", "Maintainer": "Ulrich Bodenhofer ", "URL": "http://www.bioinf.jku.at/software/procoil/", "VignetteBuilder": "knitr", "source.ver": "src/contrib/procoil_2.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/procoil_2.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/procoil_2.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/procoil_2.2.0.tgz", "vignettes": [ "vignettes/procoil/inst/doc/procoil.pdf" ], "vignetteTitles": [ "PrOCoil - A Web Service and an R Package for Predicting the Oligomerization of Coiled-Coil Proteins" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/procoil/inst/doc/procoil.R" ] }, "ProCoNA": { "Package": "ProCoNA", "Version": "1.12.0", "Depends": [ "R (>= 2.10)", "methods", "WGCNA", "MSnbase", "flashClust" ], "Imports": [ "BiocGenerics", "GOstats" ], "Suggests": [ "RUnit" ], "License": "GPL (>= 2)", "MD5sum": "6741542723a57071852680af2bcb663a", "NeedsCompilation": "no", "Title": "Protein co-expression network analysis (ProCoNA).", "Description": "Protein co-expression network construction using peptide level data, with statisical analysis. (Journal of Clinical Bioinformatics 2013, 3:11 doi:10.1186/2043-9113-3-11)", "biocViews": [ "GraphAndNetwork", "Proteomics", "Software" ], "Author": "David L Gibbs", "Maintainer": "David L Gibbs ", "source.ver": "src/contrib/ProCoNA_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ProCoNA_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ProCoNA_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ProCoNA_1.12.0.tgz", "vignettes": [ "vignettes/ProCoNA/inst/doc/ProCoNA_Vignette.pdf" ], "vignetteTitles": [ "De Novo Peptide Network Example" ], "hasREADME": true, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ProCoNA/inst/doc/ProCoNA_Vignette.R" ] }, "proFIA": { "Package": "proFIA", "Version": "1.0.10", "Depends": [ "R (>= 3.3.0)", "xcms" ], "Imports": [ "stats", "graphics", "utils", "grDevices", "methods", "pracma", "Biobase", "FNN", "minpack.lm", "BiocParallel" ], "Suggests": [ "ropls", "BiocGenerics", "plasFIA", "knitr" ], "License": "CeCILL", "Archs": "i386, x64", "MD5sum": "a6c8b7b75231be47a6dfeaa1c6fe54b1", "NeedsCompilation": "yes", "Title": "Preprocessing of FIA-HRMS data", "Description": "Flow Injection Analysis coupled to High-Resolution Mass Spectrometry is a promising approach for high-throughput metabolomics. FIA- HRMS data, however, cannot be pre-processed with current software tools which rely on liquid chromatography separation, or handle low resolution data only. Here we present the proFIA package, which implements a new methodology to pre-process FIA-HRMS raw data (netCDF, mzData, mzXML, and mzML) including noise modelling and injection peak reconstruction, and generate the peak table. The workflow includes noise modelling, band detection and filtering then signal matching and missing value imputation. The peak table can then be exported as a .tsv file for further analysis. Visualisations to assess the quality of the data and of the signal made are easely produced.", "biocViews": [ "Lipidomics", "MassSpectrometry", "Metabolomics", "PeakDetection", "Preprocessing", "Proteomics", "Software" ], "Author": "Alexis Delabriere and Etienne Thevenot.", "Maintainer": "Alexis Delabriere ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/proFIA_1.0.10.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/proFIA_1.0.10.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/proFIA_1.0.10.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/proFIA_1.0.10.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/proFIA/inst/doc/proFIA-vignette.R" ], "htmlDocs": [ "vignettes/proFIA/inst/doc/proFIA-vignette.html" ], "htmlTitles": [ "Vignette Title" ], "dependsOnMe": [ "plasFIA" ] }, "profileScoreDist": { "Package": "profileScoreDist", "Version": "1.2.0", "Depends": [ "R(>= 3.3)" ], "Imports": [ "Rcpp", "BiocGenerics", "methods", "graphics" ], "LinkingTo": [ "Rcpp" ], "Suggests": [ "BiocStyle", "knitr", "MotifDb" ], "License": "MIT + file LICENSE", "Archs": "i386, x64", "MD5sum": "a73b33115304384657fbb4a059727895", "NeedsCompilation": "yes", "Title": "Profile score distributions", "Description": "Regularization and score distributions for position count matrices.", "biocViews": [ "GeneRegulation", "Software", "StatisticalMethod" ], "Author": "Paal O. Westermark", "Maintainer": "Paal O. Westermark ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/profileScoreDist_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/profileScoreDist_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/profileScoreDist_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/profileScoreDist_1.2.0.tgz", "vignettes": [ "vignettes/profileScoreDist/inst/doc/profileScoreDist-vignette.pdf" ], "vignetteTitles": [ "Using profileScoreDist" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/profileScoreDist/inst/doc/profileScoreDist-vignette.R" ] }, "pRoloc": { "Package": "pRoloc", "Version": "1.14.6", "Depends": [ "R (>= 2.15)", "MSnbase (>= 1.19.20)", "MLInterfaces (>= 1.37.1)", "methods", "Rcpp (>= 0.10.3)", "BiocParallel" ], "Imports": [ "Biobase", "mclust (>= 4.3)", "caret", "e1071", "sampling", "class", "kernlab", "lattice", "nnet", "randomForest", "proxy", "FNN", "BiocGenerics", "stats", "dendextend", "RColorBrewer", "scales", "MASS", "knitr", "mvtnorm", "gtools", "plyr", "ggplot2", "biomaRt", "utils", "grDevices", "graphics" ], "LinkingTo": [ "Rcpp", "RcppArmadillo" ], "Suggests": [ "testthat", "rmarkdown", "pRolocdata (>= 1.9.4)", "roxygen2", "synapter", "xtable", "tsne", "hexbin", "rgl", "BiocStyle", "hpar (>= 1.15.3)", "dplyr", "GO.db", "AnnotationDbi" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "3644eb381c08e7a07a4d141c6b8a35ff", "NeedsCompilation": "yes", "Title": "A unifying bioinformatics framework for spatial proteomics", "Description": "This package implements pattern recognition techniques on quantitiative mass spectrometry data to infer protein sub-cellular localisation.", "biocViews": [ "Classification", "Clustering", "MassSpectrometry", "Proteomics", "QualityControl", "Software" ], "Author": "Laurent Gatto and Lisa M. Breckels with contributions from Thomas Burger and Samuel Wieczorek", "Maintainer": "Laurent Gatto ", "URL": "https://github.com/lgatto/pRoloc", "VignetteBuilder": "knitr", "Video": "https://www.youtube.com/playlist?list=PLvIXxpatSLA2loV5Srs2VBpJIYUlVJ4ow", "BugReports": "https://github.com/lgatto/pRoloc/issues", "source.ver": "src/contrib/pRoloc_1.14.6.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/pRoloc_1.14.6.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/pRoloc_1.14.6.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/pRoloc_1.14.6.tgz", "vignettes": [ "vignettes/pRoloc/inst/doc/HUPO_2011_poster.pdf", "vignettes/pRoloc/inst/doc/HUPO_2014_poster.pdf", "vignettes/pRoloc/inst/doc/pRoloc-ml.pdf", "vignettes/pRoloc/inst/doc/pRoloc-transfer-learning.pdf", "vignettes/pRoloc/inst/doc/pRoloc-tutorial.pdf" ], "vignetteTitles": [ "HUPO 2011 poster: pRoloc -- A unifying bioinformatics framework for organelle proteomics", "HUPO 2014 poster: A state-of-the-art machine learning pipeline for the analysis of spatial proteomics data", "Machine learning techniques available in pRoloc", "A transfer learning algorithm for spatial proteomics", "pRoloc tutorial" ], "hasREADME": true, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/pRoloc/inst/doc/HUPO_2011_poster.R", "vignettes/pRoloc/inst/doc/HUPO_2014_poster.R", "vignettes/pRoloc/inst/doc/pRoloc-goannotations.R", "vignettes/pRoloc/inst/doc/pRoloc-transfer-learning.R" ], "htmlDocs": [ "vignettes/pRoloc/inst/doc/pRoloc-goannotations.html" ], "htmlTitles": [ "Annotating spatial proteomics data" ], "dependsOnMe": [ "pRolocGUI" ], "suggestsMe": [ "MSnbase", "pRolocdata", "RforProteomics" ] }, "pRolocGUI": { "Package": "pRolocGUI", "Version": "1.8.2", "Depends": [ "methods", "R (>= 3.1.0)", "pRoloc (>= 1.11.1)", "Biobase", "MSnbase (>= 1.13.11)" ], "Imports": [ "shiny (>= 0.9.1)", "scales", "dplyr", "DT (>= 0.1.40)", "graphics", "utils" ], "Suggests": [ "pRolocdata", "knitr", "BiocStyle", "rmarkdown" ], "License": "GPL-2", "MD5sum": "edc1da4fbd1883396030d54f86298c26", "NeedsCompilation": "no", "Title": "Interactive visualisation of spatial proteomics data", "Description": "The package pRolocGUI comprises functions to interactively visualise organelle (spatial) proteomics data on the basis of pRoloc, pRolocdata and shiny.", "biocViews": [ "GUI", "Proteomics", "Software", "Visualization" ], "Author": "Lisa M Breckels, Thomas Naake and Laurent Gatto", "Maintainer": "Laurent Gatto , Lisa M Breckels ", "URL": "http://ComputationalProteomicsUnit.github.io/pRolocGUI/", "VignetteBuilder": "knitr", "Video": "https://www.youtube.com/playlist?list=PLvIXxpatSLA2loV5Srs2VBpJIYUlVJ4ow", "BugReports": "https://github.com/ComputationalProteomicsUnit/pRolocGUI/issues", "source.ver": "src/contrib/pRolocGUI_1.8.2.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/pRolocGUI_1.8.2.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/pRolocGUI_1.8.2.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/pRolocGUI_1.8.2.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/pRolocGUI/inst/doc/pRolocGUI.R" ], "htmlDocs": [ "vignettes/pRolocGUI/inst/doc/pRolocGUI.html" ], "htmlTitles": [ "pRolocGUI - Interactive visualisation of spatial proteomics data" ] }, "PROMISE": { "Package": "PROMISE", "Version": "1.26.0", "Depends": [ "R (>= 3.1.0)", "Biobase", "GSEABase" ], "Imports": [ "Biobase", "GSEABase", "stats" ], "License": "GPL (>= 2)", "MD5sum": "f85282293e35af5f2ffd4c4b00783b30", "NeedsCompilation": "no", "Title": "PRojection Onto the Most Interesting Statistical Evidence", "Description": "A general tool to identify genomic features with a specific biologically interesting pattern of associations with multiple endpoint variables as described in Pounds et. al. (2009) Bioinformatics 25: 2013-2019", "biocViews": [ "GeneExpression", "Microarray", "MultipleComparison", "OneChannel", "Software" ], "Author": "Stan Pounds , Xueyuan Cao ", "Maintainer": "Stan Pounds , Xueyuan Cao ", "source.ver": "src/contrib/PROMISE_1.26.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/PROMISE_1.26.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/PROMISE_1.26.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/PROMISE_1.26.0.tgz", "vignettes": [ "vignettes/PROMISE/inst/doc/PROMISE.pdf" ], "vignetteTitles": [ "An introduction to PROMISE" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/PROMISE/inst/doc/PROMISE.R" ], "dependsOnMe": [ "CCPROMISE" ] }, "PROPER": { "Package": "PROPER", "Version": "1.6.0", "Depends": [ "R (>= 2.10)" ], "Imports": [ "edgeR" ], "Suggests": [ "BiocStyle", "DESeq", "DSS", "knitr" ], "License": "GPL", "MD5sum": "0c6e19340cf2dc2c38c8c48fd1c2520d", "NeedsCompilation": "no", "Title": "PROspective Power Evaluation for RNAseq", "Description": "This package provide simulation based methods for evaluating the statistical power in differential expression analysis from RNA-seq data.", "biocViews": [ "DifferentialExpression", "RNASeq", "Sequencing", "Software" ], "Author": "Hao Wu", "Maintainer": "Hao Wu ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/PROPER_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/PROPER_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/PROPER_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/PROPER_1.6.0.tgz", "vignettes": [ "vignettes/PROPER/inst/doc/PROPER.pdf" ], "vignetteTitles": [ "Power and Sample size analysis for gene expression from RNA-seq" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/PROPER/inst/doc/PROPER.R" ] }, "Prostar": { "Package": "Prostar", "Version": "1.6.1", "Depends": [ "R (>= 3.3)" ], "Imports": [ "DAPAR (>= 1.5.5)", "DAPARdata", "rhandsontable", "data.table", "shinyjs", "DT", "shiny", "shinyAce", "sm" ], "Suggests": [ "BiocStyle" ], "License": "Artistic-2.0", "MD5sum": "b4807311e7b1f374d6a3080b3e9c94b4", "NeedsCompilation": "no", "Title": "Provides a GUI for DAPAR", "Description": "This package provides a GUI interface for DAPAR.", "biocViews": [ "GUI", "MassSpectrometry", "Normalization", "Preprocessing", "Proteomics", "Software" ], "Author": "Samuel Wieczorek [cre,aut], Florence Combes [aut], Thomas Burger [aut]", "Maintainer": "Samuel Wieczorek ", "source.ver": "src/contrib/Prostar_1.6.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Prostar_1.6.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Prostar_1.6.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Prostar_1.6.1.tgz", "vignettes": [ "vignettes/Prostar/inst/doc/Prostar_Tutorial.pdf", "vignettes/Prostar/inst/doc/Prostar_UserManual.pdf" ], "vignetteTitles": [ "Prostar tutorial", "Prostar user manual" ], "hasREADME": true, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Prostar/inst/doc/Prostar_Tutorial.R", "vignettes/Prostar/inst/doc/Prostar_UserManual.R" ], "suggestsMe": [ "DAPAR", "DAPARdata" ] }, "prot2D": { "Package": "prot2D", "Version": "1.12.0", "Depends": [ "R (>= 2.15)", "fdrtool", "st", "samr", "Biobase", "limma", "Mulcom", "impute", "MASS", "qvalue" ], "Suggests": [ "made4", "affy" ], "License": "GPL (>= 2)", "MD5sum": "17c792808721534caf471327bba77c1a", "NeedsCompilation": "no", "Title": "Statistical Tools for volume data from 2D Gel Electrophoresis", "Description": "The purpose of this package is to analyze (i.e. Normalize and select significant spots) data issued from 2D GEl experiments", "biocViews": [ "DifferentialExpression", "MultipleComparison", "Proteomics", "Software" ], "Author": "Sebastien Artigaud", "Maintainer": "Sebastien Artigaud ", "source.ver": "src/contrib/prot2D_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/prot2D_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/prot2D_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/prot2D_1.12.0.tgz", "vignettes": [ "vignettes/prot2D/inst/doc/prot2D.pdf" ], "vignetteTitles": [ "prot2D" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/prot2D/inst/doc/prot2D.R" ] }, "proteinProfiles": { "Package": "proteinProfiles", "Version": "1.14.0", "Depends": [ "R (>= 2.15.2)" ], "Imports": [ "graphics", "stats" ], "Suggests": [ "testthat" ], "License": "GPL-3", "MD5sum": "385415fdf0182c8bfb963b44d9516e89", "NeedsCompilation": "no", "Title": "Protein Profiling", "Description": "Significance assessment for distance measures of time-course protein profiles", "Author": "Julian Gehring", "Maintainer": "Julian Gehring ", "source.ver": "src/contrib/proteinProfiles_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/proteinProfiles_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/proteinProfiles_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/proteinProfiles_1.14.0.tgz", "vignettes": [ "vignettes/proteinProfiles/inst/doc/proteinProfiles.pdf" ], "vignetteTitles": [ "The proteinProfiles package" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/proteinProfiles/inst/doc/proteinProfiles.R" ], "biocViews": [ "Software" ] }, "ProteomicsAnnotationHubData": { "Package": "ProteomicsAnnotationHubData", "Version": "1.4.0", "Depends": [ "AnnotationHub (>= 2.1.45)", "AnnotationHubData" ], "Imports": [ "mzR (>= 2.3.2)", "MSnbase", "Biostrings", "GenomeInfoDb", "utils", "Biobase", "BiocInstaller", "RCurl" ], "Suggests": [ "knitr", "BiocStyle", "rmarkdown", "testthat" ], "License": "Artistic-2.0", "MD5sum": "5757f856e51ffff53bfb0985f22936eb", "NeedsCompilation": "no", "Title": "Transform public proteomics data resources into Bioconductor Data Structures", "Description": "These recipes convert a variety and a growing number of public proteomics data sets into easily-used standard Bioconductor data structures.", "biocViews": [ "DataImport", "Proteomics", "Software" ], "Author": "Gatto Laurent [aut, cre], Sonali Arora [aut]", "Maintainer": "Laurent Gatto ", "URL": "https://github.com/lgatto/ProteomicsAnnotationHubData", "VignetteBuilder": "knitr", "BugReports": "https://github.com/lgatto/ProteomicsAnnotationHubData/issues", "source.ver": "src/contrib/ProteomicsAnnotationHubData_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ProteomicsAnnotationHubData_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ProteomicsAnnotationHubData_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ProteomicsAnnotationHubData_1.4.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ProteomicsAnnotationHubData/inst/doc/ProteomicsAnnotationHubData.R" ], "htmlDocs": [ "vignettes/ProteomicsAnnotationHubData/inst/doc/ProteomicsAnnotationHubData.html" ], "htmlTitles": [ "Proteomics Data in Annotation Hub" ] }, "proteoQC": { "Package": "proteoQC", "Version": "1.10.0", "Depends": [ "R (>= 3.0.0)", "XML", "VennDiagram", "MSnbase" ], "Imports": [ "rTANDEM", "plyr", "seqinr", "Nozzle.R1", "ggplot2", "reshape2", "parallel", "Rcpp (>= 0.11.1)" ], "LinkingTo": [ "Rcpp" ], "Suggests": [ "RforProteomics", "knitr", "BiocStyle", "rpx", "R.utils", "RUnit", "BiocGenerics" ], "License": "LGPL-2", "Archs": "i386, x64", "MD5sum": "cbaf351b3dd8427899314c04526bd8a9", "NeedsCompilation": "yes", "Title": "An R package for proteomics data quality control", "Description": "This package creates a HTML format QC report for MS/MS-based proteomics data. The report is intended to allow the user to quickly assess the quality of proteomics data.", "biocViews": [ "MassSpectrometry", "Proteomics", "QualityControl", "ReportWriting", "Software", "Visualization" ], "Author": "Bo Wen , Laurent Gatto ", "Maintainer": "Bo Wen ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/proteoQC_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/proteoQC_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/proteoQC_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/proteoQC_1.10.0.tgz", "vignettes": [ "vignettes/proteoQC/inst/doc/proteoQC.pdf" ], "vignetteTitles": [ "proteoQC tutorial" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/proteoQC/inst/doc/proteoQC.R" ] }, "ProtGenerics": { "Package": "ProtGenerics", "Version": "1.6.0", "Depends": [ "methods" ], "License": "Artistic-2.0", "MD5sum": "adf7d84821b4444336ab9f2d1c4b9eaf", "NeedsCompilation": "no", "Title": "S4 generic functions for Bioconductor proteomics infrastructure", "Description": "S4 generic functions needed by Bioconductor proteomics packages.", "biocViews": [ "Infrastructure", "MassSpectrometry", "Proteomics", "Software" ], "Author": "Laurent Gatto ", "Maintainer": "Laurent Gatto ", "URL": "https://github.com/lgatto/ProtGenerics", "source.ver": "src/contrib/ProtGenerics_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ProtGenerics_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ProtGenerics_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ProtGenerics_1.6.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "dependsOnMe": [ "Cardinal", "MSnbase", "tofsims", "xcms" ], "importsMe": [ "MSnID", "mzID", "mzR" ] }, "PSEA": { "Package": "PSEA", "Version": "1.8.0", "Imports": [ "Biobase", "MASS" ], "Suggests": [ "BiocStyle" ], "License": "Artistic-2.0", "MD5sum": "28c3d9f8685b9630bfd1c96e5e4072de", "NeedsCompilation": "no", "Title": "Population-Specific Expression Analysis.", "Description": "Deconvolution of gene expression data by Population-Specific Expression Analysis (PSEA).", "biocViews": [ "Software" ], "Author": "Alexandre Kuhn ", "Maintainer": "Alexandre Kuhn ", "source.ver": "src/contrib/PSEA_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/PSEA_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/PSEA_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/PSEA_1.8.0.tgz", "vignettes": [ "vignettes/PSEA/inst/doc/PSEA.pdf" ], "vignetteTitles": [ "PSEA: Overview" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/PSEA/inst/doc/PSEA.R" ] }, "psichomics": { "Package": "psichomics", "Version": "1.0.8", "Depends": [ "R (>= 3.3)", "shiny (>= 1.0.0)", "shinyBS" ], "Imports": [ "AnnotationHub", "data.table", "digest", "dplyr", "DT (>= 0.2)", "fastmatch", "highcharter (>= 0.5.0)", "httr", "jsonlite", "miscTools", "plyr", "R.utils", "shinyjs", "stringr", "stats", "survival", "Sushi", "tools", "utils", "XML", "methods" ], "Suggests": [ "testthat", "knitr", "parallel", "devtools", "rmarkdown", "gplots", "covr", "car" ], "License": "MIT + file LICENSE", "MD5sum": "60d9adba9d0577bf6635020265ab27a5", "NeedsCompilation": "no", "Title": "Graphical Interface for Alternative Splicing Quantification, Analysis and Visualisation", "Description": "Package with a Shiny-based graphical interface for the integrated analysis of alternative splicing data from The Cancer Genome Atlas (TCGA). This tool interactively performs survival, principal components and differential splicing analyses with direct incorporation of clinical features (such as tumour stage or survival) associated with TCGA samples.", "biocViews": [ "AlternativeSplicing", "BiomedicalInformatics", "DifferentialSplicing", "GUI", "MultipleComparison", "PrincipalComponent", "RNASeq", "Sequencing", "Software", "Survival", "Transcription", "Transcriptomics", "Visualization" ], "Author": "Nuno Saraiva-Agostinho [aut, cre], Nuno Barbosa-Morais [aut, ths], André Falcão [ths], Lina Gallego Paez [ctb], Marie Bordone [ctb], Teresa Maia [ctb], Mariana Ferreira [ctb], Ana Carolina Leote [ctb], Bernardo Almeida [ctb]", "Maintainer": "Nuno Saraiva-Agostinho ", "URL": "https://github.com/nuno-agostinho/psichomics", "VignetteBuilder": "knitr", "BugReports": "https://github.com/nuno-agostinho/psichomics/issues", "source.ver": "src/contrib/psichomics_1.0.8.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/psichomics_1.0.8.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/psichomics_1.0.8.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/psichomics_1.0.8.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/psichomics/inst/doc/AS_events_preparation.R", "vignettes/psichomics/inst/doc/CLI_tutorial.R", "vignettes/psichomics/inst/doc/GUI_tutorial.R" ], "htmlDocs": [ "vignettes/psichomics/inst/doc/AS_events_preparation.html", "vignettes/psichomics/inst/doc/CLI_tutorial.html", "vignettes/psichomics/inst/doc/GUI_tutorial.html" ], "htmlTitles": [ "Custom alternative splicing annotation", "Command-line interface tutorial", "Visual interface tutorial" ] }, "PSICQUIC": { "Package": "PSICQUIC", "Version": "1.12.1", "Depends": [ "R (>= 3.2.2)", "methods", "IRanges", "biomaRt", "BiocGenerics", "httr", "plyr" ], "Imports": [ "RCurl" ], "Suggests": [ "org.Hs.eg.db" ], "License": "Apache License 2.0", "MD5sum": "12405efd78449a271409e030c03594d8", "NeedsCompilation": "no", "Title": "Proteomics Standard Initiative Common QUery InterfaCe", "Description": "PSICQUIC is a project within the HUPO Proteomics Standard Initiative (HUPO-PSI). It standardises programmatic access to molecular interaction databases.", "biocViews": [ "DataImport", "GraphAndNetwork", "Software", "ThirdPartyClient" ], "Author": "Paul Shannon", "Maintainer": "Paul Shannon", "source.ver": "src/contrib/PSICQUIC_1.12.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/PSICQUIC_1.12.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/PSICQUIC_1.12.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/PSICQUIC_1.12.1.tgz", "vignettes": [ "vignettes/PSICQUIC/inst/doc/PSICQUIC.pdf" ], "vignetteTitles": [ "PSICQUIC" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/PSICQUIC/inst/doc/PSICQUIC.R" ], "dependsOnMe": [ "RefNet" ] }, "psygenet2r": { "Package": "psygenet2r", "Version": "1.7.4", "Depends": [ "R (>= 3.3)" ], "Imports": [ "stringr", "RCurl", "igraph", "ggplot2", "reshape2", "grid", "parallel", "biomaRt", "BgeeDB", "topGO", "BiocInstaller", "Biobase", "labeling" ], "Suggests": [ "testthat" ], "License": "MIT + file LICENSE", "MD5sum": "3be5b8d9237bc83345d0f30159a902bd", "NeedsCompilation": "no", "Title": "psygenet2r - An R package for querying PsyGeNET and to perform comorbidity studies in psychiatric disorders", "Description": "Package to retrieve data from PsyGeNET database (www.psygenet.org) and to perform comorbidity studies with PsyGeNET's and user's data.", "biocViews": [ "BiomedicalInformatics", "DataImport", "DataRepresentation", "Genetics", "Infrastructure", "Software" ], "Author": "Alba Gutierrez-Sacristan [aut], Carles Hernandez-Ferrer [cre]", "Maintainer": "Alba Gutierrez-Sacristan ", "source.ver": "src/contrib/psygenet2r_1.7.4.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/psygenet2r_1.7.4.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/psygenet2r_1.7.4.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/psygenet2r_1.7.4.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true }, "puma": { "Package": "puma", "Version": "3.16.0", "Depends": [ "R (>= 3.2.0)", "oligo (>= 1.32.0)", "graphics", "grDevices", "methods", "stats", "utils", "mclust", "oligoClasses" ], "Imports": [ "Biobase (>= 2.5.5)", "affy (>= 1.46.0)", "affyio", "oligoClasses" ], "Suggests": [ "pumadata", "affydata", "snow", "limma", "ROCR", "annotate" ], "License": "LGPL", "Archs": "i386, x64", "MD5sum": "150bbadf51c141d316443176d2f418d8", "NeedsCompilation": "yes", "Title": "Propagating Uncertainty in Microarray Analysis(including Affymetrix tranditional 3' arrays and exon arrays and Human Transcriptome Array 2.0)", "Description": "Most analyses of Affymetrix GeneChip data (including tranditional 3' arrays and exon arrays and Human Transcriptome Array 2.0) are based on point estimates of expression levels and ignore the uncertainty of such estimates. By propagating uncertainty to downstream analyses we can improve results from microarray analyses. For the first time, the puma package makes a suite of uncertainty propagation methods available to a general audience. In additon to calculte gene expression from Affymetrix 3' arrays, puma also provides methods to process exon arrays and produces gene and isoform expression for alternative splicing study. puma also offers improvements in terms of scope and speed of execution over previously available uncertainty propagation methods. Included are summarisation, differential expression detection, clustering and PCA methods, together with useful plotting functions.", "biocViews": [ "AlternativeSplicing", "Bayesian", "ChipOnChip", "Clustering", "DataImport", "DifferentialExpression", "DifferentialSplicing", "ExonArray", "GeneExpression", "HTA2.0", "Microarray", "OneChannel", "Preprocessing", "Software", "TwoChannel", "mRNAMicroarray" ], "Author": "Richard D. Pearson, Xuejun Liu, Magnus Rattray, Marta Milo, Neil D. Lawrence, Guido Sanguinetti, Li Zhang", "Maintainer": "Xuejun Liu ", "URL": "http://umber.sbs.man.ac.uk/resources/puma", "source.ver": "src/contrib/puma_3.16.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/puma_3.16.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/puma_3.16.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/puma_3.16.0.tgz", "vignettes": [ "vignettes/puma/inst/doc/puma.pdf" ], "vignetteTitles": [ "puma User Guide" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/puma/inst/doc/puma.R" ], "suggestsMe": [ "tigre" ], "dependsOnMe": [ "pumadata" ] }, "PureCN": { "Package": "PureCN", "Version": "1.2.3", "Depends": [ "R (>= 3.2)", "DNAcopy", "VariantAnnotation (>= 1.14.1)" ], "Imports": [ "GenomicRanges (>= 1.20.3)", "IRanges (>= 2.2.1)", "RColorBrewer", "S4Vectors", "data.table", "grDevices", "graphics", "stats", "utils", "SummarizedExperiment", "GenomeInfoDb", "Rsamtools", "Biostrings" ], "Suggests": [ "PSCBS", "RUnit", "BiocStyle", "BiocGenerics", "knitr", "getopt", "rtracklayer" ], "License": "Artistic-2.0", "MD5sum": "84b782885d2826800c640c337db20aa9", "NeedsCompilation": "no", "Title": "Copy number calling and SNV classification using targeted short read sequencing", "Description": "This package estimates tumor purity, copy number, loss of heterozygosity (LOH), and status of single nucleotide variants (SNVs). PureCN is designed for targeted short read sequencing data, integrates well with standard somatic variant detection pipelines, and has support for tumor samples without matching normal samples.", "biocViews": [ "CopyNumberVariation", "Coverage", "Sequencing", "Software", "VariantAnnotation", "VariantDetection" ], "Author": "Markus Riester", "Maintainer": "Markus Riester ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/PureCN_1.2.3.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/PureCN_1.2.3.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/PureCN_1.2.3.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/PureCN_1.2.3.tgz", "vignettes": [ "vignettes/PureCN/inst/doc/PureCN.pdf" ], "vignetteTitles": [ "PureCN" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/PureCN/inst/doc/PureCN.R" ] }, "pvac": { "Package": "pvac", "Version": "1.22.0", "Depends": [ "R (>= 2.8.0)" ], "Imports": [ "affy (>= 1.20.0)", "stats", "Biobase" ], "Suggests": [ "pbapply", "affydata", "ALLMLL", "genefilter" ], "License": "LGPL (>= 2.0)", "MD5sum": "b4cab8e6891992b647d4d75c36379198", "NeedsCompilation": "no", "Title": "PCA-based gene filtering for Affymetrix arrays", "Description": "The package contains the function for filtering genes by the proportion of variation accounted for by the first principal component (PVAC).", "biocViews": [ "Microarray", "OneChannel", "QualityControl", "Software" ], "Author": "Jun Lu and Pierre R. Bushel", "Maintainer": "Jun Lu , Pierre R. Bushel ", "source.ver": "src/contrib/pvac_1.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/pvac_1.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/pvac_1.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/pvac_1.22.0.tgz", "vignettes": [ "vignettes/pvac/inst/doc/pvac.pdf" ], "vignetteTitles": [ "PCA-based gene filtering for Affymetrix GeneChips" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/pvac/inst/doc/pvac.R" ] }, "pvca": { "Package": "pvca", "Version": "1.14.0", "Depends": [ "R (>= 2.15.1)" ], "Imports": [ "Matrix", "Biobase", "vsn", "stats", "lme4" ], "Suggests": [ "golubEsets" ], "License": "LGPL (>= 2.0)", "MD5sum": "b89b9f5cb80fc42babf4206aa92a78d0", "NeedsCompilation": "no", "Title": "Principal Variance Component Analysis (PVCA)", "Description": "This package contains the function to assess the batch sourcs by fitting all \"sources\" as random effects including two-way interaction terms in the Mixed Model(depends on lme4 package) to selected principal components, which were obtained from the original data correlation matrix. This package accompanies the book \"Batch Effects and Noise in Microarray Experiements, chapter 12.", "biocViews": [ "BatchEffect", "Microarray", "Software" ], "Author": "Pierre Bushel ", "Maintainer": "Jianying LI ", "source.ver": "src/contrib/pvca_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/pvca_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/pvca_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/pvca_1.14.0.tgz", "vignettes": [ "vignettes/pvca/inst/doc/pvca.pdf" ], "vignetteTitles": [ "Batch effect estimation in Microarray data" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/pvca/inst/doc/pvca.R" ] }, "Pviz": { "Package": "Pviz", "Version": "1.8.0", "Depends": [ "R(>= 3.0.0)", "Gviz(>= 1.7.10)" ], "Imports": [ "biovizBase", "Biostrings", "GenomicRanges", "IRanges", "data.table", "methods" ], "Suggests": [ "knitr", "pepDat" ], "License": "Artistic-2.0", "MD5sum": "828e93705911e491e5e41a0b85333193", "NeedsCompilation": "no", "Title": "Peptide Annotation and Data Visualization using Gviz", "Description": "Pviz adapts the Gviz package for protein sequences and data.", "biocViews": [ "Microarray", "Proteomics", "Software", "Visualization" ], "Author": "Renan Sauteraud, Mike Jiang, Raphael Gottardo", "Maintainer": "Renan Sauteraud ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/Pviz_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Pviz_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Pviz_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Pviz_1.8.0.tgz", "vignettes": [ "vignettes/Pviz/inst/doc/Pviz.pdf" ], "vignetteTitles": [ "The Pviz users guide" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Pviz/inst/doc/Pviz.R" ], "importsMe": [ "Pbase" ], "suggestsMe": [ "pepStat" ] }, "PWMEnrich": { "Package": "PWMEnrich", "Version": "4.10.0", "Depends": [ "methods", "grid", "BiocGenerics", "Biostrings" ], "Imports": [ "seqLogo", "gdata", "evd" ], "Suggests": [ "MotifDb", "BSgenome.Dmelanogaster.UCSC.dm3", "PWMEnrich.Dmelanogaster.background", "testthat", "gtools", "parallel", "PWMEnrich.Hsapiens.background", "PWMEnrich.Mmusculus.background", "BiocStyle", "knitr" ], "License": "LGPL (>= 2)", "MD5sum": "a32de99322e0c96aaf713bf16f190c35", "NeedsCompilation": "no", "Title": "PWM enrichment analysis", "Description": "A toolkit of high-level functions for DNA motif scanning and enrichment analysis built upon Biostrings. The main functionality is PWM enrichment analysis of already known PWMs (e.g. from databases such as MotifDb), but the package also implements high-level functions for PWM scanning and visualisation. The package does not perform \"de novo\" motif discovery, but is instead focused on using motifs that are either experimentally derived or computationally constructed by other tools.", "biocViews": [ "MotifAnnotation", "SequenceMatching", "Software" ], "Author": "Robert Stojnic, Diego Diez", "Maintainer": "Robert Stojnic ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/PWMEnrich_4.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/PWMEnrich_4.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/PWMEnrich_4.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/PWMEnrich_4.10.0.tgz", "vignettes": [ "vignettes/PWMEnrich/inst/doc/PWMEnrich.pdf" ], "vignetteTitles": [ "Overview of the 'PWMEnrich' package" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/PWMEnrich/inst/doc/PWMEnrich.R" ], "suggestsMe": [ "rTRM" ], "dependsOnMe": [ "PWMEnrich.Dmelanogaster.background", "PWMEnrich.Hsapiens.background", "PWMEnrich.Mmusculus.background" ] }, "pwOmics": { "Package": "pwOmics", "Version": "1.6.0", "Depends": [ "R (>= 3.2)" ], "Imports": [ "data.table", "rBiopaxParser", "igraph", "STRINGdb", "graphics", "gplots", "Biobase", "BiocGenerics", "AnnotationDbi", "biomaRt", "AnnotationHub", "GenomicRanges" ], "Suggests": [ "ebdbNet", "longitudinal", "Mfuzz" ], "License": "GPL (>= 2)", "MD5sum": "cbc8f9b59e593b153ea0aff791b381b8", "NeedsCompilation": "no", "Title": "Pathway-based data integration of omics data", "Description": "pwOmics performs pathway-based level-specific data comparison of matching omics data sets based on pre-analysed user-specified lists of differential genes/transcripts and proteins. A separate downstream analysis of proteomic data including pathway identification and enrichment analysis, transcription factor identification and target gene identification is opposed to the upstream analysis starting with gene or transcript information as basis for identification of upstream transcription factors and regulators. The cross-platform comparative analysis allows for comprehensive analysis of single time point experiments and time-series experiments by providing static and dynamic analysis tools for data integration.", "biocViews": [ "GeneTarget", "Software", "SystemsBiology", "Transcription" ], "Author": "Astrid Wachter ", "Maintainer": "Astrid Wachter ", "source.ver": "src/contrib/pwOmics_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/pwOmics_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/pwOmics_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/pwOmics_1.6.0.tgz", "vignettes": [ "vignettes/pwOmics/inst/doc/pwOmics.pdf" ], "vignetteTitles": [ "pwOmics Vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/pwOmics/inst/doc/pwOmics.R" ] }, "qcmetrics": { "Package": "qcmetrics", "Version": "1.12.0", "Depends": [ "R (>= 2.10)" ], "Imports": [ "Biobase", "methods", "knitr", "tools", "Nozzle.R1", "xtable", "pander", "S4Vectors" ], "Suggests": [ "affy", "MSnbase", "ggplot2", "lattice", "yaqcaffy", "MAQCsubsetAFX", "RforProteomics", "AnnotationDbi", "mzR", "hgu133plus2cdf", "BiocStyle" ], "License": "GPL-2", "MD5sum": "af32fe996d5aceef163d49637657ffbd", "NeedsCompilation": "no", "Title": "A Framework for Quality Control", "Description": "The package provides a framework for generic quality control of data. It permits to create, manage and visualise individual or sets of quality control metrics and generate quality control reports in various formats.", "biocViews": [ "MassSpectrometry", "Microarray", "Proteomics", "QualityControl", "ReportWriting", "Software", "Visualization" ], "Author": "Laurent Gatto", "Maintainer": "Laurent Gatto ", "URL": "https://github.com/lgatto/qcmetrics", "VignetteBuilder": "knitr", "source.ver": "src/contrib/qcmetrics_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/qcmetrics_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/qcmetrics_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/qcmetrics_1.12.0.tgz", "vignettes": [ "vignettes/qcmetrics/inst/doc/qcmetrics.pdf" ], "vignetteTitles": [ "The 'qcmetrics' infrastructure for quality control and reporting" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/qcmetrics/inst/doc/qcmetrics.R" ] }, "QDNAseq": { "Package": "QDNAseq", "Version": "1.10.0", "Depends": [ "R (>= 3.1.0)" ], "Imports": [ "graphics", "methods", "stats", "utils", "Biobase (>= 2.18.0)", "CGHbase (>= 1.18.0)", "CGHcall (>= 2.18.0)", "DNAcopy (>= 1.32.0)", "GenomicRanges (>= 1.20)", "IRanges (>= 2.2)", "matrixStats (>= 0.50.2)", "R.utils (>= 2.3.0)", "Rsamtools (>= 1.20)" ], "Suggests": [ "BiocStyle (>= 1.8.0)", "BSgenome (>= 1.38.0)", "digest (>= 0.6.8)", "GenomeInfoDb (>= 1.6.0)", "future (>= 0.14.0)", "R.cache (>= 0.12.0)" ], "License": "GPL", "MD5sum": "d1b2ca2f3d90d46a8bf799fd2541de5a", "NeedsCompilation": "no", "Title": "Quantitative DNA sequencing for chromosomal aberrations", "Description": "Quantitative DNA sequencing for chromosomal aberrations. The genome is divided into non-overlapping fixed-sized bins, number of sequence reads in each counted, adjusted with a simultaneous two-dimensional loess correction for sequence mappability and GC content, and filtered to remove spurious regions in the genome. Downstream steps of segmentation and calling are also implemented via packages DNAcopy and CGHcall, respectively.", "biocViews": [ "CopyNumberVariation", "DNASeq", "Genetics", "GenomeAnnotation", "Preprocessing", "QualityControl", "Sequencing", "Software" ], "Author": "Ilari Scheinin [aut], Daoud Sie [aut, cre], Henrik Bengtsson [aut]", "Maintainer": "Daoud Sie ", "URL": "https://github.com/ccagc/QDNAseq", "BugReports": "https://github.com/ccagc/QDNAseq/issues", "source.ver": "src/contrib/QDNAseq_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/QDNAseq_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/QDNAseq_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/QDNAseq_1.10.0.tgz", "vignettes": [ "vignettes/QDNAseq/inst/doc/QDNAseq.pdf" ], "vignetteTitles": [ "Introduction to QDNAseq" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/QDNAseq/inst/doc/QDNAseq.R" ], "dependsOnMe": [ "GeneBreak", "QDNAseq.hg19", "QDNAseq.mm10" ] }, "qpcrNorm": { "Package": "qpcrNorm", "Version": "1.32.0", "Depends": [ "methods", "Biobase", "limma", "affy" ], "License": "LGPL (>= 2)", "MD5sum": "d2898866eadc6b3d46a32f3c08a4825e", "NeedsCompilation": "no", "Title": "Data-driven normalization strategies for high-throughput qPCR data.", "Description": "The package contains functions to perform normalization of high-throughput qPCR data. Basic functions for processing raw Ct data plus functions to generate diagnostic plots are also available.", "biocViews": [ "GeneExpression", "Preprocessing", "Software" ], "Author": "Jessica Mar", "Maintainer": "Jessica Mar ", "source.ver": "src/contrib/qpcrNorm_1.32.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/qpcrNorm_1.32.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/qpcrNorm_1.32.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/qpcrNorm_1.32.0.tgz", "vignettes": [ "vignettes/qpcrNorm/inst/doc/qpcrNorm.pdf" ], "vignetteTitles": [ "qPCR Normalization Example" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/qpcrNorm/inst/doc/qpcrNorm.R" ], "suggestsMe": [ "EasyqpcR" ] }, "qpgraph": { "Package": "qpgraph", "Version": "2.8.3", "Depends": [ "R (>= 3.0.0)" ], "Imports": [ "methods", "parallel", "Matrix (>= 1.0)", "grid", "annotate", "graph (>= 1.45.1)", "Biobase", "S4Vectors", "BiocParallel", "AnnotationDbi", "IRanges", "GenomeInfoDb", "GenomicRanges", "GenomicFeatures", "mvtnorm", "qtl", "Rgraphviz" ], "Suggests": [ "RUnit", "BiocGenerics", "BiocStyle", "genefilter", "org.EcK12.eg.db", "rlecuyer", "snow", "Category", "GOstats" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "cea07f3dc76aa306619dbb28d9c0eb00", "NeedsCompilation": "yes", "Title": "Estimation of genetic and molecular regulatory networks from high-throughput genomics data", "Description": "Estimate gene and eQTL networks from high-throughput expression and genotyping assays.", "biocViews": [ "GeneExpression", "GeneRegulation", "GeneticVariability", "Genetics", "GraphAndNetwork", "Microarray", "NetworkInference", "Pathways", "SNP", "Software", "Transcription" ], "Author": "Robert Castelo [aut, cre], Alberto Roverato [aut]", "Maintainer": "Robert Castelo ", "URL": "http://functionalgenomics.upf.edu/qpgraph", "source.ver": "src/contrib/qpgraph_2.8.3.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/qpgraph_2.8.3.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/qpgraph_2.8.3.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/qpgraph_2.8.3.tgz", "vignettes": [ "vignettes/qpgraph/inst/doc/BasicUsersGuide.pdf", "vignettes/qpgraph/inst/doc/eQTLnetworks.pdf", "vignettes/qpgraph/inst/doc/qpgraphSimulate.pdf", "vignettes/qpgraph/inst/doc/qpTxRegNet.pdf" ], "vignetteTitles": [ "BasicUsersGuide.pdf", "Estimate eQTL networks using qpgraph", "Simulating molecular regulatory networks using qpgraph", "Reverse-engineer transcriptional regulatory networks using qpgraph" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/qpgraph/inst/doc/eQTLnetworks.R", "vignettes/qpgraph/inst/doc/qpgraphSimulate.R", "vignettes/qpgraph/inst/doc/qpTxRegNet.R" ], "importsMe": [ "clipper", "ToPASeq" ] }, "qrqc": { "Package": "qrqc", "Version": "1.28.0", "Depends": [ "reshape", "ggplot2", "Biostrings", "biovizBase", "brew", "xtable", "Rsamtools (>= 1.19.38)", "testthat" ], "Imports": [ "reshape", "ggplot2", "Biostrings", "biovizBase", "graphics", "methods", "plyr", "stats" ], "LinkingTo": [ "Rsamtools" ], "License": "GPL (>=2)", "Archs": "i386, x64", "MD5sum": "0d154b99b219d3b18c1fe3c4636aacf6", "NeedsCompilation": "yes", "Title": "Quick Read Quality Control", "Description": "Quickly scans reads and gathers statistics on base and quality frequencies, read length, k-mers by position, and frequent sequences. Produces graphical output of statistics for use in quality control pipelines, and an optional HTML quality report. S4 SequenceSummary objects allow specific tests and functionality to be written around the data collected.", "biocViews": [ "DataImport", "Preprocessing", "QualityControl", "Sequencing", "Software", "Visualization" ], "Author": "Vince Buffalo", "Maintainer": "Vince Buffalo ", "URL": "http://github.com/vsbuffalo/qrqc", "source.ver": "src/contrib/qrqc_1.28.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/qrqc_1.28.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/qrqc_1.28.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/qrqc_1.28.0.tgz", "vignettes": [ "vignettes/qrqc/inst/doc/qrqc.pdf" ], "vignetteTitles": [ "Using the qrqc package to gather information about sequence qualities" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/qrqc/inst/doc/qrqc.R" ] }, "qsea": { "Package": "qsea", "Version": "1.0.3", "Depends": [ "R (>= 3.3)" ], "Imports": [ "Biostrings", "graphics", "gtools", "methods", "stats", "utils", "HMMcopy", "rtracklayer", "BSgenome", "GenomicRanges", "Rsamtools", "IRanges", "limma", "GenomeInfoDb", "BiocGenerics", "grDevices", "zoo", "BiocParallel" ], "Suggests": [ "BSgenome.Hsapiens.UCSC.hg19", "MEDIPSData", "testthat", "BiocStyle", "knitr", "rmarkdown" ], "License": "GPL (>=2)", "Archs": "i386, x64", "MD5sum": "9096a800258065725b76a6bf474d4c2d", "NeedsCompilation": "yes", "Title": "IP-seq data analysis and vizualization", "Description": "qsea (quantitative sequencing enrichment analysis) was developed as the successor of the MEDIPS package for analyzing data derived from methylated DNA immunoprecipitation (MeDIP) experiments followed by sequencing (MeDIP-seq). However, qsea provides several functionalities for the analysis of other kinds of quantitative sequencing data (e.g. ChIP-seq, MBD-seq, CMS-seq and others) including calculation of differential enrichment between groups of samples.", "biocViews": [ "ChIPSeq", "ChipOnChip", "CopyNumberVariation", "CpGIsland", "DNAMethylation", "DifferentialMethylation", "Normalization", "Preprocessing", "QualityControl", "Sequencing", "Software", "Visualization" ], "Author": "Matthias Lienhard, Lukas Chavez, Ralf Herwig", "Maintainer": "Matthias Lienhard ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/qsea_1.0.3.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/qsea_1.0.3.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/qsea_1.0.3.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/qsea_1.0.3.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/qsea/inst/doc/qsea_tutorial.R" ], "htmlDocs": [ "vignettes/qsea/inst/doc/qsea_tutorial.html" ], "htmlTitles": [ "qsea" ] }, "QUALIFIER": { "Package": "QUALIFIER", "Version": "1.18.0", "Depends": [ "R (>= 2.14.0)", "flowCore", "flowViz", "ncdfFlow", "flowWorkspace", "data.table", "reshape" ], "Imports": [ "MASS", "hwriter", "lattice", "stats4", "flowCore", "flowViz", "methods", "flowWorkspace", "latticeExtra", "grDevices", "tools", "Biobase", "XML", "grid" ], "Suggests": [ "RSVGTipsDevice", "knitr" ], "License": "Artistic-2.0", "MD5sum": "1220c1616d03d87a291775dd49f27ba0", "NeedsCompilation": "no", "Title": "Quality Control of Gated Flow Cytometry Experiments", "Description": "Provides quality control and quality assessment tools for gated flow cytometry data.", "biocViews": [ "CellBasedAssays", "FlowCytometry", "Infrastructure", "Software" ], "Author": "Mike Jiang,Greg Finak,Raphael Gottardo", "Maintainer": "Mike Jiang ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/QUALIFIER_1.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/QUALIFIER_1.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/QUALIFIER_1.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/QUALIFIER_1.18.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false }, "quantro": { "Package": "quantro", "Version": "1.8.0", "Depends": [ "R (>= 3.1.3)" ], "Imports": [ "Biobase", "minfi", "doParallel", "foreach", "iterators", "ggplot2", "methods", "RColorBrewer" ], "Suggests": [ "knitr", "RUnit", "BiocGenerics", "BiocStyle" ], "License": "GPL (>=3)", "MD5sum": "a462268dac719fd90b12f970715e24f1", "NeedsCompilation": "no", "Title": "A test for when to use quantile normalization", "Description": "A data-driven test for the assumptions of quantile normalization using raw data such as objects that inherit eSets (e.g. ExpressionSet, MethylSet). Group level information about each sample (such as Tumor / Normal status) must also be provided because the test assesses if there are global differences in the distributions between the user-defined groups.", "biocViews": [ "Microarray", "MultipleComparison", "Normalization", "Preprocessing", "Sequencing", "Software" ], "Author": "Stephanie Hicks and Rafael Irizarry", "Maintainer": "Stephanie Hicks ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/quantro_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/quantro_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/quantro_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/quantro_1.8.0.tgz", "vignettes": [ "vignettes/quantro/inst/doc/quantro-vignette.pdf" ], "vignetteTitles": [ "The quantro user's guide" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/quantro/inst/doc/quantro-vignette.R" ], "importsMe": [ "yarn" ] }, "quantsmooth": { "Package": "quantsmooth", "Version": "1.40.0", "Depends": [ "R(>= 2.10.0)", "quantreg", "grid" ], "License": "GPL-2", "MD5sum": "4406cd2d33564b4cadbea71459564905", "NeedsCompilation": "no", "Title": "Quantile smoothing and genomic visualization of array data", "Description": "Implements quantile smoothing as introduced in: Quantile smoothing of array CGH data; Eilers PH, de Menezes RX; Bioinformatics. 2005 Apr 1;21(7):1146-53.", "biocViews": [ "CopyNumberVariation", "Software", "Visualization" ], "Author": "Jan Oosting, Paul Eilers, Renee Menezes", "Maintainer": "Jan Oosting ", "source.ver": "src/contrib/quantsmooth_1.40.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/quantsmooth_1.40.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/quantsmooth_1.40.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/quantsmooth_1.40.0.tgz", "vignettes": [ "vignettes/quantsmooth/inst/doc/quantsmooth.pdf" ], "vignetteTitles": [ "quantsmooth" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/quantsmooth/inst/doc/quantsmooth.R" ], "dependsOnMe": [ "beadarraySNP" ], "importsMe": [ "GWASTools", "SIM" ], "suggestsMe": [ "PREDA" ] }, "QuartPAC": { "Package": "QuartPAC", "Version": "1.6.0", "Depends": [ "iPAC", "GraphPAC", "SpacePAC", "data.table" ], "Suggests": [ "RUnit", "BiocGenerics", "rgl" ], "License": "GPL-2", "MD5sum": "d16a2be6286d3bc8a01963201153ba9e", "NeedsCompilation": "no", "Title": "Identification of mutational clusters in protein quaternary structures.", "Description": "Identifies clustering of somatic mutations in proteins over the entire quaternary structure.", "biocViews": [ "Clustering", "Proteomics", "Software", "SomaticMutation" ], "Author": "Gregory Ryslik, Yuwei Cheng, Hongyu Zhao", "Maintainer": "Gregory Ryslik ", "source.ver": "src/contrib/QuartPAC_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/QuartPAC_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/QuartPAC_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/QuartPAC_1.6.0.tgz", "vignettes": [ "vignettes/QuartPAC/inst/doc/QuartPAC.pdf" ], "vignetteTitles": [ "SpacePAC: Identifying mutational clusters in 3D protein space using simulation" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/QuartPAC/inst/doc/QuartPAC.R" ] }, "QuasR": { "Package": "QuasR", "Version": "1.14.0", "Depends": [ "parallel", "GenomicRanges (>= 1.13.3)", "Rbowtie" ], "Imports": [ "methods", "grDevices", "graphics", "utils", "zlibbioc", "BiocGenerics", "S4Vectors (>= 0.9.25)", "IRanges", "BiocInstaller", "Biobase", "Biostrings", "BSgenome", "Rsamtools (>= 1.19.38)", "GenomicFeatures (>= 1.17.13)", "ShortRead (>= 1.19.1)", "GenomicAlignments", "BiocParallel", "GenomeInfoDb", "rtracklayer", "GenomicFiles" ], "LinkingTo": [ "Rsamtools" ], "Suggests": [ "Gviz", "RUnit", "BiocStyle" ], "License": "GPL-2", "Archs": "x64", "MD5sum": "16224a42105d200de34c86eb5912e1fd", "NeedsCompilation": "yes", "Title": "Quantify and Annotate Short Reads in R", "Description": "This package provides a framework for the quantification and analysis of Short Reads. It covers a complete workflow starting from raw sequence reads, over creation of alignments and quality control plots, to the quantification of genomic regions of interest.", "biocViews": [ "Alignment", "ChIPSeq", "Coverage", "Genetics", "MethylSeq", "Preprocessing", "QualityControl", "RNASeq", "Sequencing", "Software" ], "Author": "Anita Lerch, Dimos Gaiditzis and Michael Stadler", "Maintainer": "Michael Stadler ", "source.ver": "src/contrib/QuasR_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/QuasR_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/QuasR_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/QuasR_1.14.0.tgz", "vignettes": [ "vignettes/QuasR/inst/doc/QuasR.pdf" ], "vignetteTitles": [ "An introduction to QuasR" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/QuasR/inst/doc/QuasR.R" ] }, "QuaternaryProd": { "Package": "QuaternaryProd", "Version": "1.2.0", "Depends": [ "R (>= 3.2.0)", "Rcpp (>= 0.11.3)" ], "LinkingTo": [ "Rcpp" ], "Suggests": [ "readr", "org.Hs.eg.db", "dplyr", "stringr", "knitr", "fdrtool" ], "License": "GPL (>=3)", "Archs": "i386, x64", "MD5sum": "96afcc8c00756a9d6f511aa3986b1907", "NeedsCompilation": "yes", "Title": "Computes the Quaternary Dot Product Scoring Statistic for Signed and Unsigned Causal Graphs", "Description": "QuaternaryProd is an R package that performs causal reasoning on biological networks, including publicly available networks such as String-db. QuaternaryProd is a free alternative to commercial products such as Quiagen and Inginuity pathway analysis. For a given a set of differentially expressed genes, QuaternaryProd computes the significance of upstream regulators in the network by performing causal reasoning using the Quaternary Dot Product Scoring Statistic (Quaternary Statistic), Ternary Dot product Scoring Statistic (Ternary Statistic) and Fisher's exact test. The Quaternary Statistic handles signed, unsigned and ambiguous edges in the network. Ambiguity arises when the direction of causality is unknown, or when the source node (e.g., a protein) has edges with conflicting signs for the same target gene. On the other hand, the Ternary Statistic provides causal reasoning using the signed and unambiguous edges only. The Vignette provides more details on the Quaternary Statistic and illustrates an example of how to perform causal reasoning using String-db.", "biocViews": [ "GeneExpression", "GraphAndNetwork", "Software", "Transcription" ], "Author": "Carl Tony Fakhry [cre, aut], Ping Chen [ths], Kourosh Zarringhalam [aut, ths]", "Maintainer": "Carl Tony Fakhry ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/QuaternaryProd_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/QuaternaryProd_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/QuaternaryProd_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/QuaternaryProd_1.2.0.tgz", "vignettes": [ "vignettes/QuaternaryProd/inst/doc/QuaternaryProdVignette.pdf" ], "vignetteTitles": [ "QuaternaryProdVignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/QuaternaryProd/inst/doc/QuaternaryProdVignette.R" ] }, "QUBIC": { "Package": "QUBIC", "Version": "1.2.1", "Depends": [ "R (>= 3.1)", "biclust" ], "Imports": [ "Rcpp (>= 0.11.0)", "methods", "Matrix" ], "LinkingTo": [ "Rcpp", "RcppArmadillo" ], "Suggests": [ "QUBICdata", "qgraph", "fields", "knitr", "rmarkdown" ], "Enhances": [ "RColorBrewer" ], "License": "CC BY-NC-ND 4.0 + file LICENSE", "Archs": "i386, x64", "MD5sum": "ee366ceae5a7a4d1d49d2c3b96a44b3a", "NeedsCompilation": "yes", "Title": "An R package for qualitative biclustering in support of gene co-expression analyses", "Description": "The core function of this R package is to provide the implementation of the well-cited and well-reviewed QUBIC algorithm, aiming to deliver an effective and efficient biclustering capability. This package also includes the following related functions: (i) a qualitative representation of the input gene expression data, through a well-designed discretization way considering the underlying data property, which can be directly used in other biclustering programs; (ii) visualization of identified biclusters using heatmap in support of overall expression pattern analysis; (iii) bicluster-based co-expression network elucidation and visualization, where different correlation coefficient scores between a pair of genes are provided; and (iv) a generalize output format of biclusters and corresponding network can be freely downloaded so that a user can easily do following comprehensive functional enrichment analysis (e.g. DAVID) and advanced network visualization (e.g. Cytoscape).", "biocViews": [ "Clustering", "DifferentialExpression", "GeneExpression", "Microarray", "MultipleComparison", "Network", "Software", "StatisticalMethod", "Visualization" ], "Author": "Yu Zhang [aut, cre], Qin Ma [aut]", "Maintainer": "Yu Zhang ", "URL": "http://github.com/zy26/QUBIC", "SystemRequirements": "C++11, Rtools (>= 3.1)", "VignetteBuilder": "knitr", "BugReports": "http://github.com/zy26/QUBIC/issues", "source.ver": "src/contrib/QUBIC_1.2.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/QUBIC_1.2.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/QUBIC_1.2.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/QUBIC_1.2.1.tgz", "vignettes": [ "vignettes/QUBIC/inst/doc/qubic_vignette.pdf" ], "vignetteTitles": [ "QUBIC Tutorial" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/QUBIC/inst/doc/qubic_vignette.R" ] }, "qusage": { "Package": "qusage", "Version": "2.6.1", "Depends": [ "R (>= 2.10)", "limma (>= 3.14)", "methods" ], "Imports": [ "utils", "Biobase", "nlme", "lsmeans" ], "License": "GPL (>= 2)", "MD5sum": "faf01cb6cfd29c9923a8b00f299da13b", "NeedsCompilation": "no", "Title": "qusage: Quantitative Set Analysis for Gene Expression", "Description": "This package is an implementation the Quantitative Set Analysis for Gene Expression (QuSAGE) method described in (Yaari G. et al, Nucl Acids Res, 2013). This is a novel Gene Set Enrichment-type test, which is designed to provide a faster, more accurate, and easier to understand test for gene expression studies. qusage accounts for inter-gene correlations using the Variance Inflation Factor technique proposed by Wu et al. (Nucleic Acids Res, 2012). In addition, rather than simply evaluating the deviation from a null hypothesis with a single number (a P value), qusage quantifies gene set activity with a complete probability density function (PDF). From this PDF, P values and confidence intervals can be easily extracted. Preserving the PDF also allows for post-hoc analysis (e.g., pair-wise comparisons of gene set activity) while maintaining statistical traceability. Finally, while qusage is compatible with individual gene statistics from existing methods (e.g., LIMMA), a Welch-based method is implemented that is shown to improve specificity. For questions, contact Chris Bolen (cbolen1@gmail.com) or Steven Kleinstein (steven.kleinstein@yale.edu)", "biocViews": [ "GeneSetEnrichment", "Microarray", "RNASeq", "Software" ], "Author": "Christopher Bolen and Gur Yaari, with contributions from Juilee Thakar, Hailong Meng, Jacob Turner, Derek Blankenship, and Steven Kleinstein", "Maintainer": "Christopher Bolen ", "URL": "http://clip.med.yale.edu/qusage", "source.ver": "src/contrib/qusage_2.6.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/qusage_2.6.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/qusage_2.6.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/qusage_2.6.1.tgz", "vignettes": [ "vignettes/qusage/inst/doc/qusage.pdf" ], "vignetteTitles": [ "Running qusage" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/qusage/inst/doc/qusage.R" ], "suggestsMe": [ "SigCheck" ] }, "qvalue": { "Package": "qvalue", "Version": "2.6.0", "Depends": [ "R(>= 2.10)" ], "Imports": [ "splines", "ggplot2", "grid", "reshape2" ], "Suggests": [ "knitr" ], "License": "LGPL", "MD5sum": "be8b7972cb37667edd96948c9b56ce89", "NeedsCompilation": "no", "Title": "Q-value estimation for false discovery rate control", "Description": "This package takes a list of p-values resulting from the simultaneous testing of many hypotheses and estimates their q-values and local FDR values. The q-value of a test measures the proportion of false positives incurred (called the false discovery rate) when that particular test is called significant. The local FDR measures the posterior probability the null hypothesis is true given the test's p-value. Various plots are automatically generated, allowing one to make sensible significance cut-offs. Several mathematical results have recently been shown on the conservative accuracy of the estimated q-values from this software. The software can be applied to problems in genomics, brain imaging, astrophysics, and data mining.", "biocViews": [ "MultipleComparisons", "Software" ], "Author": "John D. Storey with contributions from Andrew J. Bass, Alan Dabney and David Robinson", "Maintainer": "John D. Storey , Andrew J. Bass ", "URL": "http://github.com/jdstorey/qvalue", "VignetteBuilder": "knitr", "source.ver": "src/contrib/qvalue_2.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/qvalue_2.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/qvalue_2.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/qvalue_2.6.0.tgz", "vignettes": [ "vignettes/qvalue/inst/doc/qvalue.pdf" ], "vignetteTitles": [ "qvalue Package" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/qvalue/inst/doc/qvalue.R" ], "dependsOnMe": [ "anota", "CancerMutationAnalysis", "ChimpHumanBrainData", "DEGseq", "DrugVsDisease", "metaseqR", "prot2D", "r3Cseq", "SSPA", "webbioc" ], "importsMe": [ "Anaquin", "anota", "ChAMP", "clusterProfiler", "derfinder", "DOSE", "edge", "erccdashboard", "IHWpaper", "methylKit", "msmsTests", "netresponse", "normr", "Rnits", "sights", "sRAP", "subSeq", "synapter", "trigger", "webbioc" ], "suggestsMe": [ "biobroom", "LBE", "maanova", "PREDA", "RNAinteractMAPK" ] }, "R3CPET": { "Package": "R3CPET", "Version": "1.6.0", "Depends": [ "R (>= 3.2)", "Rcpp (>= 0.10.4)", "methods" ], "Imports": [ "methods", "parallel", "clues", "ggplot2", "pheatmap", "clValid", "igraph", "data.table", "reshape2", "Hmisc", "RCurl", "BiocGenerics", "S4Vectors", "IRanges", "GenomeInfoDb", "GenomicRanges", "ggbio" ], "LinkingTo": [ "Rcpp" ], "Suggests": [ "BiocStyle", "knitr", "TxDb.Hsapiens.UCSC.hg19.knownGene", "biovizBase", "biomaRt", "AnnotationDbi", "org.Hs.eg.db", "shiny", "ChIPpeakAnno" ], "License": "GPL (>=2)", "Archs": "i386, x64", "MD5sum": "93d4b83cef6e0c1600563d8eb7d33074", "NeedsCompilation": "yes", "Title": "3CPET: Finding Co-factor Complexes in Chia-PET experiment using a Hierarchical Dirichlet Process", "Description": "The package provides a method to infer the set of proteins that are more probably to work together to maintain chormatin interaction given a ChIA-PET experiment results.", "biocViews": [ "Bayesian", "GeneExpression", "GenePrediction", "GraphAndNetwork", "Network", "NetworkInference", "Software" ], "Author": "Djekidel MN, Yang Chen et al.", "Maintainer": "Mohamed Nadhir Djekidel ", "VignetteBuilder": "knitr", "BugReports": "https://github.com/sirusb/R3CPET/issues", "source.ver": "src/contrib/R3CPET_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/R3CPET_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/R3CPET_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/R3CPET_1.6.0.tgz", "vignettes": [ "vignettes/R3CPET/inst/doc/R3CPET.pdf" ], "vignetteTitles": [ "3CPET: Finding Co-factor Complexes maintaining Chia-PET interactions" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/R3CPET/inst/doc/R3CPET.R" ] }, "r3Cseq": { "Package": "r3Cseq", "Version": "1.20.0", "Depends": [ "GenomicRanges", "Rsamtools", "rtracklayer", "VGAM", "qvalue" ], "Imports": [ "methods", "GenomeInfoDb", "IRanges", "Biostrings", "data.table", "sqldf", "RColorBrewer" ], "Suggests": [ "BSgenome.Mmusculus.UCSC.mm9.masked", "BSgenome.Mmusculus.UCSC.mm10.masked", "BSgenome.Hsapiens.UCSC.hg18.masked", "BSgenome.Hsapiens.UCSC.hg19.masked", "BSgenome.Rnorvegicus.UCSC.rn5.masked" ], "License": "GPL-3", "MD5sum": "01a3a820eb604116269a05195b8ac69c", "NeedsCompilation": "no", "Title": "Analysis of Chromosome Conformation Capture and Next-generation Sequencing (3C-seq)", "Description": "This package is an implementation of data analysis for the long-range interactions from 3C-seq assay.", "biocViews": [ "Preprocessing", "Sequencing", "Software" ], "Author": "Supat Thongjuea, MRC Molecular Haematology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, UK ", "Maintainer": "Supat Thongjuea ", "URL": "http://r3cseq.genereg.net", "source.ver": "src/contrib/r3Cseq_1.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/r3Cseq_1.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/r3Cseq_1.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/r3Cseq_1.20.0.tgz", "vignettes": [ "vignettes/r3Cseq/inst/doc/r3Cseq.pdf" ], "vignetteTitles": [ "r3Cseq" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/r3Cseq/inst/doc/r3Cseq.R" ] }, "R453Plus1Toolbox": { "Package": "R453Plus1Toolbox", "Version": "1.24.0", "Depends": [ "R (>= 2.12.0)", "methods", "VariantAnnotation", "Biostrings", "Biobase" ], "Imports": [ "utils", "grDevices", "graphics", "stats", "tools", "xtable", "R2HTML", "TeachingDemos", "BiocGenerics", "S4Vectors (>= 0.9.25)", "IRanges", "XVector", "GenomicRanges", "SummarizedExperiment", "biomaRt", "BSgenome", "Rsamtools", "ShortRead" ], "Suggests": [ "rtracklayer", "BSgenome.Hsapiens.UCSC.hg19", "BSgenome.Scerevisiae.UCSC.sacCer2" ], "License": "LGPL-3", "Archs": "i386, x64", "MD5sum": "25c40b05775534afe4e0cdbd9c96edb1", "NeedsCompilation": "yes", "Title": "A package for importing and analyzing data from Roche's Genome Sequencer System", "Description": "The R453Plus1 Toolbox comprises useful functions for the analysis of data generated by Roche's 454 sequencing platform. It adds functions for quality assurance as well as for annotation and visualization of detected variants, complementing the software tools shipped by Roche with their product. Further, a pipeline for the detection of structural variants is provided.", "biocViews": [ "DataImport", "DataRepresentation", "Infrastructure", "QualityControl", "ReportWriting", "Sequencing", "Software", "Visualization" ], "Author": "Hans-Ulrich Klein, Christoph Bartenhagen, Christian Ruckert", "Maintainer": "Hans-Ulrich Klein ", "source.ver": "src/contrib/R453Plus1Toolbox_1.24.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/R453Plus1Toolbox_1.24.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/R453Plus1Toolbox_1.24.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/R453Plus1Toolbox_1.24.0.tgz", "vignettes": [ "vignettes/R453Plus1Toolbox/inst/doc/vignette.pdf" ], "vignetteTitles": [ "A package for importing and analyzing data from Roche's Genome Sequencer System" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/R453Plus1Toolbox/inst/doc/vignette.R" ] }, "R4RNA": { "Package": "R4RNA", "Version": "1.2.0", "Depends": [ "R (>= 3.2.0)", "Biostrings (>= 2.38.0)" ], "License": "GPL-3", "MD5sum": "a09d285a6408229838a9610529defb80", "NeedsCompilation": "no", "Title": "An R package for RNA visualization and analysis", "Description": "A package for RNA basepair analysis, including the visualization of basepairs as arc diagrams for easy comparison and annotation of sequence and structure. Arc diagrams can additionally be projected onto multiple sequence alignments to assess basepair conservation and covariation, with numerical methods for computing statistics for each.", "biocViews": [ "Alignment", "DataImport", "DataRepresentation", "MultipleComparison", "MultipleSequenceAlignment", "Preprocessing", "Software", "Visualization" ], "Author": "Daniel Lai, Irmtraud Meyer ", "Maintainer": "Daniel Lai ", "URL": "http://www.e-rna.org/r-chie/", "source.ver": "src/contrib/R4RNA_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/R4RNA_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/R4RNA_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/R4RNA_1.2.0.tgz", "vignettes": [ "vignettes/R4RNA/inst/doc/R4RNA.pdf" ], "vignetteTitles": [ "R4RNA" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/R4RNA/inst/doc/R4RNA.R" ] }, "rain": { "Package": "rain", "Version": "1.8.0", "Depends": [ "R (>= 2.10)", "gmp", "multtest" ], "Suggests": [ "lattice", "BiocStyle" ], "License": "GPL-2", "MD5sum": "f2401b4582ae13efbe4530633ae5472c", "NeedsCompilation": "no", "Title": "Rhythmicity Analysis Incorporating Non-parametric Methods", "Description": "This package uses non-parametric methods to detect rhythms in time series. It deals with outliers, missing values and is optimized for time series comprising 10-100 measurements. As it does not assume expect any distinct waveform it is optimal or detecting oscillating behavior (e.g. circadian or cell cycle) in e.g. genome- or proteome-wide biological measurements such as: micro arrays, proteome mass spectrometry, or metabolome measurements.", "biocViews": [ "Genetics", "Microarray", "MultipleComparison", "Proteomics", "Software", "SystemsBiology", "TimeCourse" ], "Author": "Paul F. Thaben, Pål O. Westermark", "Maintainer": "Paul F. Thaben ", "source.ver": "src/contrib/rain_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/rain_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/rain_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/rain_1.8.0.tgz", "vignettes": [ "vignettes/rain/inst/doc/rain.pdf" ], "vignetteTitles": [ "Rain Usage" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/rain/inst/doc/rain.R" ] }, "rama": { "Package": "rama", "Version": "1.48.0", "Depends": [ "R(>= 2.5.0)" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "f96341350b20129944f4d7c009999002", "NeedsCompilation": "yes", "Title": "Robust Analysis of MicroArrays", "Description": "Robust estimation of cDNA microarray intensities with replicates. The package uses a Bayesian hierarchical model for the robust estimation. Outliers are modeled explicitly using a t-distribution, and the model also addresses classical issues such as design effects, normalization, transformation, and nonconstant variance.", "biocViews": [ "Microarray", "Preprocessing", "QualityControl", "Software", "TwoChannel" ], "Author": "Raphael Gottardo", "Maintainer": "Raphael Gottardo ", "source.ver": "src/contrib/rama_1.48.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/rama_1.48.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/rama_1.48.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/rama_1.48.0.tgz", "vignettes": [ "vignettes/rama/inst/doc/rama.pdf" ], "vignetteTitles": [ "rama Tutorial" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/rama/inst/doc/rama.R" ], "dependsOnMe": [ "bridge" ] }, "RamiGO": { "Package": "RamiGO", "Version": "1.20.0", "Depends": [ "gsubfn", "methods" ], "Imports": [ "igraph", "RCurl", "png", "RCytoscape", "graph" ], "License": "Artistic-2.0", "MD5sum": "6656f5a3a7979ce8b90db5fb72da0895", "NeedsCompilation": "no", "Title": "AmiGO visualize R interface", "Description": "R interface sending requests to AmiGO visualize, retrieving DAG GO trees, parsing GraphViz DOT format files and exporting GML files for Cytoscape. Also uses RCytoscape to interactively display AmiGO trees in Cytoscape.", "biocViews": [ "Classification", "GO", "GraphAndNetwork", "Software", "ThirdPartyClient", "Visualization" ], "Author": "Markus Schroeder, Daniel Gusenleitner, John Quackenbush, Aedin Culhane, Benjamin Haibe-Kains", "Maintainer": "Markus Schroeder ", "source.ver": "src/contrib/RamiGO_1.20.0.tar.gz", "vignettes": [ "vignettes/RamiGO/inst/doc/RamiGO.pdf" ], "vignetteTitles": [ "RamiGO: An Introduction (HowTo)" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RamiGO/inst/doc/RamiGO.R" ] }, "randPack": { "Package": "randPack", "Version": "1.20.0", "Depends": [ "methods" ], "Imports": [ "Biobase" ], "License": "Artistic 2.0", "MD5sum": "ce62a6ada68ebc617d2ae2a33b19b074", "NeedsCompilation": "no", "Title": "Randomization routines for Clinical Trials", "Description": "A suite of classes and functions for randomizing patients in clinical trials.", "biocViews": [ "Software", "StatisticalMethod" ], "Author": "Vincent Carey and Robert Gentleman", "Maintainer": "Robert Gentleman ", "source.ver": "src/contrib/randPack_1.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/randPack_1.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/randPack_1.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/randPack_1.20.0.tgz", "vignettes": [ "vignettes/randPack/inst/doc/randPack.pdf" ], "vignetteTitles": [ "Clinical trial randomization infrastructure" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/randPack/inst/doc/randPack.R" ] }, "RankProd": { "Package": "RankProd", "Version": "3.0.0", "Depends": [ "R (>= 3.2.1)", "stats", "methods", "Rmpfr", "gmp" ], "Imports": [ "graphics" ], "License": "file LICENSE", "License_restricts_use": "yes", "MD5sum": "95c9215478783018eeafc7aae084f3fb", "NeedsCompilation": "no", "Title": "Rank Product method for identifying differentially expressed genes with application in meta-analysis", "Description": "Non-parametric method for identifying differentially expressed (up- or down- regulated) genes based on the estimated percentage of false predictions (pfp). The method can combine data sets from different origins (meta-analysis) to increase the power of the identification.", "biocViews": [ "DifferentialExpression", "GeneExpression", "GeneSignaling", "Lipidomics", "Metabolomics", "Microarray", "Proteomics", "ResearchField", "Software", "StatisticalMethod", "SystemsBiology" ], "Author": "Francesco Del Carratore , Andris Janckevics Fangxin Hong , Ben Wittner , Rainer Breitling , and Florian Battke ", "Maintainer": "Francesco Del Carratore ", "source.ver": "src/contrib/RankProd_3.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RankProd_3.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RankProd_3.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RankProd_3.0.0.tgz", "vignettes": [ "vignettes/RankProd/inst/doc/RankProd.pdf" ], "vignetteTitles": [ "RankProd Tutorial" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/RankProd/inst/doc/RankProd.R" ], "dependsOnMe": [ "RNAither", "tRanslatome" ], "importsMe": [ "HTSanalyzeR", "synlet" ], "suggestsMe": [ "oneChannelGUI" ] }, "RareVariantVis": { "Package": "RareVariantVis", "Version": "1.8.0", "Depends": [ "BiocGenerics", "VariantAnnotation", "googleVis" ], "Imports": [ "S4Vectors", "IRanges", "GenomeInfoDb", "GenomicRanges" ], "Suggests": [ "knitr", "AshkenazimSonChr21" ], "License": "Artistic-2.0", "MD5sum": "0ba655ca0daca9a939c4bb6709a7d481", "NeedsCompilation": "no", "Title": "Visualization of rare variants in whole genome sequencing data", "Description": "Genomic variants can be analyzed and visualized using many tools. Unfortunately, number of tools for global interrogation of variants is limited. Package RareVariantVis aims to present genomic variants (especially rare ones) in a global, per chromosome way. Visualization is performed in two ways - standard that outputs png figures and interactive that uses JavaScript d3 package. Interactive visualization allows to analyze trio/family data, for example in search for causative variants in rare Mendelian diseases.", "biocViews": [ "GenomicVariation", "Sequencing", "Software", "WholeGenome" ], "Author": "Tomasz Stokowy", "Maintainer": "Tomasz Stokowy ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/RareVariantVis_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RareVariantVis_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RareVariantVis_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RareVariantVis_1.8.0.tgz", "vignettes": [ "vignettes/RareVariantVis/inst/doc/RareVariantsVis.pdf" ], "vignetteTitles": [ "RareVariantVis" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RareVariantVis/inst/doc/RareVariantsVis.R" ] }, "Rariant": { "Package": "Rariant", "Version": "1.10.0", "Depends": [ "R (>= 3.0.2)", "GenomicRanges", "VariantAnnotation" ], "Imports": [ "methods", "S4Vectors", "IRanges", "GenomeInfoDb", "ggbio", "ggplot2", "exomeCopy", "SomaticSignatures", "Rsamtools", "shiny", "VGAM", "dplyr", "reshape2" ], "Suggests": [ "h5vcData", "testthat", "knitr", "optparse", "BSgenome.Hsapiens.UCSC.hg19" ], "License": "GPL-3", "MD5sum": "bf4c6d416960c946b2592a054e2840c1", "NeedsCompilation": "no", "Title": "Identification and Assessment of Single Nucleotide Variants through Shifts in Non-Consensus Base Call Frequencies", "Description": "The 'Rariant' package identifies single nucleotide variants from sequencing data based on the difference of binomially distributed mismatch rates between matched samples.", "biocViews": [ "GenomicVariation", "Sequencing", "Software", "SomaticMutation", "StatisticalMethod", "VariantDetection", "Visualization" ], "Author": "Julian Gehring, Simon Anders, Bernd Klaus", "Maintainer": "Julian Gehring ", "URL": "https://github.com/juliangehring/Rariant", "VignetteBuilder": "knitr", "BugReports": "https://support.bioconductor.org", "source.ver": "src/contrib/Rariant_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Rariant_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Rariant_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Rariant_1.10.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Rariant/inst/doc/Rariant-vignette.R" ], "htmlDocs": [ "vignettes/Rariant/inst/doc/Rariant-vignette.html" ], "htmlTitles": [ "Rariant" ] }, "RbcBook1": { "Package": "RbcBook1", "Version": "1.42.0", "Depends": [ "R (>= 2.10)", "Biobase", "graph", "rpart" ], "License": "Artistic-2.0", "MD5sum": "829cafd37333007c39e358263172afdf", "NeedsCompilation": "no", "Title": "Support for Springer monograph on Bioconductor", "Description": "tools for building book", "biocViews": [ "Software" ], "Author": "Vince Carey and Wolfgang Huber ", "Maintainer": "Vince Carey ", "URL": "http://www.biostat.harvard.edu/~carey", "source.ver": "src/contrib/RbcBook1_1.42.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RbcBook1_1.42.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RbcBook1_1.42.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RbcBook1_1.42.0.tgz", "vignettes": [ "vignettes/RbcBook1/inst/doc/RbcBook1.pdf" ], "vignetteTitles": [ "RbcBook1 Primer" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RbcBook1/inst/doc/RbcBook1.R" ] }, "RBGL": { "Package": "RBGL", "Version": "1.50.0", "Depends": [ "graph", "methods" ], "Imports": [ "methods" ], "Suggests": [ "Rgraphviz", "XML", "RUnit", "BiocGenerics" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "5fae5f13886bd33c5a8cfcc356f00f72", "NeedsCompilation": "yes", "Title": "An interface to the BOOST graph library", "Description": "A fairly extensive and comprehensive interface to the graph algorithms contained in the BOOST library.", "biocViews": [ "GraphAndNetwork", "Network", "Software" ], "Author": "Vince Carey , Li Long , R. Gentleman", "Maintainer": "Bioconductor Package Maintainer ", "URL": "http://www.bioconductor.org", "source.ver": "src/contrib/RBGL_1.50.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RBGL_1.50.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RBGL_1.50.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RBGL_1.50.0.tgz", "vignettes": [ "vignettes/RBGL/inst/doc/RBGL.pdf" ], "vignetteTitles": [ "RBGL Overview" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RBGL/inst/doc/RBGL.R" ], "dependsOnMe": [ "apComplex", "BioNet", "CellNOptR", "joda", "pkgDepTools", "RpsiXML" ], "importsMe": [ "alpine", "biocViews", "CAMERA", "Category", "ChIPpeakAnno", "CHRONOS", "clipper", "CytoML", "DEGraph", "DEsubs", "flowClust", "flowWorkspace", "GeneAnswers", "GOSim", "GOstats", "NCIgraph", "nem", "openCyto", "OrganismDbi", "pkgDepTools", "predictionet", "RDAVIDWebService", "Streamer", "ToPASeq", "VariantFiltering" ], "suggestsMe": [ "BiocCaseStudies", "DEGraph", "GeneNetworkBuilder", "graph", "gwascat", "KEGGgraph", "keggorthology", "rBiopaxParser", "VariantTools", "yeastExpData" ] }, "RBioinf": { "Package": "RBioinf", "Version": "1.34.0", "Depends": [ "graph", "methods" ], "Suggests": [ "Rgraphviz" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "cdc0c45a05a1c69fbf8905c92db2a930", "NeedsCompilation": "yes", "Title": "RBioinf", "Description": "Functions and datasets and examples to accompany the monograph R For Bioinformatics.", "biocViews": [ "Annotation", "Classification", "Clustering", "GeneExpression", "Microarray", "MultipleComparison", "Preprocessing", "QualityControl", "Software" ], "Author": "Robert Gentleman", "Maintainer": "Robert Gentleman ", "source.ver": "src/contrib/RBioinf_1.34.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RBioinf_1.34.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RBioinf_1.34.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RBioinf_1.34.0.tgz", "vignettes": [ "vignettes/RBioinf/inst/doc/RBioinf.pdf" ], "vignetteTitles": [ "RBioinf Introduction" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RBioinf/inst/doc/RBioinf.R" ] }, "rBiopaxParser": { "Package": "rBiopaxParser", "Version": "2.14.0", "Depends": [ "R (>= 3.0.0)", "data.table" ], "Imports": [ "XML" ], "Suggests": [ "Rgraphviz", "RCurl", "graph", "RUnit", "BiocGenerics", "nem", "RBGL", "igraph" ], "License": "GPL (>= 2)", "MD5sum": "2066a75f41184b1c051d306e3726f158", "NeedsCompilation": "no", "Title": "Parses BioPax files and represents them in R", "Description": "Parses BioPAX files and represents them in R, at the moment BioPAX level 2 and level 3 are supported.", "biocViews": [ "DataRepresentation", "Software" ], "Author": "Frank Kramer", "Maintainer": "Frank Kramer ", "URL": "https://github.com/frankkramer-lab/rBiopaxParser", "source.ver": "src/contrib/rBiopaxParser_2.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/rBiopaxParser_2.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/rBiopaxParser_2.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/rBiopaxParser_2.14.0.tgz", "vignettes": [ "vignettes/rBiopaxParser/inst/doc/rBiopaxParserVignette.pdf" ], "vignetteTitles": [ "rBiopaxParser Vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/rBiopaxParser/inst/doc/rBiopaxParserVignette.R" ], "importsMe": [ "AnnotationHubData", "pwOmics" ], "suggestsMe": [ "AnnotationHub", "NetPathMiner" ] }, "RBM": { "Package": "RBM", "Version": "1.6.0", "Depends": [ "R (>= 3.2.0)", "limma", "marray" ], "License": "GPL (>= 2)", "MD5sum": "8e3ec8c0de87aa041ff0471dc2099144", "NeedsCompilation": "no", "Title": "RBM: a R package for microarray and RNA-Seq data analysis", "Description": "Use A Resampling-Based Empirical Bayes Approach to Assess Differential Expression in Two-Color Microarrays and RNA-Seq data sets.", "biocViews": [ "DifferentialExpression", "Microarray", "Software" ], "Author": "Dongmei Li and Chin-Yuan Liang", "Maintainer": "Dongmei Li ", "source.ver": "src/contrib/RBM_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RBM_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RBM_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RBM_1.6.0.tgz", "vignettes": [ "vignettes/RBM/inst/doc/RBM.pdf" ], "vignetteTitles": [ "RBM" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RBM/inst/doc/RBM.R" ] }, "Rbowtie": { "Package": "Rbowtie", "Version": "1.14.0", "Suggests": [ "parallel" ], "License": "Artistic-1.0 | file LICENSE", "Archs": "x64", "MD5sum": "00aa734da52f38f40b00a785631e27ae", "NeedsCompilation": "yes", "Title": "R bowtie wrapper", "Description": "This package provides an R wrapper around the popular bowtie short read aligner and around SpliceMap, a de novo splice junction discovery and alignment tool. The package is used by the QuasR bioconductor package. We recommend to use the QuasR package instead of using Rbowtie directly.", "biocViews": [ "Alignment", "Sequencing", "Software" ], "Author": "Florian Hahne, Anita Lerch, Michael B Stadler", "Maintainer": "Michael Stadler ", "SystemRequirements": "GNU make", "source.ver": "src/contrib/Rbowtie_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Rbowtie_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Rbowtie_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Rbowtie_1.14.0.tgz", "vignettes": [ "vignettes/Rbowtie/inst/doc/Rbowtie-Overview.pdf" ], "vignetteTitles": [ "An introduction to Rbowtie" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/Rbowtie/inst/doc/Rbowtie-Overview.R" ], "dependsOnMe": [ "QuasR" ] }, "rbsurv": { "Package": "rbsurv", "Version": "2.32.0", "Depends": [ "R (>= 2.5.0)", "Biobase (>= 2.5.5)", "survival" ], "License": "GPL (>= 2)", "MD5sum": "ea341c5bbf705091ca14b750cd3e3d28", "NeedsCompilation": "no", "Title": "Robust likelihood-based survival modeling with microarray data", "Description": "This package selects genes associated with survival.", "biocViews": [ "Microarray", "Software" ], "Author": "HyungJun Cho , Sukwoo Kim , Soo-heang Eo , Jaewoo Kang ", "Maintainer": "Soo-heang Eo ", "URL": "http://www.korea.ac.kr/~stat2242/", "source.ver": "src/contrib/rbsurv_2.32.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/rbsurv_2.32.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/rbsurv_2.32.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/rbsurv_2.32.0.tgz", "vignettes": [ "vignettes/rbsurv/inst/doc/rbsurv.pdf" ], "vignetteTitles": [ "Overview" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/rbsurv/inst/doc/rbsurv.R" ] }, "Rcade": { "Package": "Rcade", "Version": "1.16.0", "Depends": [ "R (>= 2.14.0)", "methods", "GenomicRanges", "Rsamtools", "baySeq" ], "Imports": [ "utils", "grDevices", "stats", "graphics", "rgl", "plotrix", "S4Vectors", "IRanges", "GenomeInfoDb", "GenomicAlignments" ], "Suggests": [ "limma", "biomaRt", "RUnit", "BiocGenerics", "BiocStyle" ], "License": "GPL-2", "MD5sum": "d842e9941643c8931f97b872001368fc", "NeedsCompilation": "no", "Title": "R-based analysis of ChIP-seq And Differential Expression - a tool for integrating a count-based ChIP-seq analysis with differential expression summary data", "Description": "Rcade (which stands for \"R-based analysis of ChIP-seq And Differential Expression\") is a tool for integrating ChIP-seq data with differential expression summary data, through a Bayesian framework. A key application is in identifing the genes targeted by a transcription factor of interest - that is, we collect genes that are associated with a ChIP-seq peak, and differential expression under some perturbation related to that TF.", "biocViews": [ "ChIPSeq", "DifferentialExpression", "GeneExpression", "Genetics", "Sequencing", "Software", "Transcription" ], "Author": "Jonathan Cairns", "Maintainer": "Jonathan Cairns ", "source.ver": "src/contrib/Rcade_1.16.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Rcade_1.16.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Rcade_1.16.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Rcade_1.16.0.tgz", "vignettes": [ "vignettes/Rcade/inst/doc/Rcade.pdf" ], "vignetteTitles": [ "Rcade Vignette" ], "hasREADME": true, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Rcade/inst/doc/Rcade.R" ] }, "RCAS": { "Package": "RCAS", "Version": "1.0.2", "Depends": [ "R (>= 3.3.0)", "plotly (>= 4.5.2)", "DT (>= 0.2)", "data.table", "topGO", "motifRG" ], "Imports": [ "biomaRt", "AnnotationDbi", "GenomicRanges", "BSgenome.Hsapiens.UCSC.hg19", "GenomeInfoDb", "Biostrings", "rtracklayer", "org.Hs.eg.db", "GenomicFeatures", "genomation (>= 1.5.5)", "rmarkdown (>= 0.9.5)", "knitr (>= 1.12.3)", "BiocGenerics", "S4Vectors", "stats" ], "Suggests": [ "BSgenome.Mmusculus.UCSC.mm9", "BSgenome.Celegans.UCSC.ce10", "BSgenome.Dmelanogaster.UCSC.dm3", "org.Mm.eg.db", "org.Ce.eg.db", "org.Dm.eg.db", "testthat" ], "License": "Artistic-2.0", "MD5sum": "e3e76d4a4773f4548410b2566ac1dc7f", "NeedsCompilation": "no", "Title": "RNA Centric Annotation System", "Description": "RCAS is an automated system that provides dynamic genome annotations for custom input files that contain transcriptomic regions. Such transcriptomic regions could be, for instance, peak regions detected by CLIP-Seq analysis that detect protein-RNA interactions, RNA modifications (alias the epitranscriptome), CAGE-tag locations, or any other collection of target regions at the level of the transcriptome. RCAS is designed as a reporting tool for the functional analysis of RNA-binding sites detected by high-throughput experiments. It takes as input a BED format file containing the genomic coordinates of the RNA binding sites and a GTF file that contains the genomic annotation features usually provided by publicly available databases such as Ensembl and UCSC. RCAS performs overlap operations between the genomic coordinates of the RNA binding sites and the genomic annotation features and produces in-depth annotation summaries such as the distribution of binding sites with respect to gene features (exons, introns, 5'/3' UTR regions, exon-intron boundaries, promoter regions, and whole transcripts). Moreover, by detecting the collection of targeted transcripts, RCAS can carry out functional annotation tables for enriched gene sets (annotated by the Molecular Signatures Database) and GO terms. As one of the most important questions that arise during protein-RNA interaction analysis; RCAS has a module for detecting sequence motifs enriched in the targeted regions of the transcriptome. A full interactive report in HTML format can be generated that contains interactive figures and tables that are ready for publication purposes.", "biocViews": [ "Coverage", "GO", "GeneSetEnrichment", "GeneTarget", "GenomeAnnotation", "MotifAnnotation", "MotifDiscovery", "Software", "Transcriptomics" ], "Author": "Bora Uyar [aut, cre], Dilmurat Yusuf [aut], Ricardo Wurmus [aut], Altuna Akalin [aut]", "Maintainer": "Bora Uyar ", "SystemRequirements": "pandoc (>= 1.12.3)", "VignetteBuilder": "knitr", "source.ver": "src/contrib/RCAS_1.0.2.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RCAS_1.0.2.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RCAS_1.0.2.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RCAS_1.0.2.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RCAS/inst/doc/RCAS.vignette.R" ], "htmlDocs": [ "vignettes/RCAS/inst/doc/RCAS.vignette.html" ], "htmlTitles": [ "Vignette Title" ] }, "RCASPAR": { "Package": "RCASPAR", "Version": "1.20.0", "License": "GPL (>=3)", "MD5sum": "36f46ae2593b54e7030e6fe29b3a791b", "NeedsCompilation": "no", "Title": "A package for survival time prediction based on a piecewise baseline hazard Cox regression model.", "Description": "The package is the R-version of the C-based software \\bold{CASPAR} (Kaderali,2006: \\url{http://bioinformatics.oxfordjournals.org/content/22/12/1495}). It is meant to help predict survival times in the presence of high-dimensional explanatory covariates. The model is a piecewise baseline hazard Cox regression model with an Lq-norm based prior that selects for the most important regression coefficients, and in turn the most relevant covariates for survival analysis. It was primarily tried on gene expression and aCGH data, but can be used on any other type of high-dimensional data and in disciplines other than biology and medicine.", "biocViews": [ "GeneExpression", "Genetics", "Proteomics", "Software", "Visualization", "aCGH" ], "Author": "Douaa Mugahid, Lars Kaderali", "Maintainer": "Douaa Mugahid , Lars Kaderali ", "source.ver": "src/contrib/RCASPAR_1.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RCASPAR_1.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RCASPAR_1.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RCASPAR_1.20.0.tgz", "vignettes": [ "vignettes/RCASPAR/inst/doc/RCASPAR.pdf" ], "vignetteTitles": [ "RCASPAR: Software for high-dimentional-data driven survival time prediction" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RCASPAR/inst/doc/RCASPAR.R" ] }, "rcellminer": { "Package": "rcellminer", "Version": "1.6.0", "Depends": [ "R (>= 3.2)", "Biobase", "rcdk", "fingerprint", "rcellminerData" ], "Imports": [ "stringr", "gplots", "methods", "shiny" ], "Suggests": [ "knitr", "RColorBrewer", "sqldf", "BiocGenerics", "testthat", "BiocStyle", "jsonlite" ], "License": "LGPL-3", "MD5sum": "6a59277dd33259fab3ee97ec4e5c6029", "NeedsCompilation": "no", "Title": "rcellminer: Molecular Profiles and Drug Response for the NCI-60 Cell Lines", "Description": "The NCI-60 cancer cell line panel has been used over the course of several decades as an anti-cancer drug screen. This panel was developed as part of the Developmental Therapeutics Program (DTP, http://dtp.nci.nih.gov/) of the U.S. National Cancer Institute (NCI). Thousands of compounds have been tested on the NCI-60, which have been extensively characterized by many platforms for gene and protein expression, copy number, mutation, and others (Reinhold, et al., 2012). The purpose of the CellMiner project (http://discover.nci.nih.gov/cellminer) has been to integrate data from multiple platforms used to analyze the NCI-60 and to provide a powerful suite of tools for exploration of NCI-60 data.", "biocViews": [ "CellBasedAssays", "Cheminformatics", "CopyNumberVariation", "GeneExpression", "Pharmacogenetics", "Pharmacogenomics", "Software", "SystemsBiology", "Visualization", "aCGH", "miRNA" ], "Author": "Augustin Luna, Vinodh Rajapakse, Fabricio Sousa", "Maintainer": "Augustin Luna , Vinodh Rajapakse ", "URL": "http://discover.nci.nih.gov/cellminer/", "VignetteBuilder": "knitr", "source.ver": "src/contrib/rcellminer_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/rcellminer_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/rcellminer_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/rcellminer_1.6.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/rcellminer/inst/doc/rcellminerUsage.R" ], "htmlDocs": [ "vignettes/rcellminer/inst/doc/rcellminerUsage.html" ], "htmlTitles": [ "Using rcellminer" ], "suggestsMe": [ "rcellminerData" ] }, "rCGH": { "Package": "rCGH", "Version": "1.4.0", "Depends": [ "R (>= 3.2.1)", "methods", "stats", "utils", "graphics" ], "Imports": [ "plyr", "DNAcopy", "lattice", "ggplot2", "grid", "shiny (>= 0.11.1)", "limma", "affy", "mclust", "TxDb.Hsapiens.UCSC.hg18.knownGene", "TxDb.Hsapiens.UCSC.hg19.knownGene", "TxDb.Hsapiens.UCSC.hg38.knownGene", "org.Hs.eg.db", "GenomicFeatures", "GenomeInfoDb", "GenomicRanges", "AnnotationDbi", "parallel", "IRanges", "grDevices", "aCGH" ], "Suggests": [ "BiocStyle", "knitr", "BiocGenerics", "RUnit" ], "License": "Artistic-2.0", "MD5sum": "7204ba931b5948aca2d3cb8e8215a58d", "NeedsCompilation": "no", "Title": "Comprehensive Pipeline for Analyzing and Visualizing Array-Based CGH Data", "Description": "A comprehensive pipeline for analyzing and interactively visualizing genomic profiles generated through commercial or custom aCGH arrays. As inputs, rCGH supports Agilent dual-color Feature Extraction files (.txt), from 44 to 400K, Affymetrix SNP6.0 and cytoScanHD probeset.txt, cychp.txt, and cnchp.txt files exported from ChAS or Affymetrix Power Tools. rCGH also supports custom arrays, provided data complies with the expected format. This package takes over all the steps required for individual genomic profiles analysis, from reading files to profiles segmentation and gene annotations. This package also provides several visualization functions (static or interactive) which facilitate individual profiles interpretation. Input files can be in compressed format, e.g. .bz2 or .gz.", "biocViews": [ "CopyNumberVariation", "FeatureExtraction", "Preprocessing", "Software", "aCGH" ], "Author": "Frederic Commo [aut, cre]", "Maintainer": "Frederic Commo ", "URL": "https://github.com/fredcommo/rCGH", "VignetteBuilder": "knitr", "source.ver": "src/contrib/rCGH_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/rCGH_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/rCGH_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/rCGH_1.4.0.tgz", "vignettes": [ "vignettes/rCGH/inst/doc/rCGH.pdf" ], "vignetteTitles": [ "using rCGH package" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/rCGH/inst/doc/rCGH.R" ] }, "Rchemcpp": { "Package": "Rchemcpp", "Version": "2.12.0", "Depends": [ "R (>= 2.15.0)" ], "Imports": [ "Rcpp (>= 0.11.1)", "methods", "ChemmineR" ], "LinkingTo": [ "Rcpp" ], "Suggests": [ "apcluster", "kernlab" ], "License": "GPL (>= 2.1)", "Archs": "i386, x64", "MD5sum": "958437b738a492a9f6b9046bea04b8ae", "NeedsCompilation": "yes", "Title": "Similarity measures for chemical compounds", "Description": "The Rchemcpp package implements the marginalized graph kernel and extensions, Tanimoto kernels, graph kernels, pharmacophore and 3D kernels suggested for measuring the similarity of molecules.", "biocViews": [ "Bioinformatics", "CellBasedAssays", "Clustering", "DataImport", "Infrastructure", "MicrotitrePlateAssay", "Proteomics", "Software", "Visualization" ], "Author": "Michael Mahr, Guenter Klambauer", "Maintainer": "Guenter Klambauer ", "URL": "http://www.bioinf.jku.at/software/Rchemcpp", "SystemRequirements": "GNU make", "source.ver": "src/contrib/Rchemcpp_2.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Rchemcpp_2.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Rchemcpp_2.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Rchemcpp_2.12.0.tgz", "vignettes": [ "vignettes/Rchemcpp/inst/doc/Rchemcpp.pdf" ], "vignetteTitles": [ "Rchemcpp" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Rchemcpp/inst/doc/Rchemcpp.R" ] }, "RchyOptimyx": { "Package": "RchyOptimyx", "Version": "2.14.0", "Depends": [ "R (>= 2.10)" ], "Imports": [ "Rgraphviz", "sfsmisc", "graphics", "methods", "graph", "grDevices", "flowType (>= 2.0.0)" ], "Suggests": [ "flowCore" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "996cb1417bb385922cb504aba08ec0d9", "NeedsCompilation": "yes", "Title": "Optimyzed Cellular Hierarchies for Flow Cytometry", "Description": "Constructs a hierarchy of cells using flow cytometry for maximization of an external variable (e.g., a clinical outcome or a cytokine response).", "biocViews": [ "FlowCytometry", "Software" ], "Author": "Adrin Jalali, Nima Aghaeepour", "Maintainer": "Adrin Jalali , Nima Aghaeepour ", "source.ver": "src/contrib/RchyOptimyx_2.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RchyOptimyx_2.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RchyOptimyx_2.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RchyOptimyx_2.14.0.tgz", "vignettes": [ "vignettes/RchyOptimyx/inst/doc/RchyOptimyx.pdf" ], "vignetteTitles": [ "flowType package" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RchyOptimyx/inst/doc/RchyOptimyx.R" ] }, "Rcpi": { "Package": "Rcpi", "Version": "1.10.6", "Imports": [ "stats", "utils", "methods", "RCurl", "rjson", "foreach", "doParallel", "Biostrings", "GOSemSim", "ChemmineR", "fmcsR", "rcdk (>= 3.3.8)" ], "Suggests": [ "RUnit", "BiocGenerics" ], "Enhances": [ "ChemmineOB" ], "License": "Artistic-2.0", "MD5sum": "60f319ad35b6bdae905f8af6ca4b1786", "NeedsCompilation": "no", "Title": "Molecular Informatics Toolkit for Compound-Protein Interaction in Drug Discovery", "Description": "Rcpi offers a molecular informatics toolkit with a comprehensive integration of bioinformatics and chemoinformatics tools for drug discovery.", "biocViews": [ "BiomedicalInformatics", "Cheminformatics", "DataImport", "DataRepresentation", "FeatureExtraction", "GO", "Proteomics", "Software", "SystemsBiology" ], "Author": "Nan Xiao [aut, cre], Dongsheng Cao [aut], Qingsong Xu [aut]", "Maintainer": "Nan Xiao ", "URL": "http://nanx.me/Rcpi/, https://github.com/road2stat/Rcpi", "BugReports": "https://github.com/road2stat/Rcpi/issues", "source.ver": "src/contrib/Rcpi_1.10.6.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Rcpi_1.10.6.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Rcpi_1.10.6.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Rcpi_1.10.6.tgz", "vignettes": [ "vignettes/Rcpi/inst/doc/Rcpi-quickref.pdf", "vignettes/Rcpi/inst/doc/Rcpi.pdf" ], "vignetteTitles": [ "Rcpi Quick Reference Card", "Rcpi: R/Bioconductor Package as an Integrated Informatics Platform in Drug Discovery" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Rcpi/inst/doc/Rcpi-quickref.R", "vignettes/Rcpi/inst/doc/Rcpi.R" ] }, "RCy3": { "Package": "RCy3", "Version": "1.5.2", "Depends": [ "R (>= 3.2)", "graph (>= 1.48.0)" ], "Imports": [ "httr", "methods", "RCurl", "RJSONIO" ], "Suggests": [ "BiocGenerics", "RUnit", "knitr", "igraph", "RColorBrewer", "paxtoolsr", "rmarkdown" ], "License": "Artistic-2.0", "MD5sum": "be6aabbf550d576a67c56f6b7b38a50d", "NeedsCompilation": "no", "Title": "Display and manipulate graphs in Cytoscape >= 3.3.0", "Description": "Vizualize, analyze and explore graphs, connecting R to Cytoscape (>= 3.3.0).", "biocViews": [ "GraphAndNetwork", "Network", "Software", "ThirdPartyClient", "Visualization" ], "Author": "Tanja Muetze, Georgi Kolishovski, Paul Shannon", "Maintainer": "Tanja Muetze , Georgi Kolishovski , Paul Shannon ", "URL": "https://github.com/tmuetze/Bioconductor_RCy3_the_new_RCytoscape", "SystemRequirements": "Cytoscape (>= 3.3.0), CyREST (>= 3.3.7), Java (>=8)", "VignetteBuilder": "knitr", "BugReports": "https://github.com/tmuetze/Bioconductor_RCy3_the_new_RCytoscape/issues", "source.ver": "src/contrib/RCy3_1.5.2.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RCy3_1.5.2.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RCy3_1.5.2.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RCy3_1.5.2.tgz", "vignettes": [ "vignettes/RCy3/inst/doc/RCy3.pdf" ], "vignetteTitles": [ "RCy3 Overview" ], "hasREADME": true, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RCy3/inst/doc/RCy3.R" ] }, "RCyjs": { "Package": "RCyjs", "Version": "1.6.0", "Depends": [ "R (>= 3.2.0)", "BrowserViz (>= 1.1.7)", "graph (>= 1.44.0)" ], "Imports": [ "methods", "httpuv (>= 1.3.2)", "Rcpp (>= 0.11.5)", "jsonlite (>= 0.9.15)", "BiocGenerics", "igraph" ], "Suggests": [ "RUnit", "BiocStyle", "RefNet" ], "License": "GPL-2", "MD5sum": "6f99b96c0c4ab12726c163767b2bb8a6", "NeedsCompilation": "no", "Title": "Display and manipulate graphs in cytoscape.js", "Description": "Interactive viewing and exploration of graphs, connecting R to Cytoscape.js.", "biocViews": [ "GraphAndNetwork", "Software", "ThirdPartyClient", "Visualization" ], "Author": "Paul Shannon", "Maintainer": "Paul Shannon ", "URL": "http://rcytoscape.systemsbiology.net", "source.ver": "src/contrib/RCyjs_1.6.0.tar.gz", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RCyjs_1.6.0.tgz", "vignettes": [ "vignettes/RCyjs/inst/doc/RCyjs.pdf" ], "vignetteTitles": [ "RCyjs" ], "hasREADME": true, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RCyjs/inst/doc/RCyjs.R" ] }, "RCytoscape": { "Package": "RCytoscape", "Version": "1.24.1", "Depends": [ "R (>= 2.14.0)", "graph (>= 1.31.0)", "XMLRPC (>= 0.2.4)" ], "Imports": [ "methods", "XMLRPC", "BiocGenerics" ], "Suggests": [ "RUnit" ], "License": "GPL-2", "MD5sum": "c64e5f3441ecfc646d175d4eaeb2550e", "NeedsCompilation": "no", "Title": "Display and manipulate graphs in Cytoscape", "Description": "Interactvive viewing and exploration of graphs, connecting R to Cytoscape.", "biocViews": [ "GraphAndNetwork", "Software", "ThirdPartyClient", "Visualization" ], "Author": "Paul Shannon", "Maintainer": "Paul Shannon ", "URL": "http://rcytoscape.systemsbiology.net", "source.ver": "src/contrib/RCytoscape_1.24.1.tar.gz", "vignettes": [ "vignettes/RCytoscape/inst/doc/RCytoscape.pdf" ], "vignetteTitles": [ "RCytoscape Overview" ], "hasREADME": true, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RCytoscape/inst/doc/RCytoscape.R" ], "importsMe": [ "categoryCompare", "NCIgraph", "RamiGO" ], "suggestsMe": [ "GeneNetworkBuilder", "mmnet" ] }, "RDAVIDWebService": { "Package": "RDAVIDWebService", "Version": "1.12.0", "Depends": [ "R (>= 2.14.1)", "methods", "graph", "GOstats", "ggplot2" ], "Imports": [ "Category", "GO.db", "RBGL", "rJava" ], "Suggests": [ "Rgraphviz" ], "License": "GPL (>=2)", "MD5sum": "46bc74a1c1fbbcf8e7d637435562e71f", "NeedsCompilation": "no", "Title": "An R Package for retrieving data from DAVID into R objects using Web Services API.", "Description": "Tools for retrieving data from the Database for Annotation, Visualization and Integrated Discovery (DAVID) using Web Services into R objects. This package offers the main functionalities of DAVID website including: i) user friendly connectivity to upload gene/background list/s, change gene/background position, select current specie/s, select annotations, etc. ii) Reports of the submitted Gene List, Annotation Category Summary, Gene/Term Clusters, Functional Annotation Chart, Functional Annotation Table", "biocViews": [ "DifferentialExpression", "GraphAndNetwork", "Software", "Visualization" ], "Author": "Cristobal Fresno and Elmer A. Fernandez", "Maintainer": "Cristobal Fresno ", "URL": "http://www.bdmg.com.ar, http://david.abcc.ncifcrf.gov/", "source.ver": "src/contrib/RDAVIDWebService_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RDAVIDWebService_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RDAVIDWebService_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RDAVIDWebService_1.12.0.tgz", "vignettes": [ "vignettes/RDAVIDWebService/inst/doc/RDavidWS-vignette.pdf" ], "vignetteTitles": [ "RDAVIDWebService: a versatile R interface to DAVID" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RDAVIDWebService/inst/doc/RDavidWS-vignette.R" ], "dependsOnMe": [ "CompGO" ], "suggestsMe": [ "FGNet" ] }, "rDGIdb": { "Package": "rDGIdb", "Version": "1.0.0", "Imports": [ "jsonlite", "httr", "methods", "graphics" ], "Suggests": [ "BiocStyle", "knitr", "testthat" ], "License": "MIT + file LICENSE", "MD5sum": "00d6482aad00afcc5fb04f4eded295bd", "NeedsCompilation": "no", "Title": "R Wrapper for DGIdb", "Description": "The rDGIdb package provides a wrapper for the Drug Gene Interaction Database (DGIdb). For simplicity, the wrapper query function and output resembles the user interface and results format provided on the DGIdb website (http://dgidb.genome.wustl.edu/).", "biocViews": [ "Annotation", "FunctionalGenomics", "Pharmacogenetics", "Pharmacogenomics", "ResearchField", "Software", "WorkflowStep" ], "Author": "Thomas Thurnherr, Franziska Singer, Daniel J. Stekhoven, and Niko Beerenwinkel", "Maintainer": "Thomas Thurnherr ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/rDGIdb_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/rDGIdb_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/rDGIdb_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/rDGIdb_1.0.0.tgz", "vignettes": [ "vignettes/rDGIdb/inst/doc/vignette.pdf" ], "vignetteTitles": [ "Query DGIdb using R" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/rDGIdb/inst/doc/vignette.R" ] }, "Rdisop": { "Package": "Rdisop", "Version": "1.34.0", "Depends": [ "R (>= 2.0.0)", "RcppClassic" ], "LinkingTo": [ "RcppClassic", "Rcpp" ], "Suggests": [ "RUnit" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "24d11bb4555056c907be4709ee83c275", "NeedsCompilation": "yes", "Title": "Decomposition of Isotopic Patterns", "Description": "Identification of metabolites using high precision mass spectrometry. MS Peaks are used to derive a ranked list of sum formulae, alternatively for a given sum formula the theoretical isotope distribution can be calculated to search in MS peak lists.", "biocViews": [ "MassSpectrometry", "Metabolomics", "Software" ], "Author": "Anton Pervukhin , Steffen Neumann ", "Maintainer": "Steffen Neumann ", "URL": "https://github.com/sneumann/Rdisop", "SystemRequirements": "None", "BugReports": "https://github.com/sneumann/Rdisop/issues/new", "source.ver": "src/contrib/Rdisop_1.34.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Rdisop_1.34.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Rdisop_1.34.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Rdisop_1.34.0.tgz", "vignettes": [ "vignettes/Rdisop/inst/doc/Rdisop.pdf" ], "vignetteTitles": [ "Molecule Identification with Rdisop" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": true, "hasLICENSE": false, "suggestsMe": [ "MSnbase", "RforProteomics" ] }, "RDRToolbox": { "Package": "RDRToolbox", "Version": "1.24.0", "Depends": [ "R (>= 2.9.0)" ], "Imports": [ "graphics", "grDevices", "methods", "stats", "MASS", "rgl" ], "Suggests": [ "golubEsets" ], "License": "GPL (>= 2)", "MD5sum": "d2b56ecc31d75084b182c536b8ff7021", "NeedsCompilation": "no", "Title": "A package for nonlinear dimension reduction with Isomap and LLE.", "Description": "A package for nonlinear dimension reduction using the Isomap and LLE algorithm. It also includes a routine for computing the Davis-Bouldin-Index for cluster validation, a plotting tool and a data generator for microarray gene expression data and for the Swiss Roll dataset.", "biocViews": [ "Clustering", "DimensionReduction", "FeatureExtraction", "Microarray", "Software", "Visualization" ], "Author": "Christoph Bartenhagen", "Maintainer": "Christoph Bartenhagen ", "source.ver": "src/contrib/RDRToolbox_1.24.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RDRToolbox_1.24.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RDRToolbox_1.24.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RDRToolbox_1.24.0.tgz", "vignettes": [ "vignettes/RDRToolbox/inst/doc/vignette.pdf" ], "vignetteTitles": [ "A package for nonlinear dimension reduction with Isomap and LLE." ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RDRToolbox/inst/doc/vignette.R" ] }, "ReactomePA": { "Package": "ReactomePA", "Version": "1.18.1", "Depends": [ "R (>= 3.3.0)", "DOSE (>= 2.11.12)" ], "Imports": [ "AnnotationDbi", "reactome.db", "igraph", "graphite" ], "Suggests": [ "BiocStyle", "clusterProfiler", "knitr", "org.Hs.eg.db", "testthat" ], "License": "GPL-2", "MD5sum": "763197e1b81292a893d301d454c4dd4a", "NeedsCompilation": "no", "Title": "Reactome Pathway Analysis", "Description": "This package provides functions for pathway analysis based on REACTOME pathway database. It implements enrichment analysis, gene set enrichment analysis and several functions for visualization.", "biocViews": [ "Annotation", "GeneSetEnrichment", "MultipleComparison", "Pathways", "Reactome", "Software", "Visualization" ], "Author": "Guangchuang Yu with contributions from Vladislav Petyuk", "Maintainer": "Guangchuang Yu ", "URL": "https://guangchuangyu.github.io/ReactomePA", "VignetteBuilder": "knitr", "BugReports": "https://github.com/GuangchuangYu/ReactomePA/issues", "source.ver": "src/contrib/ReactomePA_1.18.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ReactomePA_1.18.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ReactomePA_1.18.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ReactomePA_1.18.1.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ReactomePA/inst/doc/ReactomePA.R" ], "htmlDocs": [ "vignettes/ReactomePA/inst/doc/ReactomePA.html" ], "htmlTitles": [ "An R package for Reactome Pathway Analysis" ], "importsMe": [ "bioCancer", "LINC" ], "suggestsMe": [ "ChIPseeker", "CINdex", "clusterProfiler" ] }, "readat": { "Package": "readat", "Version": "1.0.0", "Depends": [ "R (>= 3.3.1)" ], "Imports": [ "assertive.base (>= 0.0-6)", "assertive.files (>= 0.0-2)", "assertive.numbers (>= 0.0-2)", "assertive.properties (>= 0.0-3)", "assertive.sets (>= 0.0-2)", "assertive.types (>= 0.0-2)", "Biobase (>= 2.32.0)", "data.table (>= 1.9.6)", "dplyr (>= 0.5.0)", "magrittr (>= 1.5)", "openxlsx (>= 3.0.0)", "pathological (>= 0.1-1)", "reshape2 (>= 1.4.1)", "stats", "stringi (>= 1.1.1)", "SummarizedExperiment (>= 1.2.3)", "testthat (>= 1.0.2)", "tidyr (>= 0.6.0)", "utils" ], "Suggests": [ "knitr", "MSnbase", "rmarkdown", "withr" ], "License": "GPL-3", "MD5sum": "8bbea6f118afed62ed487c21ed6a902c", "NeedsCompilation": "no", "Title": "Functionality to Read and Manipulate SomaLogic ADAT files", "Description": "This package contains functionality to import, transform and annotate data from ADAT files generated by the SomaLogic SOMAscan platform.", "biocViews": [ "DataImport", "GeneExpression", "OneChannel", "ProprietaryPlatforms", "Proteomics", "Software" ], "Author": "Richard Cotton [cre, aut], Aditya Bhagwat [aut]", "Maintainer": "Richard Cotton ", "URL": "https://bitbucket.org/graumannlabtools/readat", "VignetteBuilder": "knitr", "BugReports": "https://bitbucket.org/graumannlabtools/readat/issues", "source.ver": "src/contrib/readat_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/readat_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/readat_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/readat_1.0.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/readat/inst/doc/introduction.R" ], "htmlDocs": [ "vignettes/readat/inst/doc/introduction.html" ], "htmlTitles": [ "Introduction" ] }, "ReadqPCR": { "Package": "ReadqPCR", "Version": "1.20.0", "Depends": [ "R(>= 2.14.0)", "Biobase", "methods", "affy" ], "Imports": [ "Biobase" ], "Suggests": [ "qpcR" ], "License": "LGPL-3", "MD5sum": "a298d6c50e2ee56397e561d7dee9e5b8", "NeedsCompilation": "no", "Title": "Read qPCR data", "Description": "The package provides functions to read raw RT-qPCR data of different platforms.", "biocViews": [ "DataImport", "GeneExpression", "MicrotitrePlateAssay", "Software", "qPCR" ], "Author": "James Perkins, Matthias Kohl, Nor Izayu Abdul Rahman", "Maintainer": "James Perkins ", "URL": "http://www.bioconductor.org/packages/release/bioc/html/ReadqPCR.html", "source.ver": "src/contrib/ReadqPCR_1.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ReadqPCR_1.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ReadqPCR_1.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ReadqPCR_1.20.0.tgz", "vignettes": [ "vignettes/ReadqPCR/inst/doc/ReadqPCR.pdf" ], "vignetteTitles": [ "Functions to load RT-qPCR data into R" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ReadqPCR/inst/doc/ReadqPCR.R" ], "dependsOnMe": [ "NormqPCR" ] }, "reb": { "Package": "reb", "Version": "1.52.0", "Depends": [ "R (>= 2.0)", "Biobase", "idiogram (>= 1.5.3)" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "f9ac71aafd5c4e6188ff7a51f0b6bb17", "NeedsCompilation": "yes", "Title": "Regional Expression Biases", "Description": "A set of functions to dentify regional expression biases", "biocViews": [ "CopyNumberVariation", "Microarray", "Software", "Visualization" ], "Author": "Kyle A. Furge and Karl Dykema ", "Maintainer": "Karl J. Dykema ", "source.ver": "src/contrib/reb_1.52.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/reb_1.52.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/reb_1.52.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/reb_1.52.0.tgz", "vignettes": [ "vignettes/reb/inst/doc/reb.pdf" ], "vignetteTitles": [ "Smoothing of Microarray Data" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/reb/inst/doc/reb.R" ] }, "recount": { "Package": "recount", "Version": "1.0.17", "Depends": [ "R (>= 3.3.0)", "SummarizedExperiment" ], "Imports": [ "BiocParallel", "derfinder", "downloader", "GEOquery", "GenomeInfoDb", "GenomicRanges", "IRanges", "methods", "RCurl", "rentrez", "rtracklayer (>= 1.34.2)", "S4Vectors", "stats", "utils" ], "Suggests": [ "AnnotationDbi", "BiocStyle", "DESeq2", "devtools (>= 1.6)", "EnsDb.Hsapiens.v79", "GenomicFeatures", "knitcitations", "knitr (>= 1.6)", "org.Hs.eg.db", "regionReport", "rmarkdown (>= 0.9.5)", "testthat" ], "License": "Artistic-2.0", "MD5sum": "d49fcc3fb7b0b4059b5dc18ddd2ea65e", "NeedsCompilation": "no", "Title": "Explore and download data from the recount project", "Description": "Explore and download data from the recount project available at https://jhubiostatistics.shinyapps.io/recount/. Using the recount package you can download RangedSummarizedExperiment objects at the gene, exon or exon-exon junctions level, the raw counts, the phenotype metadata used, the urls to the sample coverage bigWig files or the mean coverage bigWig file for a particular study. The RangedSummarizedExperiment objects can be used by different packages for performing differential expression analysis. Using http://bioconductor.org/packages/derfinder you can perform annotation-agnostic differential expression analyses with the data from the recount project as described at http://biorxiv.org/content/early/2016/08/08/068478.", "biocViews": [ "Coverage", "DataImport", "DifferentialExpression", "GeneExpression", "RNASeq", "Sequencing", "Software" ], "Author": "Leonardo Collado-Torres [aut, cre], Abhinav Nellore [ctb], Andrew E. Jaffe [ctb], Margaret A. Taub [ctb], Kai Kammers [ctb], Shannon E. Ellis [ctb], Kasper Daniel Hansen [ctb], Ben Langmead [ctb], Jeffrey T. Leek [aut, ths]", "Maintainer": "Leonardo Collado-Torres ", "URL": "https://github.com/leekgroup/recount", "VignetteBuilder": "knitr", "BugReports": "https://support.bioconductor.org/t/recount/", "source.ver": "src/contrib/recount_1.0.17.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/recount_1.0.17.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/recount_1.0.17.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/recount_1.0.17.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/recount/inst/doc/recount-quickstart.R", "vignettes/recount/inst/doc/SRP009615-results.R" ], "htmlDocs": [ "vignettes/recount/inst/doc/recount-quickstart.html", "vignettes/recount/inst/doc/SRP009615-results.html" ], "htmlTitles": [ "recount quick start guide", "Basic DESeq2 results exploration" ] }, "recoup": { "Package": "recoup", "Version": "1.2.0", "Depends": [ "GenomicRanges", "GenomicAlignments", "ggplot2", "ComplexHeatmap" ], "Imports": [ "BiocGenerics", "biomaRt", "circlize", "rtracklayer", "plyr" ], "Suggests": [ "grid", "GenomeInfoDb", "Rsamtools", "BiocStyle", "knitr", "rmarkdown", "zoo", "RUnit", "BiocInstaller", "BSgenome", "RSQLite", "RMySQL" ], "Enhances": [ "parallel" ], "License": "GPL (>= 3)", "MD5sum": "f13eeac3e3b2cf1eec9f345ce3fbad1d", "NeedsCompilation": "no", "Title": "An R package for the creation of complex genomic profile plots", "Description": "recoup calculates and plots signal profiles created from short sequence reads derived from Next Generation Sequencing technologies. The profiles provided are either sumarized curve profiles or heatmap profiles. Currently, recoup supports genomic profile plots for reads derived from ChIP-Seq and RNA-Seq experiments. The package uses ggplot2 and ComplexHeatmap graphics facilities for curve and heatmap coverage profiles respectively.", "biocViews": [ "ChIPSeq", "Coverage", "GeneExpression", "Preprocessing", "QualityControl", "RNASeq", "Sequencing", "Software" ], "Author": "Panagiotis Moulos ", "Maintainer": "Panagiotis Moulos ", "URL": "https://github.com/pmoulos/recoup", "VignetteBuilder": "knitr", "source.ver": "src/contrib/recoup_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/recoup_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/recoup_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/recoup_1.2.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/recoup/inst/doc/recoup_intro.R" ], "htmlDocs": [ "vignettes/recoup/inst/doc/recoup_intro.html" ], "htmlTitles": [ "Introduction to the recoup package" ] }, "RedeR": { "Package": "RedeR", "Version": "1.22.0", "Depends": [ "R (>= 2.15)", "methods", "igraph" ], "Imports": [ "RCurl", "XML", "pvclust" ], "Suggests": [ "PANR" ], "License": "GPL (>= 2)", "MD5sum": "b5ddad64ae237134b4ec88baa8d0047c", "NeedsCompilation": "no", "Title": "Interactive visualization and manipulation of nested networks", "Description": "RedeR is an R-based package combined with a stand-alone Java application for interactive visualization and manipulation of modular structures, nested networks and multiple levels of hierarchical associations.", "biocViews": [ "DataRepresentation", "GraphAndNetwork", "Infrastructure", "Network", "Software", "Visualization" ], "Author": "Mauro Castro, Xin Wang, Florian Markowetz", "Maintainer": "Mauro Castro ", "URL": "http://genomebiology.com/2012/13/4/R29", "SystemRequirements": "Java Runtime Environment (>= 6)", "source.ver": "src/contrib/RedeR_1.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RedeR_1.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RedeR_1.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RedeR_1.22.0.tgz", "vignettes": [ "vignettes/RedeR/inst/doc/RedeR.pdf" ], "vignetteTitles": [ "Main vignette: interactive visualization and manipulation of nested networks" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RedeR/inst/doc/RedeR.R" ], "dependsOnMe": [ "Fletcher2013b", "SRGnet" ], "importsMe": [ "Mulder2012", "PANR", "RTN" ] }, "REDseq": { "Package": "REDseq", "Version": "1.20.0", "Depends": [ "R (>= 2.15.0)", "BiocGenerics (>= 0.1.0)", "BSgenome.Celegans.UCSC.ce2", "multtest", "Biostrings", "BSgenome", "ChIPpeakAnno" ], "Imports": [ "BiocGenerics", "AnnotationDbi", "Biostrings", "ChIPpeakAnno", "graphics", "IRanges (>= 1.13.5)", "multtest", "stats", "utils" ], "License": "GPL (>=2)", "MD5sum": "508ca179c45db20d55afb12218c90f55", "NeedsCompilation": "no", "Title": "Analysis of high-throughput sequencing data processed by restriction enzyme digestion", "Description": "The package includes functions to build restriction enzyme cut site (RECS) map, distribute mapped sequences on the map with five different approaches, find enriched/depleted RECSs for a sample, and identify differentially enriched/depleted RECSs between samples.", "biocViews": [ "Preprocessing", "SequenceMatching", "Sequencing", "Software" ], "Author": "Lihua Julie Zhu and Thomas Fazzio", "Maintainer": "Lihua Julie Zhu ", "source.ver": "src/contrib/REDseq_1.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/REDseq_1.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/REDseq_1.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/REDseq_1.20.0.tgz", "vignettes": [ "vignettes/REDseq/inst/doc/REDseq.pdf" ], "vignetteTitles": [ "REDseq Vignette" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/REDseq/inst/doc/REDseq.R" ] }, "RefNet": { "Package": "RefNet", "Version": "1.10.1", "Depends": [ "R (>= 2.15.0)", "methods", "IRanges", "PSICQUIC", "AnnotationHub", "RCurl", "shiny" ], "Imports": [ "BiocGenerics" ], "Suggests": [ "RUnit", "BiocStyle", "org.Hs.eg.db" ], "License": "Artistic-2.0", "MD5sum": "0bdee431d4bb8ea9cfdd83b7ab8da867", "NeedsCompilation": "no", "Title": "A queryable collection of molecular interactions, from many sources", "Description": "Molecular interactions with metadata, some archived, some dynamically obtained", "biocViews": [ "GraphAndNetwork", "Software" ], "Author": "Paul Shannon", "Maintainer": "Paul Shannon ", "source.ver": "src/contrib/RefNet_1.10.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RefNet_1.10.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RefNet_1.10.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RefNet_1.10.1.tgz", "vignettes": [ "vignettes/RefNet/inst/doc/RefNet.pdf" ], "vignetteTitles": [ "RefNet" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RefNet/inst/doc/RefNet.R" ], "suggestsMe": [ "RCyjs" ] }, "RefPlus": { "Package": "RefPlus", "Version": "1.44.0", "Depends": [ "R (>= 2.8.0)", "Biobase (>= 2.1.0)", "affy (>= 1.20.0)", "affyPLM (>= 1.18.0)", "preprocessCore (>= 1.4.0)" ], "Suggests": [ "affydata" ], "License": "GPL (>= 2)", "MD5sum": "7c71bc55e413af2dc37da4d5badbed54", "NeedsCompilation": "no", "Title": "A function set for the Extrapolation Strategy (RMA+) and Extrapolation Averaging (RMA++) methods.", "Description": "The package contains functions for pre-processing Affymetrix data using the RMA+ and the RMA++ methods.", "biocViews": [ "Microarray", "OneChannel", "Preprocessing", "Software" ], "Author": "Kai-Ming Chang , Chris Harbron , Marie C South ", "Maintainer": "Kai-Ming Chang ", "source.ver": "src/contrib/RefPlus_1.44.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RefPlus_1.44.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RefPlus_1.44.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RefPlus_1.44.0.tgz", "vignettes": [ "vignettes/RefPlus/inst/doc/RefPlus.pdf" ], "vignetteTitles": [ "RefPlus Manual" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RefPlus/inst/doc/RefPlus.R" ] }, "regioneR": { "Package": "regioneR", "Version": "1.6.2", "Depends": [ "memoise", "GenomicRanges", "BSgenome", "rtracklayer", "parallel" ], "Imports": [ "memoise", "GenomicRanges", "BSgenome", "rtracklayer", "parallel", "graphics", "stats", "utils", "GenomeInfoDb", "IRanges" ], "Suggests": [ "BiocStyle", "knitr", "BSgenome.Hsapiens.UCSC.hg19.masked", "testthat" ], "License": "Artistic-2.0", "MD5sum": "93ecdf4d04f690580c0f1681bddc1246", "NeedsCompilation": "no", "Title": "Association analysis of genomic regions based on permutation tests", "Description": "regioneR offers a statistical framework based on customizable permutation tests to assess the association between genomic region sets and other genomic features.", "biocViews": [ "ChIPSeq", "CopyNumberVariation", "DNASeq", "Genetics", "MethylSeq", "Software" ], "Author": "Anna Diez-Villanueva , Roberto Malinverni and Bernat Gel ", "Maintainer": "Bernat Gel ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/regioneR_1.6.2.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/regioneR_1.6.2.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/regioneR_1.6.2.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/regioneR_1.6.2.tgz", "vignettes": [ "vignettes/regioneR/inst/doc/regioneR.pdf" ], "vignetteTitles": [ "regioneR vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/regioneR/inst/doc/regioneR.R" ], "importsMe": [ "annotatr", "ChIPpeakAnno" ] }, "regionReport": { "Package": "regionReport", "Version": "1.8.2", "Depends": [ "R(>= 3.2)" ], "Imports": [ "derfinder (>= 1.1.0)", "DEFormats", "DESeq2", "GenomeInfoDb", "GenomicRanges", "knitcitations (>= 1.0.1)", "knitr (>= 1.6)", "knitrBootstrap (>= 0.9.0)", "methods", "RefManageR", "rmarkdown (>= 0.9.5)", "S4Vectors", "SummarizedExperiment" ], "Suggests": [ "BiocStyle", "biovizBase", "bumphunter (>= 1.7.6)", "Cairo", "derfinderPlot (>= 1.3.2)", "devtools (>= 1.6)", "DT", "DESeq", "edgeR", "ggbio (>= 1.13.13)", "ggplot2", "grid", "gridExtra", "IRanges", "mgcv", "pasilla", "pheatmap", "RColorBrewer", "TxDb.Hsapiens.UCSC.hg19.knownGene", "whisker" ], "License": "Artistic-2.0", "MD5sum": "cdf7a0fdbe7c76133c91cdbfc5bde865", "NeedsCompilation": "no", "Title": "Generate HTML or PDF reports for a set of genomic regions or DESeq2/edgeR results", "Description": "Generate HTML or PDF reports to explore a set of regions such as the results from annotation-agnostic expression analysis of RNA-seq data at base-pair resolution performed by derfinder. You can also create reports for DESeq2 or edgeR results.", "biocViews": [ "Coverage", "DifferentialExpression", "DifferentialMethylation", "DifferentialPeakCalling", "RNASeq", "ReportWriting", "Sequencing", "Software", "Transcription", "Visualization" ], "Author": "Leonardo Collado-Torres [aut, cre], Andrew E. Jaffe [aut], Jeffrey T. Leek [aut, ths]", "Maintainer": "Leonardo Collado-Torres ", "URL": "https://github.com/leekgroup/regionReport", "VignetteBuilder": "knitr", "BugReports": "https://support.bioconductor.org/t/regionReport/", "source.ver": "src/contrib/regionReport_1.8.2.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/regionReport_1.8.2.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/regionReport_1.8.2.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/regionReport_1.8.2.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/regionReport/inst/doc/bumphunterExample.R", "vignettes/regionReport/inst/doc/bumphunterExampleOutput.R", "vignettes/regionReport/inst/doc/regionReport.R" ], "htmlDocs": [ "vignettes/regionReport/inst/doc/bumphunterExample.html", "vignettes/regionReport/inst/doc/bumphunterExampleOutput.html", "vignettes/regionReport/inst/doc/regionReport.html" ], "htmlTitles": [ "Example report using bumphunter results", "Basic genomic regions exploration", "Introduction to regionReport" ], "suggestsMe": [ "recount" ] }, "regsplice": { "Package": "regsplice", "Version": "1.0.0", "Imports": [ "glmnet", "SummarizedExperiment", "S4Vectors", "BiocParallel", "limma", "edgeR", "stats", "utils", "methods" ], "Suggests": [ "testthat", "BiocStyle", "knitr", "rmarkdown" ], "License": "MIT + file LICENSE", "MD5sum": "a791f63171e2bd5c3c70774aded62f2b", "NeedsCompilation": "no", "Title": "Lasso-Based Methods for Detection of Differential Exon Usage", "Description": "Statistical methods for detection of differential exon usage in RNA-seq and exon microarray data sets, using L1 regularization (lasso) to improve power.", "biocViews": [ "AlternativeSplicing", "DifferentialExpression", "DifferentialSplicing", "ExonArray", "ExperimentalDesign", "Microarray", "RNASeq", "Sequencing", "Software" ], "Author": "Lukas M. Weber [aut, cre]", "Maintainer": "Lukas M. Weber ", "URL": "https://github.com/lmweber/regsplice", "VignetteBuilder": "knitr", "BugReports": "https://github.com/lmweber/regsplice/issues", "source.ver": "src/contrib/regsplice_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/regsplice_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/regsplice_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/regsplice_1.0.0.tgz", "vignettes": [ "vignettes/regsplice/inst/doc/regsplice-workflow.pdf" ], "vignetteTitles": [ "Example workflow for regsplice package" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/regsplice/inst/doc/regsplice-workflow.R" ] }, "Repitools": { "Package": "Repitools", "Version": "1.20.0", "Depends": [ "R (>= 3.0.0)", "methods", "BiocGenerics (>= 0.8.0)" ], "Imports": [ "parallel", "S4Vectors (>= 0.9.25)", "IRanges (>= 1.20.0)", "GenomeInfoDb", "GenomicRanges", "Biostrings", "Rsamtools", "GenomicAlignments", "rtracklayer", "BSgenome", "gplots", "grid", "MASS", "gsmoothr", "edgeR (>= 3.4.0)", "DNAcopy", "Ringo", "aroma.affymetrix", "Rsolnp", "cluster" ], "Suggests": [ "ShortRead", "BSgenome.Hsapiens.UCSC.hg18" ], "License": "LGPL (>= 2)", "Archs": "i386, x64", "MD5sum": "3f27f4e075425ed0b3a9bb47bcaf8aaf", "NeedsCompilation": "yes", "Title": "Epigenomic tools", "Description": "Tools for the analysis of enrichment-based epigenomic data. Features include summarization and visualization of epigenomic data across promoters according to gene expression context, finding regions of differential methylation/binding, BayMeth for quantifying methylation etc.", "biocViews": [ "DNAMethylation", "GeneExpression", "MethylSeq", "Software" ], "Author": "Mark Robinson , Dario Strbenac , Aaron Statham , Andrea Riebler ", "Maintainer": "Mark Robinson ", "source.ver": "src/contrib/Repitools_1.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Repitools_1.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Repitools_1.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Repitools_1.20.0.tgz", "vignettes": [ "vignettes/Repitools/inst/doc/Repitools_vignette.pdf" ], "vignetteTitles": [ "Using Repitools for Epigenomic Sequencing Data" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Repitools/inst/doc/Repitools_vignette.R" ] }, "ReportingTools": { "Package": "ReportingTools", "Version": "2.14.0", "Depends": [ "methods", "knitr", "utils" ], "Imports": [ "Biobase", "hwriter", "Category", "GOstats", "limma(>= 3.17.5)", "lattice", "AnnotationDbi", "edgeR", "annotate", "PFAM.db", "GSEABase", "BiocGenerics(>= 0.1.6)", "grid", "XML", "R.utils", "DESeq2(>= 1.3.41)", "ggplot2", "ggbio", "IRanges" ], "Suggests": [ "RUnit", "ALL", "hgu95av2.db", "org.Mm.eg.db", "shiny", "pasilla" ], "License": "Artistic-2.0", "MD5sum": "d40177df43301a9808e7027eda095e9c", "NeedsCompilation": "no", "Title": "Tools for making reports in various formats", "Description": "The ReportingTools software package enables users to easily display reports of analysis results generated from sources such as microarray and sequencing data. The package allows users to create HTML pages that may be viewed on a web browser such as Safari, or in other formats readable by programs such as Excel. Users can generate tables with sortable and filterable columns, make and display plots, and link table entries to other data sources such as NCBI or larger plots within the HTML page. Using the package, users can also produce a table of contents page to link various reports together for a particular project that can be viewed in a web browser. For more examples, please visit our site: http:// research-pub.gene.com/ReportingTools.", "biocViews": [ "DataRepresentation", "GO", "GeneSetEnrichment", "Microarray", "RNASeq", "Software", "Visualization" ], "Author": "Jason A. Hackney, Melanie Huntley, Jessica L. Larson, Christina Chaivorapol, Gabriel Becker, and Josh Kaminker", "Maintainer": "Jason A. Hackney , Gabriel Becker , Jessica L. Larson ", "VignetteBuilder": "utils, knitr", "source.ver": "src/contrib/ReportingTools_2.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ReportingTools_2.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ReportingTools_2.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ReportingTools_2.14.0.tgz", "vignettes": [ "vignettes/ReportingTools/inst/doc/basicReportingTools.pdf", "vignettes/ReportingTools/inst/doc/microarrayAnalysis.pdf", "vignettes/ReportingTools/inst/doc/rnaseqAnalysis.pdf", "vignettes/ReportingTools/inst/doc/shiny.pdf" ], "vignetteTitles": [ "ReportingTools basics", "Reporting on microarray differential expression", "Reporting on RNA-seq differential expression", "ReportingTools shiny" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ReportingTools/inst/doc/basicReportingTools.R", "vignettes/ReportingTools/inst/doc/knitr.R", "vignettes/ReportingTools/inst/doc/microarrayAnalysis.R", "vignettes/ReportingTools/inst/doc/rnaseqAnalysis.R", "vignettes/ReportingTools/inst/doc/shiny.R" ], "htmlDocs": [ "vignettes/ReportingTools/inst/doc/knitr.html" ], "htmlTitles": [ "Knitr and ReportingTools" ], "importsMe": [ "affycoretools", "EnrichmentBrowser" ], "suggestsMe": [ "cpvSNP", "GSEABase", "npGSEA" ] }, "ReQON": { "Package": "ReQON", "Version": "1.20.0", "Depends": [ "R (>= 3.0.2)", "Rsamtools", "seqbias" ], "Imports": [ "rJava", "graphics", "stats", "utils", "grDevices" ], "Suggests": [ "BiocStyle" ], "License": "GPL-2", "MD5sum": "c81fb414fa67f48cb9db3208b79b30f5", "NeedsCompilation": "no", "Title": "Recalibrating Quality Of Nucleotides", "Description": "Algorithm for recalibrating the base quality scores for aligned sequencing data in BAM format.", "biocViews": [ "HighThroughputSequencing", "Preprocessing", "QualityControl", "Sequencing", "Software" ], "Author": "Christopher Cabanski, Keary Cavin, Chris Bizon", "Maintainer": "Christopher Cabanski ", "SystemRequirements": "Java version >= 1.6", "source.ver": "src/contrib/ReQON_1.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ReQON_1.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ReQON_1.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ReQON_1.20.0.tgz", "vignettes": [ "vignettes/ReQON/inst/doc/ReQON.pdf" ], "vignetteTitles": [ "ReQON Tutorial" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ReQON/inst/doc/ReQON.R" ] }, "rfPred": { "Package": "rfPred", "Version": "1.12.0", "Depends": [ "Rsamtools", "GenomicRanges", "IRanges", "data.table", "methods", "parallel" ], "Suggests": [ "BiocStyle" ], "License": "GPL (>=2 )", "Archs": "i386, x64", "MD5sum": "8145be3ffc6276a0b31a4ed3ccb60e35", "NeedsCompilation": "yes", "Title": "Assign rfPred functional prediction scores to a missense variants list", "Description": "Based on external numerous data files where rfPred scores are pre-calculated on all genomic positions of the human exome, the package gives rfPred scores to missense variants identified by the chromosome, the position (hg19 version), the referent and alternative nucleotids and the uniprot identifier of the protein. Note that for using the package, the user has to be connected on the Internet or to download the TabixFile and index (approximately 3.3 Go).", "biocViews": [ "Annotation", "Classification", "Software" ], "Author": "Fabienne Jabot-Hanin, Hugo Varet and Jean-Philippe Jais", "Maintainer": "Hugo Varet ", "URL": "http://www.sbim.fr/rfPred", "source.ver": "src/contrib/rfPred_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/rfPred_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/rfPred_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/rfPred_1.12.0.tgz", "vignettes": [ "vignettes/rfPred/inst/doc/vignette.pdf" ], "vignetteTitles": [ "CalculatingrfPredscoreswithpackagerfPred" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/rfPred/inst/doc/vignette.R" ] }, "rGADEM": { "Package": "rGADEM", "Version": "2.22.0", "Depends": [ "R (>= 2.11.0)", "Biostrings", "IRanges", "BSgenome", "methods", "seqLogo" ], "Imports": [ "Biostrings", "IRanges", "methods", "graphics", "seqLogo" ], "Suggests": [ "BSgenome.Hsapiens.UCSC.hg19" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "68855b9cecf4cb029027b6df0a0b6b2d", "NeedsCompilation": "yes", "Title": "de novo motif discovery", "Description": "rGADEM is an efficient de novo motif discovery tool for large-scale genomic sequence data. It is an open-source R package, which is based on the GADEM software.", "biocViews": [ "ChIPSeq", "ChIPchip", "Microarray", "MotifDiscovery", "Sequencing", "Software" ], "Author": "Arnaud Droit, Raphael Gottardo, Gordon Robertson and Leiping Li", "Maintainer": "Arnaud Droit ", "source.ver": "src/contrib/rGADEM_2.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/rGADEM_2.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/rGADEM_2.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/rGADEM_2.22.0.tgz", "vignettes": [ "vignettes/rGADEM/inst/doc/rGADEM.pdf" ], "vignetteTitles": [ "The rGADEM users guide" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/rGADEM/inst/doc/rGADEM.R" ], "importsMe": [ "MotIV" ] }, "RGalaxy": { "Package": "RGalaxy", "Version": "1.18.0", "Depends": [ "XML", "methods", "tools", "optparse", "digest" ], "Imports": [ "BiocGenerics", "Biobase", "roxygen2" ], "Suggests": [ "RUnit", "hgu95av2.db", "knitr", "formatR", "Rserve" ], "Enhances": [ "RSclient" ], "License": "Artistic-2.0", "MD5sum": "924e98c9cd983008ebe01df4c5fb6e2f", "NeedsCompilation": "no", "Title": "Make an R function available in the Galaxy web platform", "Description": "Given an R function and its manual page, make the documented function available in Galaxy.", "biocViews": [ "Infrastructure", "Software" ], "Author": "Dan Tenenbaum", "Maintainer": "Bioconductor Package Maintainer ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/RGalaxy_1.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RGalaxy_1.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RGalaxy_1.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RGalaxy_1.18.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RGalaxy/inst/doc/RGalaxy-vignette.R" ], "htmlDocs": [ "vignettes/RGalaxy/inst/doc/RGalaxy-vignette.html" ], "htmlTitles": [ "Introduction to RGalaxy" ] }, "RGraph2js": { "Package": "RGraph2js", "Version": "1.2.0", "Imports": [ "utils", "whisker", "rjson", "digest", "graph" ], "Suggests": [ "RUnit", "BiocStyle", "BiocGenerics", "xtable", "sna" ], "License": "GPL-2", "MD5sum": "049c4cadda87991cce3113703164e6ae", "NeedsCompilation": "no", "Title": "Convert a Graph into a D3js Script", "Description": "Generator of web pages which display interactive network/graph visualizations with D3js, jQuery and Raphael.", "biocViews": [ "GraphAndNetwork", "Network", "Software", "ThirdPartyClient", "Visualization" ], "Author": "Stephane Cano [aut, cre], Sylvain Gubian [aut], Florian Martin [aut]", "Maintainer": "Stephane Cano ", "SystemRequirements": "jQuery, jQueryUI, qTip2, D3js and Raphael are required Javascript libraries made available via the online CDNJS service (http://cdnjs.cloudflare.com).", "source.ver": "src/contrib/RGraph2js_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RGraph2js_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RGraph2js_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RGraph2js_1.2.0.tgz", "vignettes": [ "vignettes/RGraph2js/inst/doc/RGraph2js.pdf" ], "vignetteTitles": [ "RGraph2js" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RGraph2js/inst/doc/RGraph2js.R" ] }, "Rgraphviz": { "Package": "Rgraphviz", "Version": "2.18.0", "Depends": [ "R (>= 2.6.0)", "methods", "utils", "graph", "grid" ], "Imports": [ "stats4", "graphics", "grDevices" ], "Suggests": [ "RUnit", "BiocGenerics", "XML" ], "License": "EPL", "Archs": "i386, x64", "MD5sum": "0c55f4c53a311f1e5ba9028d865afd09", "NeedsCompilation": "yes", "Title": "Provides plotting capabilities for R graph objects", "Description": "Interfaces R with the AT and T graphviz library for plotting R graph objects from the graph package.", "biocViews": [ "GraphAndNetwork", "Software", "Visualization" ], "Author": "Kasper Daniel Hansen [cre, aut], Jeff Gentry [aut], Li Long [aut], Robert Gentleman [aut], Seth Falcon [aut], Florian Hahne [aut], Deepayan Sarkar [aut]", "Maintainer": "Kasper Daniel Hansen ", "SystemRequirements": "optionally Graphviz (>= 2.16)", "source.ver": "src/contrib/Rgraphviz_2.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Rgraphviz_2.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Rgraphviz_2.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Rgraphviz_2.18.0.tgz", "vignettes": [ "vignettes/Rgraphviz/inst/doc/newRgraphvizInterface.pdf", "vignettes/Rgraphviz/inst/doc/Rgraphviz.pdf" ], "vignetteTitles": [ "A New Interface to Plot Graphs Using Rgraphviz", "How To Plot A Graph Using Rgraphviz" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Rgraphviz/inst/doc/newRgraphvizInterface.R", "vignettes/Rgraphviz/inst/doc/Rgraphviz.R" ], "dependsOnMe": [ "biocGraph", "BioMVCClass", "CellNOptR", "flowCL", "flowMerge", "gaucho", "GOFunction", "MineICA", "mvGST", "netresponse", "paircompviz", "pathRender", "ROntoTools", "SplicingGraphs", "TDARACNE", "ToPASeq" ], "importsMe": [ "apComplex", "biocGraph", "CompGO", "CytoML", "DEGraph", "EnrichmentBrowser", "facopy", "flowWorkspace", "GOFunction", "hyperdraw", "mirIntegrator", "nem", "OncoSimulR", "paircompviz", "pathview", "Pigengene", "qpgraph", "RchyOptimyx", "SplicingGraphs", "TRONCO" ], "suggestsMe": [ "altcdfenvs", "annotate", "BiocCaseStudies", "Category", "CNORfeeder", "CNORfuzzy", "ddgraph", "DEGraph", "flowCore", "GeneNetworkBuilder", "geneplotter", "GlobalAncova", "globaltest", "GOstats", "GSEABase", "KEGGgraph", "MLP", "NCIgraph", "NCIgraphData", "oneChannelGUI", "pcaGoPromoter", "pkgDepTools", "RBGL", "RBioinf", "rBiopaxParser", "RDAVIDWebService", "RpsiXML", "Rtreemix", "safe", "SNAData", "SPIA", "SRAdb", "Streamer", "topGO", "vtpnet" ] }, "rGREAT": { "Package": "rGREAT", "Version": "1.6.0", "Depends": [ "R (>= 3.1.2)", "GenomicRanges", "IRanges", "methods" ], "Imports": [ "rjson", "GetoptLong (>= 0.0.9)", "RCurl", "utils" ], "Suggests": [ "testthat (>= 0.3)", "knitr", "circlize" ], "License": "GPL (>= 2)", "MD5sum": "4f42ca21eed8e6df481444f21781d209", "NeedsCompilation": "no", "Title": "Client for GREAT Analysis", "Description": "This package makes GREAT (Genomic Regions Enrichment of Annotations Tool) analysis automatic by constructing a HTTP POST request according to user's input and automatically retrieving results from GREAT web server.", "biocViews": [ "Coverage", "GO", "GeneSetEnrichment", "GenomeAnnotation", "Pathways", "Sequencing", "Software", "WholeGenome" ], "Author": "Zuguang Gu", "Maintainer": "Zuguang Gu ", "URL": "https://github.com/jokergoo/rGREAT", "VignetteBuilder": "knitr", "source.ver": "src/contrib/rGREAT_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/rGREAT_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/rGREAT_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/rGREAT_1.6.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/rGREAT/inst/doc/rGREAT.R" ], "htmlDocs": [ "vignettes/rGREAT/inst/doc/rGREAT.html" ], "htmlTitles": [ "Analyze with GREAT" ] }, "RGSEA": { "Package": "RGSEA", "Version": "1.8.0", "Depends": [ "R(>= 2.10.0)" ], "Imports": [ "BiocGenerics" ], "Suggests": [ "BiocStyle", "GEOquery", "knitr", "RUnit" ], "License": "GPL(>=3)", "MD5sum": "0c0f7d4d03f8bfa58b2fface148dbccb", "NeedsCompilation": "no", "Title": "Random Gene Set Enrichment Analysis", "Description": "Combining bootstrap aggregating and Gene set enrichment analysis (GSEA), RGSEA is a classfication algorithm with high robustness and no over-fitting problem. It performs well especially for the data generated from different exprements.", "biocViews": [ "Classification", "GeneSetEnrichment", "Software", "StatisticalMethod" ], "Author": "Chengcheng Ma", "Maintainer": "Chengcheng Ma ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/RGSEA_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RGSEA_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RGSEA_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RGSEA_1.8.0.tgz", "vignettes": [ "vignettes/RGSEA/inst/doc/RGSEA.pdf" ], "vignetteTitles": [ "Introduction to RGSEA" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RGSEA/inst/doc/RGSEA.R" ] }, "rgsepd": { "Package": "rgsepd", "Version": "1.6.0", "Depends": [ "R (>= 3.3.0)", "DESeq2", "goseq (>= 1.17)" ], "Imports": [ "gplots", "biomaRt", "org.Hs.eg.db", "GO.db", "SummarizedExperiment", "hash", "AnnotationDbi" ], "Suggests": [ "boot", "tools", "RUnit", "BiocGenerics", "knitr", "xtable" ], "License": "GPL-3", "MD5sum": "7145a4be5879b2c25aa49eae5a3d16e0", "NeedsCompilation": "no", "Title": "Gene Set Enrichment / Projection Displays", "Description": "R/GSEPD is a bioinformatics package for R to help disambiguate transcriptome samples (a matrix of RNA-Seq counts at RefSeq IDs) by automating differential expression (with DESeq2), then gene set enrichment (with GOSeq), and finally a N-dimensional projection to quantify in which ways each sample is like either treatment group.", "biocViews": [ "DifferentialExpression", "GeneSetEnrichment", "RNASeq", "Software" ], "Author": "Karl Stamm", "Maintainer": "Karl Stamm ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/rgsepd_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/rgsepd_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/rgsepd_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/rgsepd_1.6.0.tgz", "vignettes": [ "vignettes/rgsepd/inst/doc/rgsepd.pdf" ], "vignetteTitles": [ "An Introduction to the rgsepd package" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/rgsepd/inst/doc/rgsepd.R" ] }, "rhdf5": { "Package": "rhdf5", "Version": "2.18.0", "Depends": [ "methods" ], "Imports": [ "zlibbioc" ], "Suggests": [ "bit64", "BiocStyle" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "f7838670e2bf8646a5ad47ee381b5f2b", "NeedsCompilation": "yes", "Title": "HDF5 interface to R", "Description": "This R/Bioconductor package provides an interface between HDF5 and R. HDF5's main features are the ability to store and access very large and/or complex datasets and a wide variety of metadata on mass storage (disk) through a completely portable file format. The rhdf5 package is thus suited for the exchange of large and/or complex datasets between R and other software package, and for letting R applications work on datasets that are larger than the available RAM.", "biocViews": [ "DataImport", "Infrastructure", "Software" ], "Author": "Bernd Fischer, Gregoire Pau", "Maintainer": "Bernd Fischer ", "SystemRequirements": "GNU make", "source.ver": "src/contrib/rhdf5_2.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/rhdf5_2.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/rhdf5_2.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/rhdf5_2.18.0.tgz", "vignettes": [ "vignettes/rhdf5/inst/doc/rhdf5.pdf" ], "vignetteTitles": [ "rhdf5" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/rhdf5/inst/doc/rhdf5.R" ], "dependsOnMe": [ "GENE.E", "GSCA" ], "importsMe": [ "biomformat", "diffHic", "DmelSGI", "DOQTL", "GENE.E", "h5vc", "HDF5Array", "IONiseR", "scater" ], "suggestsMe": [ "SummarizedExperiment" ] }, "Rhtslib": { "Package": "Rhtslib", "Version": "1.6.0", "Imports": [ "zlibbioc" ], "LinkingTo": [ "zlibbioc" ], "Suggests": [ "BiocStyle", "knitr" ], "License": "LGPL (>= 2)", "Archs": "i386, x64", "MD5sum": "55d3eb8ebd9762b87f145c33b8e72373", "NeedsCompilation": "yes", "Title": "HTSlib high-throughput sequencing library as an R package", "Description": "This package provides version 1.1 of the 'HTSlib' C library for high-throughput sequence analysis. The package is primarily useful to developers of other R packages who wish to make use of HTSlib. Motivation and instructions for use of this package are in the vignette, vignette(package=\"Rhtslib\", \"Rhtslib\").", "biocViews": [ "DataImport", "Sequencing", "Software" ], "Author": "Nathaniel Hayden [aut], Martin Morgan [aut], Bioconductor Package Maintainer [cre]", "Maintainer": "Bioconductor Package Maintainer ", "URL": "https://github.com/nhayden/Rhtslib, http://www.htslib.org/", "VignetteBuilder": "knitr", "BugReports": "https://github.com/nhayden/Rhtslib", "source.ver": "src/contrib/Rhtslib_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Rhtslib_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Rhtslib_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Rhtslib_1.6.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Rhtslib/inst/doc/Rhtslib.R" ], "htmlDocs": [ "vignettes/Rhtslib/inst/doc/Rhtslib.html" ], "htmlTitles": [ "Motivation and Use of Rhtslib" ], "dependsOnMe": [ "deepSNV" ], "importsMe": [ "csaw", "deepSNV", "diffHic" ] }, "rHVDM": { "Package": "rHVDM", "Version": "1.40.0", "Depends": [ "R (>= 2.10)", "R2HTML (>= 1.5)", "affy (>= 1.23.4)", "minpack.lm (>= 1.0-5)", "Biobase (>= 2.5.5)" ], "License": "GPL-2", "MD5sum": "4a95a4327bad2b6d6330f86de848208f", "NeedsCompilation": "no", "Title": "Hidden Variable Dynamic Modeling", "Description": "A R implementation of HVDM (Genome Biol 2006, V7(3) R25)", "biocViews": [ "Classification", "GraphAndNetwork", "Microarray", "NetworkInference", "Software", "Transcription" ], "Author": "Martino Barenco", "Maintainer": "Martino Barenco", "source.ver": "src/contrib/rHVDM_1.40.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/rHVDM_1.40.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/rHVDM_1.40.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/rHVDM_1.40.0.tgz", "vignettes": [ "vignettes/rHVDM/inst/doc/rHVDM.pdf" ], "vignetteTitles": [ "rHVDM primer" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/rHVDM/inst/doc/rHVDM.R" ] }, "RiboProfiling": { "Package": "RiboProfiling", "Version": "1.4.1", "Depends": [ "R (>= 3.2.2)", "Biostrings" ], "Imports": [ "BiocGenerics", "GenomeInfoDb", "GenomicRanges", "IRanges", "reshape2", "GenomicFeatures", "grid", "plyr", "S4Vectors", "GenomicAlignments", "ggplot2", "ggbio", "Rsamtools", "rtracklayer", "data.table", "sqldf" ], "Suggests": [ "knitr", "BiocStyle", "TxDb.Hsapiens.UCSC.hg19.knownGene", "BSgenome.Hsapiens.UCSC.hg19", "testthat", "SummarizedExperiment" ], "License": "GPL-3", "MD5sum": "e90c754d3cfccdce9a1d9848ce9b053d", "NeedsCompilation": "no", "Title": "Ribosome Profiling Data Analysis: from BAM to Data Representation and Interpretation", "Description": "Starting with a BAM file, this package provides the necessary functions for quality assessment, read start position recalibration, the counting of reads on CDS, 3'UTR, and 5'UTR, plotting of count data: pairs, log fold-change, codon frequency and coverage assessment, principal component analysis on codon coverage.", "biocViews": [ "Alignment", "Coverage", "PrincipalComponent", "QualityControl", "RiboSeq", "Sequencing", "Software" ], "Author": "Alexandra Popa", "Maintainer": "A. Popa ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/RiboProfiling_1.4.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RiboProfiling_1.4.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RiboProfiling_1.4.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RiboProfiling_1.4.1.tgz", "vignettes": [ "vignettes/RiboProfiling/inst/doc/RiboProfiling.pdf" ], "vignetteTitles": [ "Analysing Ribo-Seq data with the \"RiboProfiling\" package" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RiboProfiling/inst/doc/RiboProfiling.R" ] }, "riboSeqR": { "Package": "riboSeqR", "Version": "1.8.0", "Depends": [ "R (>= 3.0.2)", "methods", "GenomicRanges", "abind" ], "Imports": [ "Rsamtools", "IRanges", "baySeq", "GenomeInfoDb" ], "Suggests": [ "BiocStyle", "RUnit", "BiocGenerics" ], "License": "GPL-3", "MD5sum": "d140e8e95aeb56770375e802d716924c", "NeedsCompilation": "no", "Title": "Analysis of sequencing data from ribosome profiling experiments", "Description": "Plotting functions, frameshift detection and parsing of sequencing data from ribosome profiling experiments.", "biocViews": [ "Genetics", "RiboSeq", "Sequencing", "Software", "Visualization" ], "Author": "Thomas J. Hardcastle", "Maintainer": "Thomas J. Hardcastle ", "source.ver": "src/contrib/riboSeqR_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/riboSeqR_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/riboSeqR_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/riboSeqR_1.8.0.tgz", "vignettes": [ "vignettes/riboSeqR/inst/doc/riboSeqR.pdf" ], "vignetteTitles": [ "riboSeqR" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/riboSeqR/inst/doc/riboSeqR.R" ] }, "RImmPort": { "Package": "RImmPort", "Version": "1.2.0", "Imports": [ "plyr", "dplyr", "DBI", "data.table", "reshape2", "methods", "sqldf", "tools", "utils", "RSQLite" ], "Suggests": [ "knitr" ], "License": "GPL-3", "MD5sum": "2873ef43c7ffb34c1d524b7518810999", "NeedsCompilation": "no", "Title": "RImmPort: Enabling Ready-for-analysis Immunology Research Data", "Description": "The RImmPort package simplifies access to ImmPort data for analysis in the R environment. It provides a standards-based interface to the ImmPort study data that is in a proprietary format.", "biocViews": [ "BiomedicalInformatics", "DataImport", "DataRepresentation", "Software" ], "Author": "Ravi Shankar ", "Maintainer": "Ravi Shankar ", "URL": "http://bioconductor.org/packages/RImmPort/", "VignetteBuilder": "knitr", "source.ver": "src/contrib/RImmPort_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RImmPort_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RImmPort_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RImmPort_1.2.0.tgz", "vignettes": [ "vignettes/RImmPort/inst/doc/RImmPort_Article.pdf", "vignettes/RImmPort/inst/doc/RImmPort_QuickStart.pdf" ], "vignetteTitles": [ "RImmPort: Enabling ready-for-analysis immunology research data", "RImmPort: Quick Start Guide" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RImmPort/inst/doc/RImmPort_Article.R", "vignettes/RImmPort/inst/doc/RImmPort_QuickStart.R" ] }, "Ringo": { "Package": "Ringo", "Version": "1.38.0", "Depends": [ "methods", "Biobase (>= 1.14.1)", "RColorBrewer", "limma", "Matrix", "grid", "lattice" ], "Imports": [ "BiocGenerics (>= 0.1.11)", "genefilter", "limma", "vsn", "stats4" ], "Suggests": [ "rtracklayer (>= 1.3.1)", "mclust", "topGO (>= 1.15.0)" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "17a1b47d16f09dd4525f26b272c48539", "NeedsCompilation": "yes", "Title": "R Investigation of ChIP-chip Oligoarrays", "Description": "The package Ringo facilitates the primary analysis of ChIP-chip data. The main functionalities of the package are data read-in, quality assessment, data visualisation and identification of genomic regions showing enrichment in ChIP-chip. The package has functions to deal with two-color oligonucleotide microarrays from NimbleGen used in ChIP-chip projects, but also contains more general functions for ChIP-chip data analysis, given that the data is supplied as RGList (raw) or ExpressionSet (pre- processed). The package employs functions from various other packages of the Bioconductor project and provides additional ChIP-chip-specific and NimbleGen-specific functionalities.", "biocViews": [ "DataImport", "Microarray", "Preprocessing", "QualityControl", "Software", "TwoChannel" ], "Author": "Joern Toedling, Oleg Sklyar, Tammo Krueger, Matt Ritchie, Wolfgang Huber", "Maintainer": "J. Toedling ", "source.ver": "src/contrib/Ringo_1.38.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Ringo_1.38.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Ringo_1.38.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Ringo_1.38.0.tgz", "vignettes": [ "vignettes/Ringo/inst/doc/Ringo.pdf" ], "vignetteTitles": [ "R Investigation of NimbleGen Oligoarrays" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Ringo/inst/doc/Ringo.R" ], "dependsOnMe": [ "ccTutorial", "SimBindProfiles", "Starr" ], "importsMe": [ "Repitools" ] }, "RIPSeeker": { "Package": "RIPSeeker", "Version": "1.14.0", "Depends": [ "R (>= 2.15)", "methods", "S4Vectors (>= 0.9.25)", "IRanges", "GenomicRanges", "SummarizedExperiment", "Rsamtools", "GenomicAlignments", "rtracklayer" ], "Suggests": [ "biomaRt", "ChIPpeakAnno", "parallel", "GenomicFeatures" ], "License": "GPL-2", "MD5sum": "bfabcde873a440e12f7ff2aa6ec47975", "NeedsCompilation": "no", "Title": "RIPSeeker: a statistical package for identifying protein-associated transcripts from RIP-seq experiments", "Description": "Infer and discriminate RIP peaks from RIP-seq alignments using two-state HMM with negative binomial emission probability. While RIPSeeker is specifically tailored for RIP-seq data analysis, it also provides a suite of bioinformatics tools integrated within this self-contained software package comprehensively addressing issues ranging from post-alignments processing to visualization and annotation.", "biocViews": [ "RIPSeq", "Sequencing", "Software" ], "Author": "Yue Li", "Maintainer": "Yue Li ", "URL": "http://www.cs.utoronto.ca/~yueli/software.html", "source.ver": "src/contrib/RIPSeeker_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RIPSeeker_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RIPSeeker_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RIPSeeker_1.14.0.tgz", "vignettes": [ "vignettes/RIPSeeker/inst/doc/RIPSeeker.pdf" ], "vignetteTitles": [ "RIPSeeker: a statistical package for identifying protein-associated transcripts from RIP-seq experiments" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RIPSeeker/inst/doc/RIPSeeker.R" ], "dependsOnMe": [ "RIPSeekerData" ] }, "Risa": { "Package": "Risa", "Version": "1.16.0", "Depends": [ "R (>= 2.0.9)", "Biobase (>= 2.4.0)", "methods", "Rcpp (>= 0.9.13)", "biocViews", "affy" ], "Imports": [ "xcms" ], "Suggests": [ "faahKO (>= 1.2.11)" ], "License": "LGPL", "MD5sum": "6d8fff3bc2f11dce9a8317dfa554b0be", "NeedsCompilation": "no", "Title": "Converting experimental metadata from ISA-tab into Bioconductor data structures", "Description": "The Investigation / Study / Assay (ISA) tab-delimited format is a general purpose framework with which to collect and communicate complex metadata (i.e. sample characteristics, technologies used, type of measurements made) from experiments employing a combination of technologies, spanning from traditional approaches to high-throughput techniques. Risa allows to access metadata/data in ISA-Tab format and build Bioconductor data structures. Currently, data generated from microarray, flow cytometry and metabolomics-based (i.e. mass spectrometry) assays are supported. The package is extendable and efforts are undergoing to support metadata associated to proteomics assays.", "biocViews": [ "Annotation", "DataImport", "MassSpectrometry", "Software" ], "Author": "Alejandra Gonzalez-Beltran, Audrey Kauffmann, Steffen Neumann, Gabriella Rustici, ISA Team", "Maintainer": "Alejandra Gonzalez-Beltran ", "URL": "http://www.isa-tools.org/", "BugReports": "https://github.com/ISA-tools/Risa/issues", "source.ver": "src/contrib/Risa_1.16.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Risa_1.16.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Risa_1.16.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Risa_1.16.0.tgz", "vignettes": [ "vignettes/Risa/inst/doc/Risa.pdf" ], "vignetteTitles": [ "Risa: converts experimental metadata from ISA-tab into Bioconductor data structures" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Risa/inst/doc/Risa.R" ], "suggestsMe": [ "mtbls2" ] }, "RLMM": { "Package": "RLMM", "Version": "1.36.0", "Depends": [ "R (>= 2.1.0)" ], "Imports": [ "graphics", "grDevices", "MASS", "stats", "utils" ], "License": "LGPL (>= 2)", "MD5sum": "f3f6e78a8806d182fd77a1600f15208b", "NeedsCompilation": "no", "Title": "A Genotype Calling Algorithm for Affymetrix SNP Arrays", "Description": "A classification algorithm, based on a multi-chip, multi-SNP approach for Affymetrix SNP arrays. Using a large training sample where the genotype labels are known, this aglorithm will obtain more accurate classification results on new data. RLMM is based on a robust, linear model and uses the Mahalanobis distance for classification. The chip-to-chip non-biological variation is removed through normalization. This model-based algorithm captures the similarities across genotype groups and probes, as well as thousands other SNPs for accurate classification. NOTE: 100K-Xba only at for now.", "biocViews": [ "GeneticVariability", "Microarray", "OneChannel", "SNP", "Software" ], "Author": "Nusrat Rabbee , Gary Wong ", "Maintainer": "Nusrat Rabbee ", "URL": "http://www.stat.berkeley.edu/users/nrabbee/RLMM", "SystemRequirements": "Internal files Xba.CQV, Xba.regions (or other regions file)", "source.ver": "src/contrib/RLMM_1.36.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RLMM_1.36.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RLMM_1.36.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RLMM_1.36.0.tgz", "vignettes": [ "vignettes/RLMM/inst/doc/RLMM.pdf" ], "vignetteTitles": [ "RLMM Doc" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RLMM/inst/doc/RLMM.R" ] }, "Rmagpie": { "Package": "Rmagpie", "Version": "1.30.0", "Depends": [ "R (>= 2.6.1)", "Biobase (>= 2.5.5)" ], "Imports": [ "Biobase (>= 2.5.5)", "e1071", "graphics", "grDevices", "kernlab", "methods", "pamr", "stats", "utils" ], "Suggests": [ "xtable" ], "License": "GPL (>= 3)", "MD5sum": "ba5d2b5782d177919878aff332638eae", "NeedsCompilation": "no", "Title": "MicroArray Gene-expression-based Program In Error rate estimation", "Description": "Microarray Classification is designed for both biologists and statisticians. It offers the ability to train a classifier on a labelled microarray dataset and to then use that classifier to predict the class of new observations. A range of modern classifiers are available, including support vector machines (SVMs), nearest shrunken centroids (NSCs)... Advanced methods are provided to estimate the predictive error rate and to report the subset of genes which appear essential in discriminating between classes.", "biocViews": [ "Classification", "Microarray", "Software" ], "Author": "Camille Maumet , with contributions from C. Ambroise J. Zhu", "Maintainer": "Camille Maumet ", "URL": "http://www.bioconductor.org/", "source.ver": "src/contrib/Rmagpie_1.30.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Rmagpie_1.30.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Rmagpie_1.30.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Rmagpie_1.30.0.tgz", "vignettes": [ "vignettes/Rmagpie/inst/doc/Magpie_examples.pdf" ], "vignetteTitles": [ "Rmagpie Examples" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Rmagpie/inst/doc/Magpie_examples.R" ] }, "RMassBank": { "Package": "RMassBank", "Version": "2.2.1", "Depends": [ "Rcpp" ], "Imports": [ "XML", "RCurl", "rjson", "S4Vectors", "digest", "rcdk", "yaml", "mzR", "methods", "Biobase", "MSnbase" ], "Suggests": [ "gplots", "RMassBankData", "xcms (>= 1.37.1)", "CAMERA", "ontoCAT", "RUnit", "enviPat" ], "License": "Artistic-2.0", "MD5sum": "bed8cefcc3db7231fcdf5ee5af258d44", "NeedsCompilation": "no", "Title": "Workflow to process tandem MS files and build MassBank records", "Description": "Workflow to process tandem MS files and build MassBank records. Functions include automated extraction of tandem MS spectra, formula assignment to tandem MS fragments, recalibration of tandem MS spectra with assigned fragments, spectrum cleanup, automated retrieval of compound information from Internet databases, and export to MassBank records.", "biocViews": [ "Bioinformatics", "MassSpectrometry", "Metabolomics", "Software" ], "Author": "Michael Stravs, Emma Schymanski, Steffen Neumann, Erik Mueller, with contributions from Tobias Schulze", "Maintainer": "RMassBank at Eawag ", "SystemRequirements": "OpenBabel", "source.ver": "src/contrib/RMassBank_2.2.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RMassBank_2.2.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RMassBank_2.2.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RMassBank_2.2.1.tgz", "vignettes": [ "vignettes/RMassBank/inst/doc/RMassBank.pdf", "vignettes/RMassBank/inst/doc/RMassBankNonstandard.pdf", "vignettes/RMassBank/inst/doc/RMassBankXCMS.pdf" ], "vignetteTitles": [ "RMassBank walkthrough", "RMassBank non-standard usage", "RMassBank using XCMS walkthrough" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RMassBank/inst/doc/RMassBank.R", "vignettes/RMassBank/inst/doc/RMassBankNonstandard.R", "vignettes/RMassBank/inst/doc/RMassBankXCMS.R" ], "suggestsMe": [ "RMassBankData" ] }, "rMAT": { "Package": "rMAT", "Version": "3.24.0", "Depends": [ "R(>= 2.9.0)", "BiocGenerics (>= 0.1.3)", "IRanges (>= 1.13.10)", "Biobase (>= 2.15.1)", "affxparser" ], "Imports": [ "stats", "methods", "BiocGenerics", "IRanges", "Biobase", "affxparser", "stats4" ], "Suggests": [ "GenomeGraphs", "rtracklayer" ], "License": "Artistic-2.0", "MD5sum": "bc6d34187eca473eee385005a998b651", "NeedsCompilation": "yes", "Title": "R implementation from MAT program to normalize and analyze tiling arrays and ChIP-chip data.", "Description": "This package is an R version of the package MAT and contains functions to parse and merge Affymetrix BPMAP and CEL tiling array files (using C++ based Fusion SDK and Bioconductor package affxparser), normalize tiling arrays using sequence specific models, detect enriched regions from ChIP-chip experiments. Note: users should have GSL and GenomeGraphs installed. Windows users: 'consult the README file available in the inst directory of the source distribution for necessary configuration instructions'. Snow Leopard users can take advantage of increase speed with Grand Central Dispatch!", "biocViews": [ "Microarray", "Preprocessing", "Software" ], "Author": "Charles Cheung and Arnaud Droit and Raphael Gottardo", "Maintainer": "Arnaud Droit and Raphael Gottardo ", "URL": "http://www.rglab.org", "SystemRequirements": "GSL (GNU Scientific Library)", "source.ver": "src/contrib/rMAT_3.24.0.tar.gz", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/rMAT_3.24.0.tgz", "vignettes": [ "vignettes/rMAT/inst/doc/rMAT.pdf" ], "vignetteTitles": [ "The rMAT users guide" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/rMAT/inst/doc/rMAT.R" ] }, "RmiR": { "Package": "RmiR", "Version": "1.30.0", "Depends": [ "R (>= 2.7.0)", "RmiR.Hs.miRNA", "RSVGTipsDevice" ], "Imports": [ "DBI", "methods", "stats" ], "Suggests": [ "hgug4112a.db", "org.Hs.eg.db" ], "License": "Artistic-2.0", "MD5sum": "14e17ae2c910f0c1b5551743304c91ee", "NeedsCompilation": "no", "Title": "Package to work with miRNAs and miRNA targets with R", "Description": "Useful functions to merge microRNA and respective targets using differents databases", "biocViews": [ "GeneExpression", "Microarray", "Software", "TimeCourse", "Visualization" ], "Author": "Francesco Favero", "Maintainer": "Francesco Favero ", "source.ver": "src/contrib/RmiR_1.30.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RmiR_1.30.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RmiR_1.30.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RmiR_1.30.0.tgz", "vignettes": [ "vignettes/RmiR/inst/doc/RmiR.pdf" ], "vignetteTitles": [ "RmiR Vignette" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RmiR/inst/doc/RmiR.R" ], "suggestsMe": [ "oneChannelGUI" ] }, "RNAinteract": { "Package": "RNAinteract", "Version": "1.22.0", "Depends": [ "R (>= 2.12.0)", "abind", "locfit", "Biobase" ], "Imports": [ "RColorBrewer", "ICS", "ICSNP", "cellHTS2", "geneplotter", "gplots", "grid", "hwriter", "lattice", "latticeExtra", "limma", "methods", "splots (>= 1.13.12)" ], "License": "Artistic-2.0", "MD5sum": "8a0f17fb3f9284b21545720f27ae2290", "NeedsCompilation": "no", "Title": "Estimate Pairwise Interactions from multidimensional features", "Description": "RNAinteract estimates genetic interactions from multi-dimensional read-outs like features extracted from images. The screen is assumed to be performed in multi-well plates or similar designs. Starting from a list of features (e.g. cell number, area, fluorescence intensity) per well, genetic interactions are estimated. The packages provides functions for reporting interacting gene pairs, plotting heatmaps and double RNAi plots. An HTML report can be written for quality control and analysis.", "biocViews": [ "CellBasedAssays", "Preprocessing", "QualityControl", "Software", "Visualization" ], "Author": "Bernd Fischer ", "Maintainer": "Bernd Fischer ", "source.ver": "src/contrib/RNAinteract_1.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RNAinteract_1.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RNAinteract_1.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RNAinteract_1.22.0.tgz", "vignettes": [ "vignettes/RNAinteract/inst/doc/RNAinteract.pdf" ], "vignetteTitles": [ "RNAinteract" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RNAinteract/inst/doc/RNAinteract.R" ], "dependsOnMe": [ "RNAinteractMAPK" ] }, "RNAither": { "Package": "RNAither", "Version": "2.22.0", "Depends": [ "R (>= 2.10)", "topGO", "RankProd", "prada" ], "Imports": [ "geneplotter", "limma", "biomaRt", "car", "splots", "methods" ], "License": "Artistic-2.0", "MD5sum": "29cd60f4554987551067434ffb71715a", "NeedsCompilation": "no", "Title": "Statistical analysis of high-throughput RNAi screens", "Description": "RNAither analyzes cell-based RNAi screens, and includes quality assessment, customizable normalization and statistical tests, leading to lists of significant genes and biological processes.", "biocViews": [ "Annotation", "CellBasedAssays", "GO", "Preprocessing", "QualityControl", "Software", "Visualization" ], "Author": "Nora Rieber and Lars Kaderali, University of Heidelberg, Viroquant Research Group Modeling, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany", "Maintainer": "Lars Kaderali ", "source.ver": "src/contrib/RNAither_2.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RNAither_2.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RNAither_2.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RNAither_2.22.0.tgz", "vignettes": [ "vignettes/RNAither/inst/doc/vignetteRNAither.pdf" ], "vignetteTitles": [ "RNAither, an automated pipeline for the statistical analysis of high-throughput RNAi screens" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RNAither/inst/doc/vignetteRNAither.R" ] }, "RNAprobR": { "Package": "RNAprobR", "Version": "1.6.0", "Depends": [ "R (>= 3.1.1)", "GenomicFeatures(>= 1.16.3)", "plyr(>= 1.8.1)", "BiocGenerics(>= 0.10.0)" ], "Imports": [ "Biostrings(>= 2.32.1)", "GenomicRanges(>= 1.16.4)", "Rsamtools(>= 1.16.1)", "rtracklayer(>= 1.24.2)", "GenomicAlignments(>= 1.5.12)" ], "Suggests": [ "BiocStyle" ], "License": "GPL (>=2)", "MD5sum": "259ce29e97cefb8569fdddbfce2cb510", "NeedsCompilation": "no", "Title": "An R package for analysis of massive parallel sequencing based RNA structure probing data", "Description": "This package facilitates analysis of Next Generation Sequencing data for which positional information with a single nucleotide resolution is a key. It allows for applying different types of relevant normalizations, data visualization and export in a table or UCSC compatible bedgraph file.", "biocViews": [ "Coverage", "GenomeAnnotation", "Normalization", "Sequencing", "Software" ], "Author": "Lukasz Jan Kielpinski [aut], Nikos Sidiropoulos [cre, aut], Jeppe Vinther [aut]", "Maintainer": "Nikos Sidiropoulos ", "source.ver": "src/contrib/RNAprobR_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RNAprobR_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RNAprobR_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RNAprobR_1.6.0.tgz", "vignettes": [ "vignettes/RNAprobR/inst/doc/RNAprobR.pdf" ], "vignetteTitles": [ "RNAprobR: An R package for analysis of the massive parallel sequencing based methods of RNA structure probing" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RNAprobR/inst/doc/RNAprobR.R" ] }, "rnaseqcomp": { "Package": "rnaseqcomp", "Version": "1.4.0", "Depends": [ "R (>= 3.2.0)" ], "Imports": [ "RColorBrewer", "methods" ], "Suggests": [ "BiocStyle", "knitr", "rmarkdown" ], "License": "GPL-3", "MD5sum": "b0b383f3b8f4f425afc3ec8cd7032a3f", "NeedsCompilation": "no", "Title": "Benchmarks for RNA-seq Quantification Pipelines", "Description": "Several quantitative and visualized benchmarks for RNA-seq quantification pipelines. Two-condition quantifications for genes, transcripts, junctions or exons by each pipeline with necessary meta information should be organized into numeric matrices in order to proceed the evaluation.", "biocViews": [ "QualityControl", "RNASeq", "Software", "Visualization" ], "Author": "Mingxiang Teng and Rafael A. Irizarry", "Maintainer": "Mingxiang Teng ", "URL": "https://github.com/tengmx/rnaseqcomp", "VignetteBuilder": "knitr", "source.ver": "src/contrib/rnaseqcomp_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/rnaseqcomp_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/rnaseqcomp_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/rnaseqcomp_1.4.0.tgz", "vignettes": [ "vignettes/rnaseqcomp/inst/doc/rnaseqcomp.pdf" ], "vignetteTitles": [ "The rnaseqcomp user's guide" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/rnaseqcomp/inst/doc/rnaseqcomp.R" ] }, "rnaSeqMap": { "Package": "rnaSeqMap", "Version": "2.32.0", "Depends": [ "R (>= 2.11.0)", "methods", "Biobase", "Rsamtools", "GenomicAlignments" ], "Imports": [ "GenomicRanges", "IRanges", "edgeR", "DESeq", "DBI" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "d264449b52509dc1fd80df8808d37e2f", "NeedsCompilation": "yes", "Title": "rnaSeq secondary analyses", "Description": "The rnaSeqMap library provides classes and functions to analyze the RNA-sequencing data using the coverage profiles in multiple samples at a time", "biocViews": [ "Annotation", "DifferentialExpression", "GeneExpression", "RNASeq", "ReportWriting", "SAGE", "Sequencing", "Software", "Transcription", "Visualization" ], "Author": "Anna Lesniewska ; Michal Okoniewski ", "Maintainer": "Michal Okoniewski ", "source.ver": "src/contrib/rnaSeqMap_2.32.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/rnaSeqMap_2.32.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/rnaSeqMap_2.32.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/rnaSeqMap_2.32.0.tgz", "vignettes": [ "vignettes/rnaSeqMap/inst/doc/rnaSeqMap.pdf" ], "vignetteTitles": [ "rnaSeqMap primer" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/rnaSeqMap/inst/doc/rnaSeqMap.R" ], "dependsOnMe": [ "ampliQueso" ] }, "RNASeqPower": { "Package": "RNASeqPower", "Version": "1.14.0", "License": "LGPL (>=2)", "MD5sum": "685017f2ad8309d3c16958b74dc947c6", "NeedsCompilation": "no", "Title": "Sample size for RNAseq studies", "Description": "RNA-seq, sample size", "biocViews": [ "RNASeq", "Software" ], "Author": "Terry M Therneau [aut, cre], Hart Stephen [ctb]", "Maintainer": "Terry M Therneau ", "source.ver": "src/contrib/RNASeqPower_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RNASeqPower_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RNASeqPower_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RNASeqPower_1.14.0.tgz", "vignettes": [ "vignettes/RNASeqPower/inst/doc/samplesize.pdf" ], "vignetteTitles": [ "RNAseq samplesize" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RNASeqPower/inst/doc/samplesize.R" ] }, "RnaSeqSampleSize": { "Package": "RnaSeqSampleSize", "Version": "1.6.0", "Depends": [ "R (>= 2.10)", "RnaSeqSampleSizeData" ], "Imports": [ "biomaRt", "edgeR", "heatmap3", "matlab", "KEGGREST", "Rcpp (>= 0.11.2)" ], "LinkingTo": [ "Rcpp" ], "Suggests": [ "BiocStyle", "knitr" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "8dffc306e07720525d95bdec11f75cfa", "NeedsCompilation": "yes", "Title": "RnaSeqSampleSize", "Description": "RnaSeqSampleSize package provides a sample size calculation method based on negative binomial model and the exact test for assessing differential expression analysis of RNA-seq data", "biocViews": [ "DifferentialExpression", "ExperimentalDesign", "GeneExpression", "RNASeq", "Sequencing", "Software" ], "Author": "Shilin Zhao, Chung-I Li, Yan Guo, Quanhu Sheng, Yu Shyr", "Maintainer": "Shilin Zhao ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/RnaSeqSampleSize_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RnaSeqSampleSize_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RnaSeqSampleSize_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RnaSeqSampleSize_1.6.0.tgz", "vignettes": [ "vignettes/RnaSeqSampleSize/inst/doc/RnaSeqSampleSize.pdf" ], "vignetteTitles": [ "RnaSeqSampleSize: Sample size estimation by real data" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RnaSeqSampleSize/inst/doc/RnaSeqSampleSize.R" ] }, "RnBeads": { "Package": "RnBeads", "Version": "1.6.1", "Depends": [ "R (>= 3.0.0)", "BiocGenerics", "S4Vectors (>= 0.9.25)", "GenomicRanges", "MASS", "RColorBrewer", "cluster", "ff", "fields", "ggplot2 (>= 0.9.2)", "gplots", "gridExtra", "limma", "matrixStats", "methods", "illuminaio", "methylumi", "plyr" ], "Imports": [ "IRanges" ], "Suggests": [ "Category", "GEOquery", "GOstats", "Gviz", "IlluminaHumanMethylation450kmanifest", "RPMM", "RefFreeEWAS", "RnBeads.hg19", "XML", "annotate", "biomaRt", "foreach", "doParallel", "ggbio", "isva", "mclust", "mgcv", "minfi", "nlme", "org.Hs.eg.db", "org.Mm.eg.db", "org.Rn.eg.db", "quadprog", "rtracklayer", "sva", "wateRmelon", "wordcloud", "argparse", "glmnet", "impute" ], "License": "GPL-3", "MD5sum": "c305e40da0de671c295e52360904bbb2", "NeedsCompilation": "no", "Title": "RnBeads", "Description": "RnBeads facilitates comprehensive analysis of various types of DNA methylation data at the genome scale.", "biocViews": [ "BatchEffect", "CpGIsland", "DNAMethylation", "DataImport", "DifferentialMethylation", "Epigenetics", "MethylSeq", "MethylationArray", "Preprocessing", "QualityControl", "Sequencing", "Software", "TwoChannel" ], "Author": "Yassen Assenov [aut], Pavlo Lutsik [aut], Fabian Mueller [aut, cre]", "Maintainer": "Fabian Mueller ", "source.ver": "src/contrib/RnBeads_1.6.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RnBeads_1.6.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RnBeads_1.6.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RnBeads_1.6.1.tgz", "vignettes": [ "vignettes/RnBeads/inst/doc/RnBeads_Annotations.pdf", "vignettes/RnBeads/inst/doc/RnBeads.pdf" ], "vignetteTitles": [ "RnBeads Annotation", "Comprehensive DNA Methylation Analysis with RnBeads" ], "hasREADME": true, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RnBeads/inst/doc/RnBeads_Annotations.R", "vignettes/RnBeads/inst/doc/RnBeads.R" ], "suggestsMe": [ "RnBeads.hg19", "RnBeads.hg38", "RnBeads.mm10", "RnBeads.mm9", "RnBeads.rn5" ] }, "Rnits": { "Package": "Rnits", "Version": "1.8.0", "Depends": [ "R (>= 3.1.0)", "Biobase", "ggplot2", "limma", "methods" ], "Imports": [ "affy", "boot", "impute", "splines", "graphics", "qvalue", "reshape2" ], "Suggests": [ "BiocStyle", "knitr", "GEOquery", "stringr" ], "License": "GPL-3", "MD5sum": "579f3d6bd1ca54c7fd8576b46a34d152", "NeedsCompilation": "no", "Title": "R Normalization and Inference of Time Series data", "Description": "R/Bioconductor package for normalization, curve registration and inference in time course gene expression data", "biocViews": [ "DifferentialExpression", "GeneExpression", "Microarray", "Normalization", "Software", "TimeCourse" ], "Author": "Dipen P. Sangurdekar ", "Maintainer": "Dipen P. Sangurdekar ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/Rnits_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Rnits_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Rnits_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Rnits_1.8.0.tgz", "vignettes": [ "vignettes/Rnits/inst/doc/Rnits-vignette.pdf" ], "vignetteTitles": [ "R/Bioconductor package for normalization and differential expression inference in time series gene expression microarray data." ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Rnits/inst/doc/Rnits-vignette.R" ] }, "roar": { "Package": "roar", "Version": "1.10.0", "Depends": [ "R (>= 3.0.1)" ], "Imports": [ "methods", "BiocGenerics", "S4Vectors", "IRanges", "GenomicRanges", "SummarizedExperiment", "GenomicAlignments (>= 0.99.4)", "rtracklayer", "GenomeInfoDb" ], "Suggests": [ "RNAseqData.HNRNPC.bam.chr14", "testthat" ], "License": "GPL-3", "MD5sum": "92865bf8ceb4c85c7e934b4e00a92a51", "NeedsCompilation": "no", "Title": "Identify differential APA usage from RNA-seq alignments", "Description": "Identify preferential usage of APA sites, comparing two biological conditions, starting from known alternative sites and alignments obtained from standard RNA-seq experiments.", "biocViews": [ "HighThroughputSequencing", "RNAseq", "Sequencing", "Software", "Transcription" ], "Author": "Elena Grassi", "Maintainer": "Elena Grassi ", "URL": "https://github.com/vodkatad/roar/", "source.ver": "src/contrib/roar_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/roar_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/roar_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/roar_1.10.0.tgz", "vignettes": [ "vignettes/roar/inst/doc/roar.pdf" ], "vignetteTitles": [ "Identify differential APA usage from RNA-seq alignments" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/roar/inst/doc/roar.R" ], "importsMe": [ "XBSeq" ] }, "ROC": { "Package": "ROC", "Version": "1.50.0", "Depends": [ "R (>= 1.9.0)", "utils", "methods" ], "Suggests": [ "Biobase" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "365d2b3224174fc2e405a7cd5334ab9b", "NeedsCompilation": "yes", "Title": "utilities for ROC, with uarray focus", "Description": "utilities for ROC, with uarray focus", "biocViews": [ "DifferentialExpression", "Software" ], "Author": "Vince Carey , Henning Redestig for C++ language enhancements", "Maintainer": "Vince Carey ", "URL": "http://www.bioconductor.org", "source.ver": "src/contrib/ROC_1.50.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ROC_1.50.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ROC_1.50.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ROC_1.50.0.tgz", "vignettes": [ "vignettes/ROC/inst/doc/ROCnotes.pdf" ], "vignetteTitles": [ "ROC notes" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ROC/inst/doc/ROCnotes.R" ], "dependsOnMe": [ "maPredictDSC", "TCC", "wateRmelon" ], "importsMe": [ "clst" ], "suggestsMe": [ "genefilter", "MCRestimate" ] }, "Roleswitch": { "Package": "Roleswitch", "Version": "1.12.0", "Depends": [ "R (>= 2.10)", "pracma", "reshape", "plotrix", "microRNA", "biomaRt", "Biostrings", "Biobase", "DBI" ], "Suggests": [ "ggplot2" ], "License": "GPL-2", "MD5sum": "ed14309b2d303faea5d1c9d3cd938388", "NeedsCompilation": "no", "Title": "Infer miRNA-mRNA interactions using paired expression data from a single sample", "Description": "Infer Probabilities of MiRNA-mRNA Interaction Signature (ProMISe) using paired expression data from a single sample. Roleswitch operates in two phases by inferring the probability of mRNA (miRNA) being the targets (\"targets\") of miRNA (mRNA), taking into account the expression of all of the mRNAs (miRNAs) due to their potential competition for the same miRNA (mRNA). Due to dynamic miRNA repression in the cell, Roleswitch assumes that the total transcribed mRNA levels are higher than the observed (equilibrium) mRNA levels and iteratively updates the total transcription of each mRNA targets based on the above inference. NB: in the paper, we used ProMISe as both the model name and inferred score name.", "biocViews": [ "Software", "miRNA" ], "Author": "Yue Li", "Maintainer": "Yue Li ", "URL": "http://www.cs.utoronto.ca/~yueli/roleswitch.html", "source.ver": "src/contrib/Roleswitch_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Roleswitch_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Roleswitch_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Roleswitch_1.12.0.tgz", "vignettes": [ "vignettes/Roleswitch/inst/doc/Roleswitch.pdf" ], "vignetteTitles": [ "Roleswitch" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Roleswitch/inst/doc/Roleswitch.R" ], "importsMe": [ "miRLAB" ] }, "rols": { "Package": "rols", "Version": "2.2.5", "Depends": [ "methods" ], "Imports": [ "httr", "progress", "jsonlite", "utils", "Biobase" ], "Suggests": [ "GO.db", "knitr (>= 1.1.0)", "BiocStyle", "testthat", "lubridate", "DT", "rmarkdown" ], "License": "GPL-2", "MD5sum": "71371ef54d2b74ec773a0447266be541", "NeedsCompilation": "no", "Title": "An R interface to the Ontology Lookup Service", "Description": "An interface to the Ontology Lookup Service (OLS) to access and query hundred of ontolgies directly from R.", "biocViews": [ "Annotation", "GO", "MassSpectrometry", "Software" ], "Author": "Laurent Gatto , with contributions from Tiago Chedraoui Silva.", "Maintainer": "Laurent Gatto ", "URL": "http://lgatto.github.com/rols/", "VignetteBuilder": "knitr", "BugReports": "https://github.com/lgatto/rols/issues", "source.ver": "src/contrib/rols_2.2.5.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/rols_2.2.5.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/rols_2.2.5.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/rols_2.2.5.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/rols/inst/doc/rols.R" ], "htmlDocs": [ "vignettes/rols/inst/doc/rols.html" ], "htmlTitles": [ "The rols interface to the Ontology Lookup Service" ], "suggestsMe": [ "MSnbase", "RforProteomics" ] }, "ROntoTools": { "Package": "ROntoTools", "Version": "2.2.0", "Depends": [ "methods", "graph", "boot", "KEGGREST", "KEGGgraph", "Rgraphviz" ], "Suggests": [ "RUnit", "BiocGenerics" ], "License": "CC BY-NC-ND 4.0 + file LICENSE", "MD5sum": "dc6003bfe9be7bcd476adce52eb50e64", "NeedsCompilation": "no", "Title": "R Onto-Tools suite", "Description": "Suite of tools for functional analysis.", "biocViews": [ "GraphsAndNetworks", "Microarray", "NetworkAnalysis", "Software" ], "Author": "Calin Voichita and Sahar Ansari and Sorin Draghici ", "Maintainer": "Calin Voichita ", "source.ver": "src/contrib/ROntoTools_2.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ROntoTools_2.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ROntoTools_2.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ROntoTools_2.2.0.tgz", "vignettes": [ "vignettes/ROntoTools/inst/doc/rontotools.pdf" ], "vignetteTitles": [ "ROntoTools" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/ROntoTools/inst/doc/rontotools.R" ], "importsMe": [ "mirIntegrator" ] }, "ropls": { "Package": "ropls", "Version": "1.6.2", "Imports": [ "Biobase", "methods" ], "Suggests": [ "BiocGenerics", "BiocStyle", "CAMERA", "faahKO", "knitr", "multtest", "rmarkdown", "RUnit", "xcms" ], "License": "CeCILL", "MD5sum": "2fb5a979001b540f29ac634a73b46e31", "NeedsCompilation": "no", "Title": "PCA, PLS(-DA) and OPLS(-DA) for multivariate analysis and feature selection of omics data", "Description": "Latent variable modeling with Principal Component Analysis(PCA) and Partial Least Squares (PLS) are powerful methods for visualization, regression, classification, and feature selection of omics data where the number of variables exceeds the number of samples and with multicollinearity among variables. Orthogonal Partial Least Squares (OPLS) enables to separately model the variation correlated (predictive) to the factor of interest and the uncorrelated (orthogonal) variation. While performing similarly to PLS, OPLS facilitates interpretation. Successful applications of these chemometrics techniques include spectroscopic data such as Raman spectroscopy, nuclear magnetic resonance (NMR), mass spectrometry (MS) in metabolomics and proteomics, but also transcriptomics data. In addition to scores, loadings and weights plots, the package provides metrics and graphics to determine the optimal number of components (e.g. with the R2 and Q2 coefficients), check the validity of the model by permutation testing, detect outliers, and perform feature selection (e.g. with Variable Importance in Projection or regression coefficients). The package can be accessed via a user interface on the Workflow4Metabolomics.org online resource for computational metabolomics (built upon the Galaxy environment).", "biocViews": [ "Classification", "Lipidomics", "MassSpectrometry", "Metabolomics", "PrincipalComponent", "Proteomics", "Regression", "Software", "Transcriptomics" ], "Author": "Etienne A. Thevenot ", "Maintainer": "Etienne A. Thevenot ", "URL": "http://dx.doi.org/10.1021/acs.jproteome.5b00354", "VignetteBuilder": "knitr", "source.ver": "src/contrib/ropls_1.6.2.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ropls_1.6.2.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ropls_1.6.2.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ropls_1.6.2.tgz", "vignettes": [ "vignettes/ropls/inst/doc/ropls-vignette.pdf" ], "vignetteTitles": [ "Vignette Title" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ropls/inst/doc/ropls-vignette.R" ], "importsMe": [ "biosigner" ], "suggestsMe": [ "proFIA" ] }, "ROTS": { "Package": "ROTS", "Version": "1.2.0", "Depends": [ "R (>= 3.3)" ], "Imports": [ "Rcpp", "stats", "Biobase", "methods" ], "LinkingTo": [ "Rcpp" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "8c70dc276838e5fffe5f20f388e34401", "NeedsCompilation": "yes", "Title": "Reproducibility-Optimized Test Statistic", "Description": "Calculates the Reproducibility-Optimized Test Statistic (ROTS) for differential testing in omics data.", "biocViews": [ "DifferentialExpression", "GeneExpression", "Microarray", "Proteomics", "RNASeq", "Software" ], "Author": "Fatemeh Seyednasrollah, Tomi Suomi, Laura L. Elo", "Maintainer": "Fatemeh Seyednasrollah ", "source.ver": "src/contrib/ROTS_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ROTS_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ROTS_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ROTS_1.2.0.tgz", "vignettes": [ "vignettes/ROTS/inst/doc/ROTS.pdf" ], "vignetteTitles": [ "ROTS: Reproducibility Optimized Test Statistic" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ROTS/inst/doc/ROTS.R" ], "importsMe": [ "PECA" ] }, "RPA": { "Package": "RPA", "Version": "1.30.0", "Depends": [ "R (>= 3.1.1)", "affy", "BiocGenerics", "methods", "phyloseq" ], "Suggests": [ "affydata", "parallel" ], "License": "BSD_2_clause + file LICENSE", "MD5sum": "6510539053459f44732d4705802c8ccf", "NeedsCompilation": "no", "Title": "RPA: Robust Probabilistic Averaging for probe-level analysis", "Description": "Probabilistic analysis of probe reliability and differential gene expression on short oligonucleotide arrays. Lahti et al. \"Probabilistic Analysis of Probe Reliability in Differential Gene Expression Studies with Short Oligonucleotide Arrays\", TCBB/IEEE, 2011. http://doi.ieeecomputersociety.org/10.1109/TCBB.2009.38", "biocViews": [ "GeneExpression", "Microarray", "Preprocessing", "QualityControl", "Software" ], "Author": "Leo Lahti ", "Maintainer": "Leo Lahti ", "URL": "https://github.com/antagomir/RPA", "BugReports": "https://github.com/antagomir/RPA", "source.ver": "src/contrib/RPA_1.30.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RPA_1.30.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RPA_1.30.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RPA_1.30.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "dependsOnMe": [ "prebs" ] }, "RpsiXML": { "Package": "RpsiXML", "Version": "2.16.0", "Depends": [ "methods", "annotate (>= 1.21.0)", "graph (>= 1.21.0)", "Biobase", "RBGL (>= 1.17.0)", "XML (>= 2.4.0)", "hypergraph (>= 1.15.2)", "AnnotationDbi" ], "Suggests": [ "org.Hs.eg.db", "org.Mm.eg.db", "org.Dm.eg.db", "org.Rn.eg.db", "org.Sc.sgd.db", "hom.Hs.inp.db", "hom.Mm.inp.db", "hom.Dm.inp.db", "hom.Rn.inp.db", "hom.Sc.inp.db", "Rgraphviz", "ppiStats", "ScISI" ], "License": "LGPL-3", "MD5sum": "a165ca5863cd8c0237d348cc8cddd190", "NeedsCompilation": "no", "Title": "R interface to PSI-MI 2.5 files", "Description": "Queries, data structure and interface to visualization of interaction datasets. This package inplements the PSI-MI 2.5 standard and supports up to now 8 databases. Further databases supporting PSI-MI 2.5 standard will be added continuously.", "biocViews": [ "Infrastructure", "Proteomics", "Software" ], "Author": "Jitao David Zhang, Stefan Wiemann, Marc Carlson, with contributions from Tony Chiang", "Maintainer": "Jitao David Zhang ", "URL": "http://www.bioconductor.org", "source.ver": "src/contrib/RpsiXML_2.16.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RpsiXML_2.16.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RpsiXML_2.16.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RpsiXML_2.16.0.tgz", "vignettes": [ "vignettes/RpsiXML/inst/doc/RpsiXML.pdf", "vignettes/RpsiXML/inst/doc/RpsiXMLApp.pdf" ], "vignetteTitles": [ "Reading PSI-25 XML files", "Application Examples of RpsiXML package" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RpsiXML/inst/doc/RpsiXML.R", "vignettes/RpsiXML/inst/doc/RpsiXMLApp.R" ], "dependsOnMe": [ "ScISI" ], "importsMe": [ "ScISI" ] }, "rpx": { "Package": "rpx", "Version": "1.10.2", "Depends": [ "methods" ], "Imports": [ "XML", "RCurl", "utils" ], "Suggests": [ "MSnbase", "Biostrings", "BiocStyle", "testthat", "knitr" ], "License": "GPL-2", "MD5sum": "6ad203643070cc6b2504e7869ca5ca24", "NeedsCompilation": "no", "Title": "R Interface to the ProteomeXchange Repository", "Description": "This package implements an interface to proteomics data submitted to the ProteomeXchange consortium.", "biocViews": [ "DataImport", "MassSpectrometry", "Proteomics", "Software", "ThirdPartyClient" ], "Author": "Laurent Gatto", "Maintainer": "Laurent Gatto ", "URL": "https://github.com/lgatto/rpx", "VignetteBuilder": "knitr", "BugReports": "https://github.com/lgatto/rpx/issues", "source.ver": "src/contrib/rpx_1.10.2.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/rpx_1.10.2.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/rpx_1.10.2.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/rpx_1.10.2.tgz", "vignettes": [ "vignettes/rpx/inst/doc/rpx.pdf" ], "vignetteTitles": [ "An interface to proteomics data repositories" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/rpx/inst/doc/rpx.R" ], "suggestsMe": [ "MSnbase", "proteoQC" ], "importsMe": [ "RforProteomics" ] }, "Rqc": { "Package": "Rqc", "Version": "1.8.0", "Depends": [ "BiocParallel", "ShortRead", "ggplot2" ], "Imports": [ "BiocGenerics", "Biostrings", "IRanges", "methods", "S4Vectors", "knitr (>= 1.7)", "BiocStyle", "plyr", "markdown", "grid", "reshape2", "digest", "Rcpp (>= 0.11.6)", "biovizBase", "shiny", "Rsamtools", "GenomicAlignments", "GenomicFiles" ], "LinkingTo": [ "Rcpp" ], "Suggests": [ "testthat" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "82465dc0ed9fdc82684e11c477b6f4cc", "NeedsCompilation": "yes", "Title": "Quality Control Tool for High-Throughput Sequencing Data", "Description": "Rqc is an optimised tool designed for quality control and assessment of high-throughput sequencing data. It performs parallel processing of entire files and produces a report which contains a set of high-resolution graphics.", "biocViews": [ "DataImport", "QualityControl", "Sequencing", "Software" ], "Author": "Welliton Souza, Benilton Carvalho ", "Maintainer": "Welliton Souza ", "URL": "https://github.com/labbcb/Rqc", "VignetteBuilder": "knitr", "source.ver": "src/contrib/Rqc_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Rqc_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Rqc_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Rqc_1.8.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Rqc/inst/doc/Rqc.R" ], "htmlDocs": [ "vignettes/Rqc/inst/doc/Rqc.html" ], "htmlTitles": [ "Using Rqc" ] }, "rqubic": { "Package": "rqubic", "Version": "1.20.0", "Imports": [ "methods", "Biobase", "BiocGenerics", "biclust" ], "Suggests": [ "RColorBrewer" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "b186c4b98bed632104f4cf2506227dbe", "NeedsCompilation": "yes", "Title": "Qualitative biclustering algorithm for expression data analysis in R", "Description": "This package implements the QUBIC algorithm introduced by Li et al. for the qualitative biclustering with gene expression data.", "biocViews": [ "Clustering", "Microarray", "Software" ], "Author": "Jitao David Zhang, with inputs from Laura Badi and Martin Ebeling", "Maintainer": "Jitao David Zhang ", "source.ver": "src/contrib/rqubic_1.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/rqubic_1.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/rqubic_1.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/rqubic_1.20.0.tgz", "vignettes": [ "vignettes/rqubic/inst/doc/rqubic.pdf" ], "vignetteTitles": [ "Qualitative Biclustering with Bioconductor Package rqubic" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/rqubic/inst/doc/rqubic.R" ] }, "rRDP": { "Package": "rRDP", "Version": "1.8.0", "Depends": [ "Biostrings (>= 2.26.2)" ], "Suggests": [ "rRDPData" ], "License": "GPL-2 | file LICENSE", "MD5sum": "b392f51cc676ab4f350ab70691667869", "NeedsCompilation": "no", "Title": "Interface to the RDP Classifier", "Description": "Seamlessly interfaces RDP classifier (version 2.9).", "biocViews": [ "Classification", "Genetics", "Infrastructure", "Microbiome", "Sequencing", "Software" ], "Author": "Michael Hahsler, Anurag Nagar", "Maintainer": "Michael Hahsler ", "SystemRequirements": "Java", "source.ver": "src/contrib/rRDP_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/rRDP_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/rRDP_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/rRDP_1.8.0.tgz", "vignettes": [ "vignettes/rRDP/inst/doc/rRDP.pdf" ], "vignetteTitles": [ "rRDP: Interface to the RDP Classifier" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/rRDP/inst/doc/rRDP.R" ], "dependsOnMe": [ "rRDPData" ] }, "RRHO": { "Package": "RRHO", "Version": "1.14.0", "Depends": [ "R (>= 2.10)", "grid" ], "Imports": [ "VennDiagram" ], "Suggests": [ "lattice" ], "License": "GPL-2", "MD5sum": "5f4e0c293bd7e6125cc7ed49f0405f87", "NeedsCompilation": "no", "Title": "Inference on agreement between ordered lists", "Description": "The package is aimed at inference on the amount of agreement in two sorted lists using the Rank-Rank Hypergeometric Overlap test.", "biocViews": [ "Genetics", "Microarray", "SequenceMatching", "Software", "Transcription" ], "Author": "Jonathan Rosenblatt and Jason Stein", "Maintainer": "Jonathan Rosenblatt ", "source.ver": "src/contrib/RRHO_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RRHO_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RRHO_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RRHO_1.14.0.tgz", "vignettes": [ "vignettes/RRHO/inst/doc/RRHO.pdf" ], "vignetteTitles": [ "RRHO" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RRHO/inst/doc/RRHO.R" ] }, "Rsamtools": { "Package": "Rsamtools", "Version": "1.26.2", "Depends": [ "methods", "GenomeInfoDb (>= 1.1.3)", "GenomicRanges (>= 1.21.6)", "Biostrings (>= 2.37.1)" ], "Imports": [ "utils", "BiocGenerics (>= 0.1.3)", "S4Vectors (>= 0.7.11)", "IRanges (>= 2.3.7)", "XVector (>= 0.9.1)", "zlibbioc", "bitops", "BiocParallel" ], "LinkingTo": [ "S4Vectors", "IRanges", "XVector", "Biostrings" ], "Suggests": [ "GenomicAlignments", "ShortRead (>= 1.19.10)", "GenomicFeatures", "TxDb.Dmelanogaster.UCSC.dm3.ensGene", "KEGG.db", "TxDb.Hsapiens.UCSC.hg18.knownGene", "RNAseqData.HNRNPC.bam.chr14", "BSgenome.Hsapiens.UCSC.hg19", "pasillaBamSubset", "RUnit", "BiocStyle" ], "License": "Artistic-2.0 | file LICENSE", "Archs": "i386, x64", "MD5sum": "57f272df193b7252d90860170efb74b5", "NeedsCompilation": "yes", "Title": "Binary alignment (BAM), FASTA, variant call (BCF), and tabix file import", "Description": "This package provides an interface to the 'samtools', 'bcftools', and 'tabix' utilities (see 'LICENCE') for manipulating SAM (Sequence Alignment / Map), FASTA, binary variant call (BCF) and compressed indexed tab-delimited (tabix) files.", "biocViews": [ "Alignment", "Coverage", "DataImport", "QualityControl", "Sequencing", "Software" ], "Author": "Martin Morgan, Herv\\'e Pag\\`es, Valerie Obenchain, Nathaniel Hayden", "Maintainer": "Bioconductor Package Maintainer ", "URL": "http://bioconductor.org/packages/release/bioc/html/Rsamtools.html", "Video": "https://www.youtube.com/watch?v=Rfon-DQYbWA&list=UUqaMSQd_h-2EDGsU6WDiX0Q", "source.ver": "src/contrib/Rsamtools_1.26.2.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Rsamtools_1.26.2.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Rsamtools_1.26.2.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Rsamtools_1.26.2.tgz", "vignettes": [ "vignettes/Rsamtools/inst/doc/Rsamtools-Overview.pdf", "vignettes/Rsamtools/inst/doc/Rsamtools-UsingCLibraries.pdf" ], "vignetteTitles": [ "An introduction to Rsamtools", "Using samtools C libraries" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/Rsamtools/inst/doc/Rsamtools-Overview.R", "vignettes/Rsamtools/inst/doc/Rsamtools-UsingCLibraries.R" ], "dependsOnMe": [ "ArrayExpressHTS", "BaalChIP", "BitSeq", "chimera", "CODEX", "contiBAIT", "CoverageView", "exomeCopy", "exomePeak", "GenoGAM", "GenomicAlignments", "GenomicFiles", "girafe", "gmapR", "Guitar", "HelloRanges", "leeBamViews", "MEDIPS", "methylPipe", "MMDiff2", "oneChannelGUI", "podkat", "qrqc", "r3Cseq", "Rcade", "ReQON", "rfPred", "RIPSeeker", "rnaSeqMap", "SGSeq", "ShortRead", "SICtools", "SNPhood", "ssviz", "systemPipeR", "TarSeqQC", "TBX20BamSubset", "TEQC", "TitanCNA", "VariantAnnotation", "wavClusteR" ], "importsMe": [ "AllelicImbalance", "alpine", "AneuFinder", "annmap", "AnnotationHubData", "ArrayExpressHTS", "BadRegionFinder", "BBCAnalyzer", "biovizBase", "BSgenome", "CAGEr", "casper", "CexoR", "ChIPComp", "ChIPpeakAnno", "ChIPQC", "chromstaR", "cn.mops", "CNVPanelizer", "CNVrd2", "compEpiTools", "CopywriteR", "CrispRVariants", "csaw", "customProDB", "derfinder", "DEXSeq", "DiffBind", "diffHic", "DOQTL", "easyRNASeq", "EDASeq", "ensembldb", "epigenomix", "eudysbiome", "FourCSeq", "FunChIP", "FunciSNP", "GeneGeneInteR", "genomation", "GenomicAlignments", "GenomicInteractions", "GenVisR", "ggbio", "GGtools", "GoogleGenomics", "GOTHiC", "GreyListChIP", "GUIDEseq", "Gviz", "gwascat", "h5vc", "HTSeqGenie", "INSPEcT", "LungCancerLines", "MADSEQ", "MafDb.ESP6500SI.V2.SSA137", "maftools", "metagene", "methylKit", "mosaics", "nucleR", "PGA", "PICS", "PureCN", "QDNAseq", "qsea", "QuasR", "R453Plus1Toolbox", "Rariant", "Repitools", "RiboProfiling", "riboSeqR", "RNAprobR", "Rqc", "rtracklayer", "segmentSeq", "similaRpeak", "soGGi", "SplicingGraphs", "tracktables", "trackViewer", "transcriptR", "TransView", "TVTB", "VariantFiltering", "VariantTools" ], "suggestsMe": [ "AnnotationHub", "bamsignals", "BaseSpaceR", "BiocParallel", "biomvRCNS", "Chicago", "gage", "GenomeInfoDb", "GenomicFeatures", "GenomicRanges", "GeuvadisTranscriptExpr", "gQTLstats", "metaseqR", "parathyroidSE", "recoup", "RnaSeqTutorial", "seqbias", "SigFuge", "Streamer" ] }, "rsbml": { "Package": "rsbml", "Version": "2.32.0", "Depends": [ "R (>= 2.6.0)", "BiocGenerics (>= 0.3.2)", "methods", "utils" ], "Imports": [ "BiocGenerics", "graph", "utils" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "6554f15f6563d0fd65b37c9359098dde", "NeedsCompilation": "yes", "Title": "R support for SBML, using libsbml", "Description": "Links R to libsbml for SBML parsing, validating output, provides an S4 SBML DOM, converts SBML to R graph objects. Optionally links to the SBML ODE Solver Library (SOSLib) for simulating models.", "biocViews": [ "GraphAndNetwork", "Network", "Pathways", "Software" ], "Author": "Michael Lawrence ", "Maintainer": "Michael Lawrence ", "URL": "http://www.sbml.org", "SystemRequirements": "libsbml (==5.10.2)", "source.ver": "src/contrib/rsbml_2.32.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/rsbml_2.32.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/rsbml_2.32.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/rsbml_2.32.0.tgz", "vignettes": [ "vignettes/rsbml/inst/doc/quick-start.pdf" ], "vignetteTitles": [ "Quick start for rsbml" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": true, "hasLICENSE": false, "Rfiles": [ "vignettes/rsbml/inst/doc/quick-start.R" ], "dependsOnMe": [ "BiGGR" ], "suggestsMe": [ "piano", "SBMLR" ] }, "rSFFreader": { "Package": "rSFFreader", "Version": "0.22.0", "Depends": [ "ShortRead (>= 1.23.17)" ], "Imports": [ "methods", "Biostrings", "IRanges" ], "LinkingTo": [ "S4Vectors", "IRanges", "XVector", "Biostrings" ], "Suggests": [ "xtable" ], "License": "Artistic-2.0", "MD5sum": "a7b2fe2b7cd14a16be2b051a5371f001", "NeedsCompilation": "yes", "Title": "rSFFreader reads in sff files generated by Roche 454 and Life Sciences Ion Torrent sequencers", "Description": "rSFFreader reads sequence, qualities and clip point values from sff files generated by Roche 454 and Life Sciences Ion Torrent sequencers into similar classes as are present for fastq files.", "biocViews": [ "DataImport", "Sequencing", "Software" ], "Author": "Matt Settles , Sam Hunter, Brice Sarver, Ilia Zhbannikov, Kyu-Chul Cho", "Maintainer": "Matt Settles ", "source.ver": "src/contrib/rSFFreader_0.22.0.tar.gz", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/rSFFreader_0.22.0.tgz", "vignettes": [ "vignettes/rSFFreader/inst/doc/rSFFreader.pdf" ], "vignetteTitles": [ "An introduction to rSFFreader" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/rSFFreader/inst/doc/rSFFreader.R" ], "importsMe": [ "hiReadsProcessor" ] }, "Rsubread": { "Package": "Rsubread", "Version": "1.24.2", "License": "GPL-3", "MD5sum": "5e2485502268daa7404b1d8b9d2443bb", "NeedsCompilation": "yes", "Title": "Subread sequence alignment for R", "Description": "Provides powerful and easy-to-use tools for analyzing next-gen sequencing read data. Includes quality assessment of sequence reads, read alignment, read summarization, exon-exon junction detection, fusion detection, detection of short and long indels, absolute expression calling and SNP calling. Can be used with reads generated from any of the major sequencing platforms including Illumina GA/HiSeq/MiSeq, Roche GS-FLX, ABI SOLiD and LifeTech Ion PGM/Proton sequencers.", "biocViews": [ "Alignment", "ChIPSeq", "GeneExpression", "GeneRegulation", "GeneticVariability", "Genetics", "GenomeAnnotation", "Preprocessing", "QualityControl", "RNASeq", "SNP", "SequenceMatching", "Sequencing", "Software" ], "Author": "Wei Shi and Yang Liao with contributions from Gordon Smyth, Jenny Dai and Timothy Triche, Jr.", "Maintainer": "Wei Shi ", "URL": "http://bioconductor.org/packages/release/bioc/html/Rsubread.html", "source.ver": "src/contrib/Rsubread_1.24.2.tar.gz", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Rsubread_1.24.2.tgz", "vignettes": [ "vignettes/Rsubread/inst/doc/Rsubread.pdf" ], "vignetteTitles": [ "Rsubread Vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Rsubread/inst/doc/Rsubread.R" ], "importsMe": [ "dupRadar" ] }, "RSVSim": { "Package": "RSVSim", "Version": "1.14.0", "Depends": [ "R (>= 3.0.0)", "Biostrings", "GenomicRanges" ], "Imports": [ "methods", "IRanges", "ShortRead" ], "Suggests": [ "BSgenome.Hsapiens.UCSC.hg19", "BSgenome.Hsapiens.UCSC.hg19.masked", "MASS", "rtracklayer" ], "License": "LGPL-3", "MD5sum": "08651d08ec44da9eb93bd2da01f4489d", "NeedsCompilation": "no", "Title": "RSVSim: an R/Bioconductor package for the simulation of structural variations", "Description": "RSVSim is a package for the simulation of deletions, insertions, inversion, tandem-duplications and translocations of various sizes in any genome available as FASTA-file or BSgenome data package. SV breakpoints can be placed uniformly accross the whole genome, with a bias towards repeat regions and regions of high homology (for hg19) or at user-supplied coordinates.", "biocViews": [ "Sequencing", "Software" ], "Author": "Christoph Bartenhagen", "Maintainer": "Christoph Bartenhagen ", "source.ver": "src/contrib/RSVSim_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RSVSim_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RSVSim_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RSVSim_1.14.0.tgz", "vignettes": [ "vignettes/RSVSim/inst/doc/vignette.pdf" ], "vignetteTitles": [ "RSVSim: an R/Bioconductor package for the simulation of structural variations" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RSVSim/inst/doc/vignette.R" ] }, "rTANDEM": { "Package": "rTANDEM", "Version": "1.14.2", "Depends": [ "XML", "Rcpp", "data.table (>= 1.8.8)" ], "Imports": [ "methods" ], "LinkingTo": [ "Rcpp" ], "Suggests": [ "biomaRt" ], "License": "Artistic-1.0 | file LICENSE", "Archs": "i386, x64", "MD5sum": "0ec069add992e318de75437b7ff59aef", "NeedsCompilation": "yes", "Title": "Interfaces the tandem protein identification algorithm in R", "Description": "This package interfaces the tandem protein identification algorithm in R. Identification can be launched in the X!Tandem style, by using as sole parameter the path to a parameter file. But rTANDEM aslo provides extended syntax and functions to streamline launching analyses, as well as function to convert results, parameters and taxonomy to/from R. A related package, shinyTANDEM, provides visualization interface for result objects.", "biocViews": [ "MassSpectrometry", "Proteomics", "Software" ], "Author": "Frederic Fournier , Charles Joly Beauparlant , Rene Paradis , Arnaud Droit ", "Maintainer": "Frederic Fournier ", "SystemRequirements": "rTANDEM uses expat and pthread libraries. See the README file for details.", "source.ver": "src/contrib/rTANDEM_1.14.2.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/rTANDEM_1.14.2.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/rTANDEM_1.14.2.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/rTANDEM_1.14.2.tgz", "vignettes": [ "vignettes/rTANDEM/inst/doc/rTANDEM.pdf" ], "vignetteTitles": [ "The rTANDEM users guide" ], "hasREADME": true, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/rTANDEM/inst/doc/rTANDEM.R" ], "dependsOnMe": [ "PGA", "sapFinder", "shinyTANDEM" ], "importsMe": [ "proteoQC" ], "suggestsMe": [ "RforProteomics" ] }, "RTCA": { "Package": "RTCA", "Version": "1.26.0", "Depends": [ "methods", "stats", "graphics", "Biobase", "RColorBrewer", "gtools" ], "Suggests": [ "xtable" ], "License": "LGPL-3", "MD5sum": "9fbd86d7388dcd65a2e22895249e4ff1", "NeedsCompilation": "no", "Title": "Open-source toolkit to analyse data from xCELLigence System (RTCA)", "Description": "Import, analyze and visualize data from Roche(R) xCELLigence RTCA systems. The package imports real-time cell electrical impedance data into R. As an alternative to commercial software shipped along the system, the Bioconductor package RTCA provides several unique transformation (normalization) strategies and various visualization tools.", "biocViews": [ "CellBasedAssays", "Infrastructure", "Software", "TimeCourse", "Visualization" ], "Author": "Jitao David Zhang", "Maintainer": "Jitao David Zhang ", "URL": "http://code.google.com/p/xcelligence/,http://www.xcelligence.roche.com/,http://www.nextbiomotif.com/Home/scientific-programming", "source.ver": "src/contrib/RTCA_1.26.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RTCA_1.26.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RTCA_1.26.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RTCA_1.26.0.tgz", "vignettes": [ "vignettes/RTCA/inst/doc/aboutRTCA.pdf", "vignettes/RTCA/inst/doc/RTCAtransformation.pdf" ], "vignetteTitles": [ "Introduction to Data Analysis of the Roche xCELLigence System with RTCA Package", "RTCAtransformation: Discussion of transformation methods of RTCA data" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RTCA/inst/doc/aboutRTCA.R", "vignettes/RTCA/inst/doc/RTCAtransformation.R" ] }, "RTCGA": { "Package": "RTCGA", "Version": "1.4.0", "Depends": [ "R (>= 3.3.0)" ], "Imports": [ "XML", "assertthat", "stringi", "rvest", "data.table", "xml2", "dplyr", "purrr", "survival", "survminer", "ggplot2", "ggthemes", "viridis", "knitr", "scales" ], "Suggests": [ "devtools", "testthat", "pander", "Biobase", "GenomicRanges", "IRanges", "S4Vectors", "RTCGA.rnaseq", "RTCGA.clinical", "RTCGA.mutations", "RTCGA.RPPA", "RTCGA.mRNA", "RTCGA.miRNASeq", "RTCGA.methylation", "RTCGA.CNV", "RTCGA.PANCAN12", "magrittr", "tidyr" ], "License": "GPL-2", "MD5sum": "bed45d2ee1409741f737e313b6d34455", "NeedsCompilation": "no", "Title": "The Cancer Genome Atlas Data Integration", "Description": "The Cancer Genome Atlas (TCGA) Data Portal provides a platform for researchers to search, download, and analyze data sets generated by TCGA. It contains clinical information, genomic characterization data, and high level sequence analysis of the tumor genomes. The key is to understand genomics to improve cancer care. RTCGA package offers download and integration of the variety and volume of TCGA data using patient barcode key, what enables easier data possession. This may have an benefcial infuence on impact on development of science and improvement of patients' treatment. Furthermore, RTCGA package transforms TCGA data to tidy form which is convenient to use.", "biocViews": [ "DataImport", "DataRepresentation", "Preprocessing", "RNASeq", "Software" ], "Author": "Marcin Kosinski , Przemyslaw Biecek ", "Maintainer": "Marcin Kosinski ", "URL": "https://rtcga.github.io/RTCGA", "VignetteBuilder": "knitr", "BugReports": "https://github.com/RTCGA/RTCGA/issues", "source.ver": "src/contrib/RTCGA_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RTCGA_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RTCGA_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RTCGA_1.4.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "htmlDocs": [ "vignettes/RTCGA/inst/doc/RTCGA_Workflow.html" ], "htmlTitles": [ "Integrating TCGA Data - RTCGA Workflow" ], "dependsOnMe": [ "RTCGA.clinical", "RTCGA.CNV", "RTCGA.methylation", "RTCGA.miRNASeq", "RTCGA.mRNA", "RTCGA.mutations", "RTCGA.PANCAN12", "RTCGA.rnaseq", "RTCGA.RPPA" ] }, "RTCGAToolbox": { "Package": "RTCGAToolbox", "Version": "2.4.0", "Depends": [ "R (>= 3.2.0)" ], "Imports": [ "methods", "XML", "limma (>= 3.18)", "survival", "RCircos", "data.table (>= 1.9.4)", "RCurl", "RJSONIO" ], "Suggests": [ "BiocStyle", "knitr", "rmarkdown", "Homo.sapiens" ], "License": "GPL (>= 2)", "MD5sum": "e03f9e9c1fbc9f7090a259f942b21d15", "NeedsCompilation": "no", "Title": "A new tool for exporting TCGA Firehose data", "Description": "Managing data from large scale projects such as The Cancer Genome Atlas (TCGA) for further analysis is an important and time consuming step for research projects. Several efforts, such as Firehose project, make TCGA pre-processed data publicly available via web services and data portals but it requires managing, downloading and preparing the data for following steps. We developed an open source and extensible R based data client for Firehose pre-processed data and demonstrated its use with sample case studies. Results showed that RTCGAToolbox could improve data management for researchers who are interested with TCGA data. In addition, it can be integrated with other analysis pipelines for following data analysis.", "biocViews": [ "DifferentialExpression", "GeneExpression", "Sequencing", "Software" ], "Author": "Mehmet Kemal Samur", "Maintainer": "Mehmet Kemal Samur ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/RTCGAToolbox_2.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RTCGAToolbox_2.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RTCGAToolbox_2.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RTCGAToolbox_2.4.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/RTCGAToolbox/inst/doc/RTCGAToolbox-vignette.R" ], "htmlDocs": [ "vignettes/RTCGAToolbox/inst/doc/RTCGAToolbox-vignette.html" ], "htmlTitles": [ "Vignette Title" ] }, "RTN": { "Package": "RTN", "Version": "1.12.0", "Depends": [ "R (>= 2.15)", "methods", "igraph" ], "Imports": [ "RedeR", "minet", "snow", "limma", "data.table", "ff", "car", "IRanges" ], "Suggests": [ "HTSanalyzeR", "RUnit", "BiocGenerics" ], "License": "Artistic-2.0", "MD5sum": "8396a5cba75ec897b08670b58448703e", "NeedsCompilation": "no", "Title": "Reconstruction of transcriptional networks and analysis of master regulators", "Description": "This package provides classes and methods for transcriptional network inference and analysis. Modulators of transcription factor activity are assessed by conditional mutual information, and master regulators are mapped to phenotypes using different strategies, e.g., gene set enrichment, shadow and synergy analyses. Additionally, master regulators can be linked to genetic markers using eQTL/VSE analysis, taking advantage of the haplotype block structure mapped to the human genome in order to explore risk-associated SNPs identified in GWAS studies.", "biocViews": [ "GeneExpression", "GeneRegulation", "GeneSetEnrichment", "GeneticVariability", "GraphAndNetwork", "NetworkAnalysis", "NetworkEnrichment", "NetworkInference", "SNP", "Software" ], "Author": "Mauro Castro, Xin Wang, Michael Fletcher, Florian Markowetz and Kerstin Meyer", "Maintainer": "Mauro Castro ", "URL": "http://dx.doi.org/10.1038/ncomms3464", "source.ver": "src/contrib/RTN_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RTN_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RTN_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RTN_1.12.0.tgz", "vignettes": [ "vignettes/RTN/inst/doc/RTN.pdf" ], "vignetteTitles": [ "Main vignette: reconstruction and analysis of transcriptional networks in R" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RTN/inst/doc/RTN.R" ], "dependsOnMe": [ "Fletcher2013b" ] }, "RTopper": { "Package": "RTopper", "Version": "1.20.0", "Depends": [ "R (>= 2.11.0)", "Biobase" ], "Imports": [ "limma", "multtest" ], "Suggests": [ "limma", "org.Hs.eg.db", "KEGG.db", "GO.db" ], "License": "GPL (>= 3)", "MD5sum": "598f72d6a8a7defbbb1d2775c0cf7d5e", "NeedsCompilation": "no", "Title": "This package is designed to perform Gene Set Analysis across multiple genomic platforms", "Description": "the RTopper package is designed to perform and integrate gene set enrichment results across multiple genomic platforms.", "biocViews": [ "Microarray", "Software" ], "Author": "Luigi Marchionni , Svitlana Tyekucheva ", "Maintainer": "Luigi Marchionni ", "source.ver": "src/contrib/RTopper_1.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RTopper_1.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RTopper_1.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RTopper_1.20.0.tgz", "vignettes": [ "vignettes/RTopper/inst/doc/RTopper.pdf" ], "vignetteTitles": [ "RTopper user's manual" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/RTopper/inst/doc/RTopper.R" ] }, "rtracklayer": { "Package": "rtracklayer", "Version": "1.34.2", "Depends": [ "R (>= 3.3)", "methods", "GenomicRanges (>= 1.21.20)" ], "Imports": [ "XML (>= 1.98-0)", "BiocGenerics (>= 0.13.8)", "S4Vectors (>= 0.9.33)", "IRanges (>= 2.3.7)", "XVector (>= 0.9.4)", "GenomeInfoDb (>= 1.3.14)", "Biostrings (>= 2.37.1)", "zlibbioc", "RCurl (>= 1.4-2)", "Rsamtools (>= 1.17.8)", "GenomicAlignments (>= 1.5.4)", "tools" ], "LinkingTo": [ "S4Vectors", "IRanges", "XVector" ], "Suggests": [ "BSgenome (>= 1.33.4)", "humanStemCell", "microRNA (>= 1.1.1)", "genefilter", "limma", "org.Hs.eg.db", "hgu133plus2.db", "BSgenome.Hsapiens.UCSC.hg19", "TxDb.Hsapiens.UCSC.hg19.knownGene" ], "License": "Artistic-2.0 + file LICENSE", "Archs": "i386, x64", "MD5sum": "f631b7060bd3b397e5e938bb0af94f22", "NeedsCompilation": "yes", "Title": "R interface to genome browsers and their annotation tracks", "Description": "Extensible framework for interacting with multiple genome browsers (currently UCSC built-in) and manipulating annotation tracks in various formats (currently GFF, BED, bedGraph, BED15, WIG, BigWig and 2bit built-in). The user may export/import tracks to/from the supported browsers, as well as query and modify the browser state, such as the current viewport.", "biocViews": [ "Annotation", "DataImport", "Software", "Visualization" ], "Author": "Michael Lawrence, Vince Carey, Robert Gentleman", "Maintainer": "Michael Lawrence ", "source.ver": "src/contrib/rtracklayer_1.34.2.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/rtracklayer_1.34.2.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/rtracklayer_1.34.2.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/rtracklayer_1.34.2.tgz", "vignettes": [ "vignettes/rtracklayer/inst/doc/rtracklayer.pdf" ], "vignetteTitles": [ "rtracklayer" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/rtracklayer/inst/doc/rtracklayer.R" ], "dependsOnMe": [ "BSgenome", "ChIPComp", "CoverageView", "cummeRbund", "EatonEtAlChIPseq", "exomePeak", "geneXtendeR", "GenomicFiles", "groHMM", "Guitar", "HelloRanges", "IdeoViz", "MethylSeekR", "r3Cseq", "regioneR", "RIPSeeker", "spliceR" ], "importsMe": [ "AnnotationHubData", "annotatr", "ballgown", "BiSeq", "BSgenome", "CAGEr", "casper", "CexoR", "ChIPseeker", "ChromHeatMap", "CNEr", "coMET", "CompGO", "consensusSeekeR", "contiBAIT", "conumee", "customProDB", "DeepBlueR", "derfinder", "diffloop", "ensembldb", "erma", "FourCSeq", "FunciSNP", "FunciSNP.data", "genbankr", "geneAttribution", "geneLenDataBase", "genomation", "GenomicFeatures", "GenomicInteractions", "genotypeeval", "ggbio", "GGtools", "gmapR", "GOTHiC", "gQTLBase", "GreyListChIP", "Gviz", "gwascat", "hiAnnotator", "HiTC", "HTSeqGenie", "MADSEQ", "MEDIPS", "metagene", "methyAnalysis", "methylKit", "motifbreakR", "MotifDb", "normr", "Pbase", "PGA", "proBAMr", "qsea", "QuasR", "RCAS", "recount", "recoup", "regioneR", "Repitools", "RiboProfiling", "RNAprobR", "roar", "seqplots", "SGSeq", "similaRpeak", "soGGi", "SVM2CRM", "TFBSTools", "trackViewer", "transcriptR", "VariantAnnotation", "VariantTools", "wavClusteR" ], "suggestsMe": [ "alpine", "AnnotationHub", "biovizBase", "ChIPpeakAnno", "CINdex", "compEpiTools", "CrispRVariants", "dsQTL", "FDb.FANTOM4.promoters.hg19", "GenomicAlignments", "GenomicRanges", "GeuvadisTranscriptExpr", "goseq", "InPAS", "interactiveDisplay", "metaseqR", "methylumi", "MotIV", "MutationalPatterns", "NarrowPeaks", "oneChannelGUI", "OrganismDbi", "PasillaTranscriptExpr", "PICS", "PING", "pqsfinder", "PureCN", "R453Plus1Toolbox", "Ringo", "rMAT", "RnBeads", "RSVSim", "signeR", "triplex", "TSSi", "TVTB" ] }, "Rtreemix": { "Package": "Rtreemix", "Version": "1.36.0", "Depends": [ "R (>= 2.5.0)" ], "Imports": [ "methods", "graph", "Biobase", "Hmisc" ], "Suggests": [ "Rgraphviz" ], "License": "LGPL", "Archs": "i386, x64", "MD5sum": "a683e28989c5abdb2d044f64bac7cebe", "NeedsCompilation": "yes", "Title": "Rtreemix: Mutagenetic trees mixture models.", "Description": "Rtreemix is a package that offers an environment for estimating the mutagenetic trees mixture models from cross-sectional data and using them for various predictions. It includes functions for fitting the trees mixture models, likelihood computations, model comparisons, waiting time estimations, stability analysis, etc.", "biocViews": [ "Software", "StatisticalMethod" ], "Author": "Jasmina Bogojeska", "Maintainer": "Jasmina Bogojeska ", "source.ver": "src/contrib/Rtreemix_1.36.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Rtreemix_1.36.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Rtreemix_1.36.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Rtreemix_1.36.0.tgz", "vignettes": [ "vignettes/Rtreemix/inst/doc/Rtreemix.pdf" ], "vignetteTitles": [ "Rtreemix" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Rtreemix/inst/doc/Rtreemix.R" ] }, "rTRM": { "Package": "rTRM", "Version": "1.12.0", "Depends": [ "R (>= 2.10)", "igraph (>= 1.0)" ], "Imports": [ "AnnotationDbi", "DBI", "RSQLite" ], "Suggests": [ "RUnit", "BiocGenerics", "MotifDb", "graph", "PWMEnrich", "biomaRt", "knitr", "Biostrings", "BSgenome.Mmusculus.UCSC.mm8.masked", "org.Hs.eg.db", "org.Mm.eg.db", "ggplot2" ], "License": "GPL-3", "MD5sum": "7ec063219a9b776dc48b5b6b9b0bb3bc", "NeedsCompilation": "no", "Title": "Identification of transcriptional regulatory modules from PPI networks", "Description": "rTRM identifies transcriptional regulatory modules (TRMs) from protein-protein interaction networks.", "biocViews": [ "GeneRegulation", "GraphAndNetwork", "Network", "Software", "Transcription" ], "Author": "Diego Diez", "Maintainer": "Diego Diez ", "URL": "https://github.com/ddiez/rTRM", "VignetteBuilder": "knitr", "BugReports": "https://github.com/ddiez/rTRM/issues", "source.ver": "src/contrib/rTRM_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/rTRM_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/rTRM_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/rTRM_1.12.0.tgz", "vignettes": [ "vignettes/rTRM/inst/doc/rTRM_Introduction.pdf" ], "vignetteTitles": [ "Introduction to rTRM" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/rTRM/inst/doc/rTRM_Introduction.R" ], "importsMe": [ "rTRMui" ] }, "rTRMui": { "Package": "rTRMui", "Version": "1.12.0", "Imports": [ "shiny (>= 0.9)", "rTRM", "MotifDb", "org.Hs.eg.db", "org.Mm.eg.db" ], "License": "GPL-3", "MD5sum": "92e4c1c86212a1497e4a4b999e309349", "NeedsCompilation": "no", "Title": "A shiny user interface for rTRM", "Description": "This package provides a web interface to compute transcriptional regulatory modules with rTRM.", "biocViews": [ "GUI", "GeneRegulation", "GraphAndNetwork", "Network", "Software", "Transcription" ], "Author": "Diego Diez", "Maintainer": "Diego Diez ", "URL": "https://github.com/ddiez/rTRMui", "BugReports": "https://github.com/ddiez/rTRMui/issues", "source.ver": "src/contrib/rTRMui_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/rTRMui_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/rTRMui_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/rTRMui_1.12.0.tgz", "vignettes": [ "vignettes/rTRMui/inst/doc/rTRMui.pdf" ], "vignetteTitles": [ "Introduction to rTRMui" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/rTRMui/inst/doc/rTRMui.R" ] }, "RUVcorr": { "Package": "RUVcorr", "Version": "1.6.0", "Imports": [ "corrplot", "MASS", "stats", "lattice", "grDevices", "gridExtra", "snowfall", "psych", "BiocParallel", "grid", "bladderbatch", "reshape2" ], "Suggests": [ "knitr", "BiocStyle", "hgu133a2.db" ], "License": "GPL-2", "MD5sum": "923f0a218fba54fb99935aedc813510a", "NeedsCompilation": "no", "Title": "Removal of unwanted variation for gene-gene correlations and related analysis", "Description": "RUVcorr allows to apply global removal of unwanted variation (ridged version of RUV) to real and simulated gene expression data.", "biocViews": [ "GeneExpression", "Normalization", "Software" ], "Author": "Saskia Freytag", "Maintainer": "Saskia Freytag ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/RUVcorr_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RUVcorr_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RUVcorr_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RUVcorr_1.6.0.tgz", "vignettes": [ "vignettes/RUVcorr/inst/doc/RUVcorrVignetteNew.pdf" ], "vignetteTitles": [ "RUVcorr" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RUVcorr/inst/doc/RUVcorrVignetteNew.R" ] }, "RUVnormalize": { "Package": "RUVnormalize", "Version": "1.8.0", "Depends": [ "R (>= 2.10.0)" ], "Imports": [ "RUVnormalizeData", "Biobase" ], "Enhances": [ "spams" ], "License": "GPL-3", "MD5sum": "30b5ecfe60231cbf74e06dc13f9691a2", "NeedsCompilation": "no", "Title": "RUV for normalization of expression array data", "Description": "RUVnormalize is meant to remove unwanted variation from gene expression data when the factor of interest is not defined, e.g., to clean up a dataset for general use or to do any kind of unsupervised analysis.", "biocViews": [ "Normalization", "Software", "StatisticalMethod" ], "Author": "Laurent Jacob", "Maintainer": "Laurent Jacob ", "source.ver": "src/contrib/RUVnormalize_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RUVnormalize_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RUVnormalize_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RUVnormalize_1.8.0.tgz", "vignettes": [ "vignettes/RUVnormalize/inst/doc/RUVnormalize.pdf" ], "vignetteTitles": [ "RUVnormalize" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RUVnormalize/inst/doc/RUVnormalize.R" ] }, "RUVSeq": { "Package": "RUVSeq", "Version": "1.8.0", "Depends": [ "Biobase", "EDASeq (>= 1.99.1)", "edgeR" ], "Imports": [ "methods", "MASS" ], "Suggests": [ "BiocStyle", "knitr", "RColorBrewer", "zebrafishRNASeq", "DESeq2" ], "License": "Artistic-2.0", "MD5sum": "41142c2fbb6a7ac6de80ab8b93646595", "NeedsCompilation": "no", "Title": "Remove Unwanted Variation from RNA-Seq Data", "Description": "This package implements the remove unwanted variation (RUV) methods of Risso et al. (2014) for the normalization of RNA-Seq read counts between samples.", "biocViews": [ "DifferentialExpression", "Preprocessing", "RNASeq", "Software" ], "Author": "Davide Risso [aut, cre, cph], Sandrine Dudoit [aut], Lorena Pantano [ctb], Kamil Slowikowski [ctb]", "Maintainer": "Davide Risso ", "URL": "https://github.com/drisso/RUVSeq", "VignetteBuilder": "knitr", "BugReports": "https://github.com/drisso/RUVSeq/issues", "source.ver": "src/contrib/RUVSeq_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/RUVSeq_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/RUVSeq_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/RUVSeq_1.8.0.tgz", "vignettes": [ "vignettes/RUVSeq/inst/doc/RUVSeq.pdf" ], "vignetteTitles": [ "RUVSeq: Remove Unwanted Variation from RNA-Seq Data" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/RUVSeq/inst/doc/RUVSeq.R" ] }, "S4Vectors": { "Package": "S4Vectors", "Version": "0.12.2", "Depends": [ "R (>= 3.3.0)", "methods", "utils", "stats", "stats4", "BiocGenerics (>= 0.15.10)" ], "Suggests": [ "IRanges", "GenomicRanges", "Matrix", "ShortRead", "graph", "data.table", "RUnit" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "df48bd8a07a23fc72a0401173d2a8167", "NeedsCompilation": "yes", "Title": "S4 implementation of vectors and lists", "Description": "The S4Vectors package defines the Vector and List virtual classes and a set of generic functions that extend the semantic of ordinary vectors and lists in R. Package developers can easily implement vector-like or list-like objects as concrete subclasses of Vector or List. In addition, a few low-level concrete subclasses of general interest (e.g. DataFrame, Rle, and Hits) are implemented in the S4Vectors package itself (many more are implemented in the IRanges package and in other Bioconductor infrastructure packages).", "biocViews": [ "DataRepresentation", "Infrastructure", "Software" ], "Author": "H. Pagès, M. Lawrence and P. Aboyoun", "Maintainer": "Bioconductor Package Maintainer ", "source.ver": "src/contrib/S4Vectors_0.12.2.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/S4Vectors_0.12.2.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/S4Vectors_0.12.2.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/S4Vectors_0.12.2.tgz", "vignettes": [ "vignettes/S4Vectors/inst/doc/RleTricks.pdf", "vignettes/S4Vectors/inst/doc/S4QuickOverview.pdf" ], "vignetteTitles": [ "Rle Tips and Tricks", "A quick overview of the S4 class system" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/S4Vectors/inst/doc/RleTricks.R", "vignettes/S4Vectors/inst/doc/S4QuickOverview.R" ], "dependsOnMe": [ "altcdfenvs", "AnnotationHubData", "ASpli", "Biostrings", "BiSeq", "BSgenome", "bumphunter", "CellMapper", "CexoR", "ChIPComp", "ChIPpeakAnno", "chipseq", "ChIPseqR", "CODEX", "CSAR", "DESeq2", "DEXSeq", "DirichletMultinomial", "DMRcaller", "epigenomix", "ExperimentHubData", "ExpressionAtlas", "fCCAC", "GenomeInfoDb", "GenomicAlignments", "GenomicFeatures", "GenomicRanges", "GenomicTuples", "girafe", "groHMM", "Gviz", "HDF5Array", "HelloRanges", "htSeqTools", "InPAS", "IRanges", "isomiRs", "meshr", "MotifDb", "OTUbase", "pd.ag", "pd.aragene.1.0.st", "pd.aragene.1.1.st", "pd.ath1.121501", "pd.barley1", "pd.bovgene.1.0.st", "pd.bovgene.1.1.st", "pd.bovine", "pd.bsubtilis", "pd.cangene.1.0.st", "pd.cangene.1.1.st", "pd.canine", "pd.canine.2", "pd.celegans", "pd.chicken", "pd.chigene.1.0.st", "pd.chigene.1.1.st", "pd.chogene.2.0.st", "pd.chogene.2.1.st", "pd.citrus", "pd.clariom.d.human", "pd.clariom.s.human", "pd.clariom.s.human.ht", "pd.clariom.s.mouse", "pd.clariom.s.mouse.ht", "pd.clariom.s.rat", "pd.clariom.s.rat.ht", "pd.cotton", "pd.cyngene.1.0.st", "pd.cyngene.1.1.st", "pd.cyrgene.1.0.st", "pd.cyrgene.1.1.st", "pd.cytogenetics.array", "pd.drogene.1.0.st", "pd.drogene.1.1.st", "pd.drosgenome1", "pd.drosophila.2", "pd.e.coli.2", "pd.ecoli", "pd.ecoli.asv2", "pd.elegene.1.0.st", "pd.elegene.1.1.st", "pd.equgene.1.0.st", "pd.equgene.1.1.st", "pd.felgene.1.0.st", "pd.felgene.1.1.st", "pd.fingene.1.0.st", "pd.fingene.1.1.st", "pd.genomewidesnp.5", "pd.genomewidesnp.6", "pd.guigene.1.0.st", "pd.guigene.1.1.st", "pd.hc.g110", "pd.hg.focus", "pd.hg.u133.plus.2", "pd.hg.u133a", "pd.hg.u133a.2", "pd.hg.u133a.tag", "pd.hg.u133b", "pd.hg.u219", "pd.hg.u95a", "pd.hg.u95av2", "pd.hg.u95b", "pd.hg.u95c", "pd.hg.u95d", "pd.hg.u95e", "pd.hg18.60mer.expr", "pd.ht.hg.u133.plus.pm", "pd.ht.hg.u133a", "pd.ht.mg.430a", "pd.hta.2.0", "pd.hu6800", "pd.huex.1.0.st.v2", "pd.hugene.1.0.st.v1", "pd.hugene.1.1.st.v1", "pd.hugene.2.0.st", "pd.hugene.2.1.st", "pd.maize", "pd.mapping250k.nsp", "pd.mapping250k.sty", "pd.mapping50k.hind240", "pd.mapping50k.xba240", "pd.margene.1.0.st", "pd.margene.1.1.st", "pd.medgene.1.0.st", "pd.medgene.1.1.st", "pd.medicago", "pd.mg.u74a", "pd.mg.u74av2", "pd.mg.u74b", "pd.mg.u74bv2", "pd.mg.u74c", "pd.mg.u74cv2", "pd.mirna.1.0", "pd.mirna.2.0", "pd.mirna.3.0", "pd.mirna.4.0", "pd.moe430a", "pd.moe430b", "pd.moex.1.0.st.v1", "pd.mogene.1.0.st.v1", "pd.mogene.1.1.st.v1", "pd.mogene.2.0.st", "pd.mogene.2.1.st", "pd.mouse430.2", "pd.mouse430a.2", "pd.mta.1.0", "pd.mu11ksuba", "pd.mu11ksubb", "pd.nugo.hs1a520180", "pd.nugo.mm1a520177", "pd.ovigene.1.0.st", "pd.ovigene.1.1.st", "pd.pae.g1a", "pd.plasmodium.anopheles", "pd.poplar", "pd.porcine", "pd.porgene.1.0.st", "pd.porgene.1.1.st", "pd.rabgene.1.0.st", "pd.rabgene.1.1.st", "pd.rae230a", "pd.rae230b", "pd.raex.1.0.st.v1", "pd.ragene.1.0.st.v1", "pd.ragene.1.1.st.v1", "pd.ragene.2.0.st", "pd.ragene.2.1.st", "pd.rat230.2", "pd.rcngene.1.0.st", "pd.rcngene.1.1.st", "pd.rg.u34a", "pd.rg.u34b", "pd.rg.u34c", "pd.rhegene.1.0.st", "pd.rhegene.1.1.st", "pd.rhesus", "pd.rice", "pd.rjpgene.1.0.st", "pd.rjpgene.1.1.st", "pd.rn.u34", "pd.rta.1.0", "pd.rusgene.1.0.st", "pd.rusgene.1.1.st", "pd.s.aureus", "pd.soybean", "pd.soygene.1.0.st", "pd.soygene.1.1.st", "pd.sugar.cane", "pd.tomato", "pd.u133.x3p", "pd.vitis.vinifera", "pd.wheat", "pd.x.laevis.2", "pd.x.tropicalis", "pd.xenopus.laevis", "pd.yeast.2", "pd.yg.s98", "pd.zebgene.1.0.st", "pd.zebgene.1.1.st", "pd.zebrafish", "plethy", "RIPSeeker", "RnBeads", "segmentSeq", "SNPlocs.Hsapiens.dbSNP141.GRCh38", "triplex", "VariantTools", "XtraSNPlocs.Hsapiens.dbSNP141.GRCh38", "XVector" ], "importsMe": [ "affycoretools", "ALDEx2", "AllelicImbalance", "alpine", "AneuFinder", "AnnotationDbi", "AnnotationForge", "AnnotationHub", "annotatr", "ArrayTV", "BadRegionFinder", "ballgown", "BasicSTARRseq", "biovizBase", "BiSeq", "BitSeq", "BPRMeth", "BSgenome", "bsseq", "casper", "cgdv17", "chipenrich", "ChIPQC", "ChIPseeker", "chromstaR", "CINdex", "cleaver", "cn.mops", "CNEr", "CNPBayes", "CNVPanelizer", "coMET", "compEpiTools", "consensusSeekeR", "contiBAIT", "copynumber", "CopywriteR", "CoverageView", "CRISPRseek", "CrispRVariants", "csaw", "cummeRbund", "customProDB", "DChIPRep", "debrowser", "DECIPHER", "derfinder", "derfinderHelper", "derfinderPlot", "DiffBind", "diffHic", "diffloop", "DMRcate", "DOSE", "DRIMSeq", "easyRNASeq", "eegc", "ELMER", "EnrichmentBrowser", "ensembldb", "ensemblVEP", "epivizr", "epivizrData", "epivizrStandalone", "erma", "ExperimentHub", "facopy", "fastseg", "FindMyFriends", "FunciSNP", "genbankr", "genefilter", "GeneRegionScan", "GenoGAM", "genomation", "genomeIntervals", "GenomicAlignments", "GenomicFiles", "GenomicInteractions", "genoset", "GGBase", "ggbio", "GGtools", "gmapR", "GoogleGenomics", "GOpro", "GOTHiC", "gQTLBase", "gQTLstats", "GRmetrics", "GUIDEseq", "gwascat", "h5vc", "HTSeqGenie", "INSPEcT", "InteractionSet", "IVAS", "JunctionSeq", "kebabs", "LOLA", "M3D", "MADSEQ", "MAST", "matter", "MEAL", "methylKit", "methylPipe", "methylumi", "minfi", "MinimumDistance", "MiRaGE", "MMDiff2", "mosaics", "motifbreakR", "MotIV", "msa", "MSnbase", "MultiAssayExperiment", "MultiDataSet", "mygene", "myvariant", "NarrowPeaks", "nucleoSim", "nucleR", "oligoClasses", "OrganismDbi", "Pbase", "pcaExplorer", "pd.atdschip.tiling", "pdInfoBuilder", "PGA", "PICS", "PING", "polyester", "pqsfinder", "prebs", "procoil", "PureCN", "qcmetrics", "qpgraph", "QuasR", "R3CPET", "R453Plus1Toolbox", "RareVariantVis", "Rariant", "Rcade", "RCAS", "recount", "regionReport", "regsplice", "Repitools", "RiboProfiling", "RMassBank", "roar", "Rqc", "Rsamtools", "rtracklayer", "SeqArray", "seqplots", "SeqVarTools", "sevenbridges", "SGSeq", "ShortRead", "simulatorZ", "SMITE", "SNPchip", "SNPhood", "SNPlocs.Hsapiens.dbSNP.20100427", "SNPlocs.Hsapiens.dbSNP.20101109", "SNPlocs.Hsapiens.dbSNP.20110815", "SNPlocs.Hsapiens.dbSNP.20111119", "SNPlocs.Hsapiens.dbSNP141.GRCh38", "SNPlocs.Hsapiens.dbSNP144.GRCh37", "SNPlocs.Hsapiens.dbSNP144.GRCh38", "soGGi", "SomaticCancerAlterations", "SomaticSignatures", "SplicingGraphs", "SPLINTER", "STAN", "SummarizedExperiment", "TarSeqQC", "TCGAbiolinks", "TFBSTools", "trackViewer", "transcriptR", "TransView", "TSSi", "TVTB", "VanillaICE", "VariantAnnotation", "VariantFiltering", "wavClusteR", "xcms", "XtraSNPlocs.Hsapiens.dbSNP141.GRCh38", "XtraSNPlocs.Hsapiens.dbSNP144.GRCh37", "XtraSNPlocs.Hsapiens.dbSNP144.GRCh38", "XVector", "yamss" ], "suggestsMe": [ "alternativeSplicingEvents.hg19", "BiocGenerics", "RTCGA", "scran" ] }, "safe": { "Package": "safe", "Version": "3.14.0", "Depends": [ "R (>= 2.4.0)", "AnnotationDbi", "Biobase", "methods", "SparseM" ], "Suggests": [ "GO.db", "PFAM.db", "reactome.db", "hgu133a.db", "breastCancerUPP", "survival", "foreach", "doRNG", "Rgraphviz", "GOstats" ], "License": "GPL (>= 2)", "MD5sum": "7ee04c60f66ea6ca4c366afed81c23bc", "NeedsCompilation": "no", "Title": "Significance Analysis of Function and Expression", "Description": "SAFE is a resampling-based method for testing functional categories in gene expression experiments. SAFE can be applied to 2-sample and multi-class comparisons, or simple linear regressions. Other experimental designs can also be accommodated through user-defined functions.", "biocViews": [ "DifferentialExpression", "GeneSetEnrichment", "Pathways", "Software", "StatisticalMethod" ], "Author": "William T. Barry", "Maintainer": "William T. Barry ", "source.ver": "src/contrib/safe_3.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/safe_3.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/safe_3.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/safe_3.14.0.tgz", "vignettes": [ "vignettes/safe/inst/doc/SAFEmanual3.pdf" ], "vignetteTitles": [ "SAFE manual" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/safe/inst/doc/SAFEmanual3.R" ], "importsMe": [ "EGSEA", "EnrichmentBrowser" ] }, "sagenhaft": { "Package": "sagenhaft", "Version": "1.44.0", "Depends": [ "R (>= 2.10)", "SparseM (>= 0.73)", "methods" ], "Imports": [ "graphics", "methods", "SparseM", "stats", "utils" ], "License": "GPL (>= 2)", "MD5sum": "491d572d8e20c56f56a101cb9529a3c6", "NeedsCompilation": "no", "Title": "Collection of functions for reading and comparing SAGE libraries", "Description": "This package implements several functions useful for analysis of gene expression data by sequencing tags as done in SAGE (Serial Analysis of Gene Expressen) data, i.e. extraction of a SAGE library from sequence files, sequence error correction, library comparison. Sequencing error correction is implementing using an Expectation Maximization Algorithm based on a Mixture Model of tag counts.", "biocViews": [ "SAGE", "Software" ], "Author": "Tim Beissbarth , with contributions from Gordon Smyth and Lavinia Hyde .", "Maintainer": "Tim Beissbarth ", "URL": "http://tagcalling.mbgproject.org", "source.ver": "src/contrib/sagenhaft_1.44.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/sagenhaft_1.44.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/sagenhaft_1.44.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/sagenhaft_1.44.0.tgz", "vignettes": [ "vignettes/sagenhaft/inst/doc/SAGEnhaft.pdf" ], "vignetteTitles": [ "SAGEnhaft" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/sagenhaft/inst/doc/SAGEnhaft.R" ] }, "SAGx": { "Package": "SAGx", "Version": "1.48.0", "Depends": [ "R (>= 2.5.0)", "stats", "multtest", "methods" ], "Imports": [ "Biobase", "stats4" ], "Suggests": [ "KEGG.db", "hu6800.db", "MASS" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "b6f34e285fa324da6f36612ef81c6e24", "NeedsCompilation": "yes", "Title": "Statistical Analysis of the GeneChip", "Description": "A package for retrieval, preparation and analysis of data from the Affymetrix GeneChip. In particular the issue of identifying differentially expressed genes is addressed.", "biocViews": [ "Clustering", "DataImport", "DifferentialExpression", "GeneExpression", "GeneSetEnrichment", "KEGG", "Microarray", "MultipleComparison", "OneChannel", "Pathways", "Preprocessing", "Regression", "Software" ], "Author": "Per Broberg", "Maintainer": "Per Broberg, ", "URL": "http://home.swipnet.se/pibroberg/expression_hemsida1.html", "source.ver": "src/contrib/SAGx_1.48.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SAGx_1.48.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SAGx_1.48.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SAGx_1.48.0.tgz", "vignettes": [ "vignettes/SAGx/inst/doc/samroc-ex.pdf" ], "vignetteTitles": [ "samroc - example" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SAGx/inst/doc/samroc-ex.R" ] }, "SamSPECTRAL": { "Package": "SamSPECTRAL", "Version": "1.28.0", "Depends": [ "R (>= 2.10)" ], "Imports": [ "methods" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "615a3b87f79fba9b83c9a305bcc21d3f", "NeedsCompilation": "yes", "Title": "Identifies cell population in flow cytometry data.", "Description": "Samples large data such that spectral clustering is possible while preserving density information in edge weights. More specifically, given a matrix of coordinates as input, SamSPECTRAL first builds the communities to sample the data points. Then, it builds a graph and after weighting the edges by conductance computation, the graph is passed to a classic spectral clustering algorithm to find the spectral clusters. The last stage of SamSPECTRAL is to combine the spectral clusters. The resulting \"connected components\" estimate biological cell populations in the data sample. For instructions on manual installation, refer to the PDF file provided in the following documentation.", "biocViews": [ "Cancer", "CellBiology", "Clustering", "FlowCytometry", "HIV", "Software", "StemCells" ], "Author": "Habil Zare and Parisa Shooshtari", "Maintainer": "Habil Zare ", "source.ver": "src/contrib/SamSPECTRAL_1.28.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SamSPECTRAL_1.28.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SamSPECTRAL_1.28.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SamSPECTRAL_1.28.0.tgz", "vignettes": [ "vignettes/SamSPECTRAL/inst/doc/Clustering_by_SamSPECTRAL.pdf" ], "vignetteTitles": [ "A modified spectral clustering method for clustering Flow Cytometry Data" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SamSPECTRAL/inst/doc/Clustering_by_SamSPECTRAL.R" ], "importsMe": [ "CONFESS" ] }, "sangerseqR": { "Package": "sangerseqR", "Version": "1.10.0", "Depends": [ "R (>= 3.0.2)", "Biostrings" ], "Imports": [ "methods", "shiny" ], "Suggests": [ "BiocStyle", "knitr", "RUnit", "BiocGenerics" ], "License": "GPL-2", "MD5sum": "3c03310759fa77654a54dea43750cadf", "NeedsCompilation": "no", "Title": "Tools for Sanger Sequencing Data in R", "Description": "This package contains several tools for analyzing Sanger Sequencing data files in R, including reading .scf and .ab1 files, making basecalls and plotting chromatograms.", "biocViews": [ "SNP", "Sequencing", "Software", "Visualization" ], "Author": "Jonathon T. Hill, Bradley Demarest", "Maintainer": "Jonathon Hill ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/sangerseqR_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/sangerseqR_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/sangerseqR_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/sangerseqR_1.10.0.tgz", "vignettes": [ "vignettes/sangerseqR/inst/doc/sangerseq_walkthrough.pdf" ], "vignetteTitles": [ "sangerseqR" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/sangerseqR/inst/doc/sangerseq_walkthrough.R" ], "suggestsMe": [ "CrispRVariants" ] }, "SANTA": { "Package": "SANTA", "Version": "2.12.0", "Depends": [ "R (>= 2.14)", "igraph" ], "Imports": [ "Matrix", "snow" ], "Suggests": [ "RUnit", "BiocGenerics", "knitr", "knitcitations", "formatR", "org.Sc.sgd.db", "BioNet", "DLBCL", "msm" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "7b6f6134362efb79a4a0f325ffec499b", "NeedsCompilation": "yes", "Title": "Spatial Analysis of Network Associations", "Description": "This package provides methods for measuring the strength of association between a network and a phenotype. It does this by measuring clustering of the phenotype across the network (Knet). Vertices can also be individually ranked by their strength of association with high-weight vertices (Knode).", "biocViews": [ "Clustering", "Network", "NetworkEnrichment", "Software" ], "Author": "Alex J. Cornish and Florian Markowetz", "Maintainer": "Alex J. Cornish ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/SANTA_2.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SANTA_2.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SANTA_2.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SANTA_2.12.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SANTA/inst/doc/SANTA-vignette.R" ], "htmlDocs": [ "vignettes/SANTA/inst/doc/SANTA-vignette.html" ], "htmlTitles": [ "Introduction to SANTA" ] }, "sapFinder": { "Package": "sapFinder", "Version": "1.12.0", "Depends": [ "R (>= 3.0.0)", "rTANDEM (>= 1.3.5)" ], "Imports": [ "pheatmap", "Rcpp (>= 0.10.6)", "graphics", "grDevices", "stats", "utils" ], "LinkingTo": [ "Rcpp" ], "Suggests": [ "RUnit", "BiocGenerics", "BiocStyle" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "06483162261e357163b2f4a2f0036862", "NeedsCompilation": "yes", "Title": "A package for variant peptides detection and visualization in shotgun proteomics.", "Description": "sapFinder is developed to automate (1) variation-associated database construction, (2) database searching, (3) post-processing, (4) HTML-based report generation in shotgun proteomics.", "biocViews": [ "MassSpectrometry", "Proteomics", "RNASeq", "ReportWriting", "SNP", "Software", "Visualization" ], "Author": "Shaohang Xu, Bo Wen", "Maintainer": "Shaohang Xu , Bo Wen ", "source.ver": "src/contrib/sapFinder_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/sapFinder_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/sapFinder_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/sapFinder_1.12.0.tgz", "vignettes": [ "vignettes/sapFinder/inst/doc/sapFinder.pdf" ], "vignetteTitles": [ "sapFinder Vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/sapFinder/inst/doc/sapFinder.R" ] }, "savR": { "Package": "savR", "Version": "1.12.0", "Depends": [ "ggplot2" ], "Imports": [ "methods", "reshape2", "scales", "gridExtra", "XML" ], "Suggests": [ "Cairo", "testthat" ], "License": "AGPL-3", "MD5sum": "cd7bd7dc9e5f9d7ce6ccc9af7121e5cc", "NeedsCompilation": "no", "Title": "Parse and analyze Illumina SAV files", "Description": "Parse Illumina Sequence Analysis Viewer (SAV) files, access data, and generate QC plots.", "biocViews": [ "Sequencing", "Software" ], "Author": "R. Brent Calder", "Maintainer": "R. Brent Calder ", "URL": "https://github.com/bcalder/savR", "BugReports": "https://github.com/bcalder/savR/issues", "source.ver": "src/contrib/savR_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/savR_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/savR_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/savR_1.12.0.tgz", "vignettes": [ "vignettes/savR/inst/doc/savR.pdf" ], "vignetteTitles": [ "Using savR" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/savR/inst/doc/savR.R" ] }, "SBMLR": { "Package": "SBMLR", "Version": "1.70.0", "Depends": [ "XML", "deSolve" ], "Suggests": [ "rsbml" ], "License": "GPL-2", "MD5sum": "af7bc56c4aff2e98edabdd08931c866d", "NeedsCompilation": "no", "Title": "SBML-R Interface and Analysis Tools", "Description": "This package contains a systems biology markup language (SBML) interface to R.", "biocViews": [ "GraphAndNetwork", "Network", "Pathways", "Software" ], "Author": "Tomas Radivoyevitch, Vishak Venkateswaran", "Maintainer": "Tomas Radivoyevitch ", "URL": "http://epbi-radivot.cwru.edu/SBMLR/SBMLR.html", "source.ver": "src/contrib/SBMLR_1.70.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SBMLR_1.70.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SBMLR_1.70.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SBMLR_1.70.0.tgz", "vignettes": [ "vignettes/SBMLR/inst/doc/quick-start.pdf" ], "vignetteTitles": [ "Quick intro to SBMLR" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SBMLR/inst/doc/quick-start.R" ] }, "SC3": { "Package": "SC3", "Version": "1.3.18", "Depends": [ "R(>= 3.3)" ], "Imports": [ "graphics", "stats", "utils", "methods", "e1071", "parallel", "foreach", "doParallel", "doRNG", "shiny", "ggplot2", "pheatmap (>= 1.0.8)", "ROCR", "robustbase", "rrcov", "cluster", "WriteXLS", "Rcpp (>= 0.11.1)", "scater" ], "LinkingTo": [ "Rcpp", "RcppArmadillo" ], "Suggests": [ "knitr", "rmarkdown", "testthat", "mclust" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "c5a36c1213c87f64d6c440c7601f7fe3", "NeedsCompilation": "no", "Title": "Single-Cell Consensus Clustering", "Description": "A tool for unsupervised clustering and analysis of single cell RNA-Seq data.", "biocViews": [ "Classification", "Clustering", "DataRepresentation", "DifferentialExpression", "DimensionReduction", "GUI", "RNASeq", "SingleCell", "Software", "SupportVectorMachine", "Transcription", "Transcriptomics", "Visualization" ], "Author": "Vladimir Kiselev", "Maintainer": "Vladimir Kiselev ", "URL": "https://github.com/hemberg-lab/SC3", "VignetteBuilder": "knitr", "BugReports": "https://support.bioconductor.org/t/sc3/", "source.ver": "src/contrib/SC3_1.3.18.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SC3_1.3.18.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SC3_1.3.18.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SC3_1.3.18.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SC3/inst/doc/my-vignette.R" ], "htmlDocs": [ "vignettes/SC3/inst/doc/my-vignette.html" ], "htmlTitles": [ "SC3 package manual" ] }, "SCAN.UPC": { "Package": "SCAN.UPC", "Version": "2.16.0", "Depends": [ "R (>= 2.14.0)", "Biobase (>= 2.6.0)", "oligo", "Biostrings", "GEOquery", "affy", "affyio", "foreach", "sva" ], "Imports": [ "utils", "methods", "MASS", "tools", "IRanges" ], "Suggests": [ "pd.hg.u95a" ], "License": "MIT", "MD5sum": "35243a75ca33443c3741b3def392bead", "NeedsCompilation": "no", "Title": "Single-channel array normalization (SCAN) and Universal exPression Codes (UPC)", "Description": "SCAN is a microarray normalization method to facilitate personalized-medicine workflows. Rather than processing microarray samples as groups, which can introduce biases and present logistical challenges, SCAN normalizes each sample individually by modeling and removing probe- and array-specific background noise using only data from within each array. SCAN can be applied to one-channel (e.g., Affymetrix) or two-channel (e.g., Agilent) microarrays. The Universal exPression Codes (UPC) method is an extension of SCAN that estimates whether a given gene/transcript is active above background levels in a given sample. The UPC method can be applied to one-channel or two-channel microarrays as well as to RNA-Seq read counts. Because UPC values are represented on the same scale and have an identical interpretation for each platform, they can be used for cross-platform data integration.", "biocViews": [ "Microarray", "OneChannel", "Preprocessing", "RNASeq", "Software", "TwoChannel" ], "Author": "Stephen R. Piccolo and Andrea H. Bild and W. Evan Johnson", "Maintainer": "Stephen R. Piccolo ", "URL": "http://bioconductor.org, http://jlab.bu.edu/software/scan-upc", "source.ver": "src/contrib/SCAN.UPC_2.16.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SCAN.UPC_2.16.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SCAN.UPC_2.16.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SCAN.UPC_2.16.0.tgz", "vignettes": [ "vignettes/SCAN.UPC/inst/doc/SCAN.vignette.pdf" ], "vignetteTitles": [ "Primer" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SCAN.UPC/inst/doc/SCAN.vignette.R" ] }, "scater": { "Package": "scater", "Version": "1.2.0", "Depends": [ "R (>= 3.3)", "Biobase", "ggplot2", "methods" ], "Imports": [ "biomaRt", "BiocGenerics", "data.table", "dplyr", "edgeR", "ggbeeswarm", "grid", "limma", "matrixStats", "parallel", "plyr", "reshape2", "rhdf5", "rjson", "shiny", "shinydashboard", "stats", "tximport", "viridis" ], "Suggests": [ "BiocStyle", "cowplot", "cluster", "destiny", "knitr", "monocle", "mvoutlier", "rmarkdown", "Rtsne", "testthat", "magrittr" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "3b3a617010a6cf8b129040fc01812e20", "NeedsCompilation": "yes", "Title": "Single-cell analysis toolkit for gene expression data in R", "Description": "A collection of tools for doing various analyses of single-cell RNA-seq gene expression data, with a focus on quality control.", "biocViews": [ "DataImport", "DataRepresentation", "DimensionReduction", "GeneExpression", "Infrastructure", "Normalization", "Preprocessing", "QualityControl", "RNASeq", "Sequencing", "SingleCell", "Software", "Transcriptomics", "Visualization" ], "Author": "Davis McCarthy", "Maintainer": "Davis McCarthy ", "URL": "https://github.com/davismcc/scater", "VignetteBuilder": "knitr", "BugReports": "https://github.com/davismcc/scater/issues", "source.ver": "src/contrib/scater_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/scater_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/scater_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/scater_1.2.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/scater/inst/doc/vignette.R" ], "htmlDocs": [ "vignettes/scater/inst/doc/vignette.html" ], "htmlTitles": [ "An introduction to the scater package" ], "dependsOnMe": [ "scran" ], "importsMe": [ "SC3" ], "suggestsMe": [ "switchde" ] }, "scde": { "Package": "scde", "Version": "2.2.0", "Depends": [ "R (>= 3.0.0)", "flexmix" ], "Imports": [ "Rcpp (>= 0.10.4)", "RcppArmadillo (>= 0.5.400.2.0)", "mgcv", "Rook", "rjson", "MASS", "Cairo", "RColorBrewer", "edgeR", "quantreg", "methods", "nnet", "RMTstat", "extRemes", "pcaMethods", "BiocParallel", "parallel" ], "LinkingTo": [ "Rcpp", "RcppArmadillo" ], "Suggests": [ "knitr", "cba", "fastcluster", "WGCNA", "GO.db", "org.Hs.eg.db", "rmarkdown" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "f812f348edd4868eab6f9d3f2d7514df", "NeedsCompilation": "yes", "Title": "Single Cell Differential Expression", "Description": "The scde package implements a set of statistical methods for analyzing single-cell RNA-seq data. scde fits individual error models for single-cell RNA-seq measurements. These models can then be used for assessment of differential expression between groups of cells, as well as other types of analysis. The scde package also contains the pagoda framework which applies pathway and gene set overdispersion analysis to identify and characterize putative cell subpopulations based on transcriptional signatures. The overall approach to the differential expression analysis is detailed in the following publication: \"Bayesian approach to single-cell differential expression analysis\" (Kharchenko PV, Silberstein L, Scadden DT, Nature Methods, doi: 10.1038/nmeth.2967). The overall approach to subpopulation identification and characterization is detailed in the following pre-print: \"Characterizing transcriptional heterogeneity through pathway and gene set overdispersion analysis\" (Fan J, Salathia N, Liu R, Kaeser G, Yung Y, Herman J, Kaper F, Fan JB, Zhang K, Chun J, and Kharchenko PV, Nature Methods, doi:10.1038/nmeth.3734).", "biocViews": [ "Bayesian", "DifferentialExpression", "RNASeq", "Software", "StatisticalMethod", "Transcription" ], "Author": "Peter Kharchenko [aut, cre], Jean Fan [aut]", "Maintainer": "Jean Fan ", "URL": "http://pklab.med.harvard.edu/scde", "VignetteBuilder": "knitr", "BugReports": "https://github.com/hms-dbmi/scde/issues", "source.ver": "src/contrib/scde_2.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/scde_2.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/scde_2.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/scde_2.2.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false }, "ScISI": { "Package": "ScISI", "Version": "1.46.0", "Depends": [ "R (>= 2.10)", "GO.db", "RpsiXML", "annotate", "apComplex" ], "Imports": [ "AnnotationDbi", "GO.db", "RpsiXML", "annotate", "methods", "org.Sc.sgd.db", "utils" ], "Suggests": [ "ppiData", "xtable" ], "License": "LGPL", "MD5sum": "31e8ff5011f1adae4e0adbab0699d1d7", "NeedsCompilation": "no", "Title": "In Silico Interactome", "Description": "Package to create In Silico Interactomes", "biocViews": [ "DecisionTree", "GraphAndNetwork", "NetworkInference", "Proteomics", "Software" ], "Author": "Tony Chiang ", "Maintainer": "Tony Chiang ", "source.ver": "src/contrib/ScISI_1.46.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ScISI_1.46.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ScISI_1.46.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ScISI_1.46.0.tgz", "vignettes": [ "vignettes/ScISI/inst/doc/vignette.pdf" ], "vignetteTitles": [ "ScISI Vignette" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ScISI/inst/doc/vignette.R" ], "dependsOnMe": [ "PCpheno", "ppiStats", "SLGI" ], "importsMe": [ "PCpheno", "SLGI" ], "suggestsMe": [ "RpsiXML" ] }, "scran": { "Package": "scran", "Version": "1.2.2", "Depends": [ "R (>= 3.3.0)", "BiocParallel", "scater" ], "Imports": [ "dynamicTreeCut", "zoo", "edgeR", "stats", "BiocGenerics", "methods", "Biobase", "utils", "Matrix", "shiny", "graphics", "grDevices", "statmod" ], "Suggests": [ "limSolve", "limma", "testthat", "knitr", "BiocStyle", "org.Mm.eg.db", "DESeq2", "monocle", "S4Vectors", "ggplot2" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "1b2e2a58ae36171a12ba289c2143f431", "NeedsCompilation": "yes", "Title": "Methods for Single-Cell RNA-Seq Data Analysis", "Description": "Implements a variety of low-level analyses of single-cell RNA-seq data. Methods are provided for normalization of cell-specific biases, assignment of cell cycle phase, and detection of highly variable and significantly correlated genes.", "biocViews": [ "GeneExpression", "Normalization", "RNASeq", "Sequencing", "SingleCell", "Software", "Transcriptomics" ], "Author": "Aaron Lun [aut, cre], Karsten Bach [aut], Jong Kyoung Kim [ctb], Antonio Scialdone [ctb]", "Maintainer": "Aaron Lun ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/scran_1.2.2.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/scran_1.2.2.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/scran_1.2.2.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/scran_1.2.2.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/scran/inst/doc/scran.R" ], "htmlDocs": [ "vignettes/scran/inst/doc/scran.html" ], "htmlTitles": [ "Using scran to perform basic analyses of single-cell RNA-seq data" ], "suggestsMe": [ "SIMLR" ] }, "scsR": { "Package": "scsR", "Version": "1.10.0", "Depends": [ "R (>= 2.14.0)", "STRINGdb", "methods", "BiocGenerics", "Biostrings", "IRanges", "plyr", "tcltk" ], "Imports": [ "sqldf", "hash", "ggplot2", "graphics", "grDevices", "RColorBrewer" ], "Suggests": [ "RUnit" ], "License": "GPL-2", "MD5sum": "78c07fb85efcae4507a9564e11c4d861", "NeedsCompilation": "no", "Title": "SiRNA correction for seed mediated off-target effect", "Description": "Corrects genome-wide siRNA screens for seed mediated off-target effect. Suitable functions to identify the effective seeds/miRNAs and to visualize their effect are also provided in the package.", "biocViews": [ "Preprocessing", "Software" ], "Author": "Andrea Franceschini", "Maintainer": "Andrea Franceschini , Roger Meier , Christian von Mering ", "source.ver": "src/contrib/scsR_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/scsR_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/scsR_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/scsR_1.10.0.tgz", "vignettes": [ "vignettes/scsR/inst/doc/scsR.pdf" ], "vignetteTitles": [ "scsR Vignette" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/scsR/inst/doc/scsR.R" ] }, "segmentSeq": { "Package": "segmentSeq", "Version": "2.8.0", "Depends": [ "R (>= 2.3.0)", "methods", "baySeq (>= 1.99.0)", "S4Vectors", "parallel", "GenomicRanges", "ShortRead" ], "Imports": [ "Rsamtools", "IRanges", "GenomeInfoDb", "graphics", "grDevices", "utils", "abind" ], "Suggests": [ "BiocStyle", "BiocGenerics" ], "License": "GPL-3", "MD5sum": "b90281e6a4c16ac38e665c9fec01a00e", "NeedsCompilation": "no", "Title": "Methods for identifying small RNA loci from high-throughput sequencing data", "Description": "High-throughput sequencing technologies allow the production of large volumes of short sequences, which can be aligned to the genome to create a set of matches to the genome. By looking for regions of the genome which to which there are high densities of matches, we can infer a segmentation of the genome into regions of biological significance. The methods in this package allow the simultaneous segmentation of data from multiple samples, taking into account replicate data, in order to create a consensus segmentation. This has obvious applications in a number of classes of sequencing experiments, particularly in the discovery of small RNA loci and novel mRNA transcriptome discovery.", "biocViews": [ "Alignment", "DataImport", "DifferentialExpression", "MultipleComparison", "QualityControl", "Sequencing", "Software" ], "Author": "Thomas J. Hardcastle", "Maintainer": "Thomas J. Hardcastle ", "source.ver": "src/contrib/segmentSeq_2.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/segmentSeq_2.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/segmentSeq_2.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/segmentSeq_2.8.0.tgz", "vignettes": [ "vignettes/segmentSeq/inst/doc/methylationAnalysis.pdf", "vignettes/segmentSeq/inst/doc/segmentSeq.pdf" ], "vignetteTitles": [ "segmentsSeq: Methylation locus identification", "segmentSeq: small RNA locus detection" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/segmentSeq/inst/doc/methylationAnalysis.R", "vignettes/segmentSeq/inst/doc/segmentSeq.R" ] }, "SELEX": { "Package": "SELEX", "Version": "1.6.0", "Depends": [ "R (>= 2.7.0)", "rJava (>= 0.5-0)", "Biostrings (>= 2.26.0)" ], "License": "GPL (>=2)", "MD5sum": "2aaeca6f6c75ac4e6251767a771d6821", "NeedsCompilation": "no", "Title": "Functions for analyzing SELEX-seq data", "Description": "Tools for quantifying DNA binding specificities based on SELEX-seq data", "biocViews": [ "GeneRegulation", "MotifAnnotation", "MotifDiscovery", "Software", "Transcription" ], "Author": "Chaitanya Rastogi, Dahong Liu, and Harmen Bussemaker", "Maintainer": "Harmen Bussemaker ", "URL": "http://bussemakerlab.org/software/SELEX/", "SystemRequirements": "Java (>= 1.5)", "source.ver": "src/contrib/SELEX_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SELEX_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SELEX_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SELEX_1.6.0.tgz", "vignettes": [ "vignettes/SELEX/inst/doc/SELEX.pdf" ], "vignetteTitles": [ "Motif Discovery with SELEX-seq" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SELEX/inst/doc/SELEX.R" ] }, "SemDist": { "Package": "SemDist", "Version": "1.8.0", "Depends": [ "R (>= 3.1)", "AnnotationDbi", "GO.db", "annotate" ], "Suggests": [ "GOSemSim" ], "License": "GPL (>= 2)", "MD5sum": "a425f53c9317f9ba19d949ee9de9d5e1", "NeedsCompilation": "no", "Title": "Information Accretion-based Function Predictor Evaluation", "Description": "This package implements methods to calculate information accretion for a given version of the gene ontology and uses this data to calculate remaining uncertainty, misinformation, and semantic similarity for given sets of predicted annotations and true annotations from a protein function predictor.", "biocViews": [ "Annotation", "Classification", "GO", "Software" ], "Author": "Ian Gonzalez and Wyatt Clark", "Maintainer": "Ian Gonzalez ", "URL": "http://github.com/iangonzalez/SemDist", "source.ver": "src/contrib/SemDist_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SemDist_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SemDist_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SemDist_1.8.0.tgz", "vignettes": [ "vignettes/SemDist/inst/doc/introduction.pdf" ], "vignetteTitles": [ "introduction.pdf" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SemDist/inst/doc/introduction.R" ] }, "SEPA": { "Package": "SEPA", "Version": "1.4.0", "Depends": [ "R(>= 2.10.0)" ], "Imports": [ "ggplot2", "shiny", "topGO", "segmented", "reshape2", "org.Hs.eg.db", "org.Mm.eg.db" ], "Suggests": [ "knitr" ], "License": "GPL(>=2)", "MD5sum": "79a06a4599df557f9e4217dc3dc97a2f", "NeedsCompilation": "no", "Title": "SEPA", "Description": "Given single-cell RNA-seq data and true experiment time of cells or pseudo-time cell ordering, SEPA provides convenient functions for users to assign genes into different gene expression patterns such as constant, monotone increasing and increasing then decreasing. SEPA then performs GO enrichment analysis to analysis the functional roles of genes with same or similar patterns.", "biocViews": [ "GO", "GUI", "GeneExpression", "Software", "Visualization" ], "Author": "Zhicheng Ji, Hongkai Ji", "Maintainer": "Zhicheng Ji ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/SEPA_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SEPA_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SEPA_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SEPA_1.4.0.tgz", "vignettes": [ "vignettes/SEPA/inst/doc/SEPA.pdf" ], "vignetteTitles": [ "SEPA: Single-Cell Gene Expression Pattern Analysis" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SEPA/inst/doc/SEPA.R" ] }, "seq2pathway": { "Package": "seq2pathway", "Version": "1.6.0", "Depends": [ "R (>= 2.10.0)" ], "Imports": [ "nnet", "WGCNA", "GSA", "biomaRt", "GenomicRanges", "seq2pathway.data" ], "License": "GPL-2", "MD5sum": "1ee0ec8a9cbee0b144d12312cb0bd1ca", "NeedsCompilation": "no", "Title": "a novel tool for functional gene-set (or termed as pathway) analysis of next-generation sequencing data", "Description": "Seq2pathway is a novel tool for functional gene-set (or termed as pathway) analysis of next-generation sequencing data, consisting of \"seq2gene\" and \"gene2path\" components. The seq2gene links sequence-level measurements of genomic regions (including SNPs or point mutation coordinates) to gene-level scores, and the gene2pathway summarizes gene scores to pathway-scores for each sample. The seq2gene has the feasibility to assign both coding and non-exon regions to a broader range of neighboring genes than only the nearest one, thus facilitating the study of functional non-coding regions. The gene2pathway takes into account the quantity of significance for gene members within a pathway compared those outside a pathway. The output of seq2pathway is a general structure of quantitative pathway-level scores, thus allowing one to functional interpret such datasets as RNA-seq, ChIP-seq, GWAS, and derived from other next generational sequencing experiments.", "biocViews": [ "Software" ], "Author": "Xinan Yang ; Bin Wang ", "Maintainer": "Xinan Yang with contribution from Lorenzo Pesce and Ana Marija Sokovic ", "source.ver": "src/contrib/seq2pathway_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/seq2pathway_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/seq2pathway_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/seq2pathway_1.6.0.tgz", "vignettes": [ "vignettes/seq2pathway/inst/doc/seq2pathwaypackage.pdf" ], "vignetteTitles": [ "An R package for sequence" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/seq2pathway/inst/doc/seq2pathwaypackage.R" ] }, "SeqArray": { "Package": "SeqArray", "Version": "1.14.1", "Depends": [ "R (>= 3.3.0)", "gdsfmt (>= 1.10.1)" ], "Imports": [ "methods", "parallel", "S4Vectors", "IRanges", "GenomicRanges", "GenomeInfoDb", "SummarizedExperiment", "Biostrings", "VariantAnnotation" ], "LinkingTo": [ "gdsfmt" ], "Suggests": [ "BiocParallel", "digest", "crayon", "RUnit", "Biobase", "BiocGenerics", "knitr", "Rcpp", "SNPRelate" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "b8523fe4ac2431e52ee3a11006cc9157", "NeedsCompilation": "yes", "Title": "Big Data Management of Whole-genome Sequence Variant Calls", "Description": "Big data management of whole-genome sequencing variant calls with thousands of individuals: genotypic data (e.g., SNVs, indels and structural variation calls) and annotations in SeqArray files are stored in an array-oriented and compressed manner, with efficient data access using the R programming language.", "biocViews": [ "DataRepresentation", "Genetics", "Infrastructure", "Sequencing", "Software" ], "Author": "Xiuwen Zheng [aut, cre], Stephanie Gogarten [aut], David Levine [ctb], Cathy Laurie [ctb]", "Maintainer": "Xiuwen Zheng ", "URL": "http://github.com/zhengxwen/SeqArray", "VignetteBuilder": "knitr", "BugReports": "http://github.com/zhengxwen/SeqArray/issues", "source.ver": "src/contrib/SeqArray_1.14.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SeqArray_1.14.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SeqArray_1.14.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SeqArray_1.14.1.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SeqArray/inst/doc/R_Integration.R", "vignettes/SeqArray/inst/doc/SeqArrayTutorial.R" ], "htmlDocs": [ "vignettes/SeqArray/inst/doc/OverviewSlides.html", "vignettes/SeqArray/inst/doc/R_Integration.html", "vignettes/SeqArray/inst/doc/SeqArrayTutorial.html" ], "htmlTitles": [ "SeqArray Overview", "R Integration", "SeqArray Data Format and Access" ], "dependsOnMe": [ "SeqVarTools" ], "importsMe": [ "GENESIS" ] }, "seqbias": { "Package": "seqbias", "Version": "1.22.0", "Depends": [ "R (>= 2.13.0)", "GenomicRanges (>= 0.1.0)", "Biostrings (>= 2.15.0)", "methods" ], "Imports": [ "zlibbioc" ], "LinkingTo": [ "Rsamtools (>= 1.19.38)" ], "Suggests": [ "Rsamtools", "ggplot2" ], "License": "LGPL-3", "Archs": "i386, x64", "MD5sum": "849001ed43f2489d1b843d0ef578311c", "NeedsCompilation": "yes", "Title": "Estimation of per-position bias in high-throughput sequencing data", "Description": "This package implements a model of per-position sequencing bias in high-throughput sequencing data using a simple Bayesian network, the structure and parameters of which are trained on a set of aligned reads and a reference genome sequence.", "biocViews": [ "Sequencing", "Software" ], "Author": "Daniel Jones ", "Maintainer": "Daniel Jones ", "source.ver": "src/contrib/seqbias_1.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/seqbias_1.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/seqbias_1.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/seqbias_1.22.0.tgz", "vignettes": [ "vignettes/seqbias/inst/doc/overview.pdf" ], "vignetteTitles": [ "Assessing and Adjusting for Technical Bias in High Throughput Sequencing Data" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/seqbias/inst/doc/overview.R" ], "dependsOnMe": [ "ReQON" ] }, "seqCNA": { "Package": "seqCNA", "Version": "1.20.0", "Depends": [ "R (>= 3.0)", "GLAD (>= 2.14)", "doSNOW (>= 1.0.5)", "adehabitatLT (>= 0.3.4)", "seqCNA.annot (>= 0.99)", "methods" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "44fb143b689ad761a83a5b0b52668da1", "NeedsCompilation": "yes", "Title": "Copy number analysis of high-throughput sequencing cancer data", "Description": "Copy number analysis of high-throughput sequencing cancer data with fast summarization, extensive filtering and improved normalization", "biocViews": [ "CopyNumberVariation", "Genetics", "Sequencing", "Software" ], "Author": "David Mosen-Ansorena", "Maintainer": "David Mosen-Ansorena ", "SystemRequirements": "samtools", "source.ver": "src/contrib/seqCNA_1.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/seqCNA_1.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/seqCNA_1.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/seqCNA_1.20.0.tgz", "vignettes": [ "vignettes/seqCNA/inst/doc/seqCNA.pdf" ], "vignetteTitles": [ "seqCNA" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/seqCNA/inst/doc/seqCNA.R" ] }, "SeqGSEA": { "Package": "SeqGSEA", "Version": "1.14.0", "Depends": [ "Biobase", "doParallel", "DESeq" ], "Imports": [ "methods", "biomaRt" ], "Suggests": [ "easyRNASeq", "GenomicRanges" ], "License": "GPL (>= 3)", "MD5sum": "d5f1c9747089cda26d28b7aac210df3c", "NeedsCompilation": "no", "Title": "Gene Set Enrichment Analysis (GSEA) of RNA-Seq Data: integrating differential expression and splicing", "Description": "The package generally provides methods for gene set enrichment analysis of high-throughput RNA-Seq data by integrating differential expression and splicing. It uses negative binomial distribution to model read count data, which accounts for sequencing biases and biological variation. Based on permutation tests, statistical significance can also be achieved regarding each gene's differential expression and splicing, respectively.", "biocViews": [ "DifferentialExpression", "GeneExpression", "GeneSetEnrichment", "RNASeq", "Sequencing", "Software" ], "Author": "Xi Wang ", "Maintainer": "Xi Wang ", "source.ver": "src/contrib/SeqGSEA_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SeqGSEA_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SeqGSEA_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SeqGSEA_1.14.0.tgz", "vignettes": [ "vignettes/SeqGSEA/inst/doc/SeqGSEA.pdf" ], "vignetteTitles": [ "Gene set enrichment analysis of RNA-Seq data with the SeqGSEA package" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SeqGSEA/inst/doc/SeqGSEA.R" ] }, "seqLogo": { "Package": "seqLogo", "Version": "1.40.0", "Depends": [ "methods", "grid" ], "Imports": [ "stats4" ], "License": "LGPL (>= 2)", "MD5sum": "4fd759c2257243dea8f0c89c5329710b", "NeedsCompilation": "no", "Title": "Sequence logos for DNA sequence alignments", "Description": "seqLogo takes the position weight matrix of a DNA sequence motif and plots the corresponding sequence logo as introduced by Schneider and Stephens (1990).", "biocViews": [ "SequenceMatching", "Software" ], "Author": "Oliver Bembom", "Maintainer": "Oliver Bembom ", "source.ver": "src/contrib/seqLogo_1.40.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/seqLogo_1.40.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/seqLogo_1.40.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/seqLogo_1.40.0.tgz", "vignettes": [ "vignettes/seqLogo/inst/doc/seqLogo.pdf" ], "vignetteTitles": [ "Sequence logos for DNA sequence alignments" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/seqLogo/inst/doc/seqLogo.R" ], "dependsOnMe": [ "motifRG", "rGADEM" ], "importsMe": [ "motifRG", "PWMEnrich", "rGADEM", "spliceSites", "SPLINTER", "TFBSTools" ], "suggestsMe": [ "BCRANK", "DiffLogo", "MotifDb" ] }, "seqPattern": { "Package": "seqPattern", "Version": "1.6.0", "Depends": [ "methods", "R (>= 2.15.0)" ], "Imports": [ "Biostrings", "GenomicRanges", "IRanges", "KernSmooth", "plotrix" ], "Suggests": [ "BSgenome.Drerio.UCSC.danRer7", "CAGEr", "RUnit", "BiocGenerics", "BiocStyle" ], "Enhances": [ "parallel" ], "License": "GPL-3", "MD5sum": "b0f51e76f8e30b7bcd2969f97622d83c", "NeedsCompilation": "no", "Title": "Visualising oligonucleotide patterns and motif occurrences across a set of sorted sequences", "Description": "Visualising oligonucleotide patterns and sequence motifs occurrences across a large set of sequences centred at a common reference point and sorted by a user defined feature.", "biocViews": [ "SequenceMatching", "Software", "Visualization" ], "Author": "Vanja Haberle ", "Maintainer": "Vanja Haberle ", "source.ver": "src/contrib/seqPattern_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/seqPattern_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/seqPattern_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/seqPattern_1.6.0.tgz", "vignettes": [ "vignettes/seqPattern/inst/doc/seqPattern.pdf" ], "vignetteTitles": [ "seqPattern" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/seqPattern/inst/doc/seqPattern.R" ], "importsMe": [ "genomation" ] }, "seqplots": { "Package": "seqplots", "Version": "1.12.0", "Depends": [ "R (>= 3.2.0)" ], "Imports": [ "methods", "IRanges", "BSgenome", "digest", "rtracklayer", "GenomicRanges", "Biostrings", "shiny (>= 0.13.0)", "DBI", "RSQLite", "plotrix", "fields", "grid", "kohonen", "parallel", "GenomeInfoDb", "class", "S4Vectors", "ggplot2", "reshape2", "gridExtra", "jsonlite", "DT (>= 0.1.0)", "RColorBrewer" ], "Suggests": [ "testthat", "BiocStyle", "knitr", "rmarkdown" ], "License": "GPL-3", "MD5sum": "500c15544ad7da18d01ae140659ec078", "NeedsCompilation": "no", "Title": "An interactive tool for visualizing NGS signals and sequence motif densities along genomic features using average plots and heatmaps", "Description": "SeqPlots is a tool for plotting next generation sequencing (NGS) based experiments' signal tracks, e.g. reads coverage from ChIP-seq, RNA-seq and DNA accessibility assays like DNase-seq and MNase-seq, over user specified genomic features, e.g. promoters, gene bodies, etc. It can also calculate sequence motif density profiles from reference genome. The data are visualized as average signal profile plot, with error estimates (standard error and 95% confidence interval) shown as fields, or as series of heatmaps that can be sorted and clustered using hierarchical clustering, k-means algorithm and self organising maps. Plots can be prepared using R programming language or web browser based graphical user interface (GUI) implemented using Shiny framework. The dual-purpose implementation allows running the software locally on desktop or deploying it on server. SeqPlots is useful for both for exploratory data analyses and preparing replicable, publication quality plots. Other features of the software include collaboration and data sharing capabilities, as well as ability to store pre-calculated result matrixes, that combine many sequencing experiments and in-silico generated tracks with multiple different features. These binaries can be further used to generate new combination plots on fly, run automated batch operations or share with colleagues, who can adjust their plotting parameters without loading actual tracks and recalculating numeric values. SeqPlots relays on Bioconductor packages, mainly on rtracklayer for data input and BSgenome packages for reference genome sequence and annotations.", "biocViews": [ "ChIPSeq", "RNASeq", "Sequencing", "Software", "Visualization" ], "Author": "Przemyslaw Stempor", "Maintainer": "Przemyslaw Stempor ", "URL": "http://github.com/przemol/seqplots", "VignetteBuilder": "knitr", "BugReports": "http://github.com/przemol/seqplots/issues", "source.ver": "src/contrib/seqplots_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/seqplots_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/seqplots_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/seqplots_1.12.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/seqplots/inst/doc/QuickStart.R", "vignettes/seqplots/inst/doc/SeqPlotsGUI.R" ], "htmlDocs": [ "vignettes/seqplots/inst/doc/QuickStart.html", "vignettes/seqplots/inst/doc/SeqPlotsGUI.html" ], "htmlTitles": [ "Vignette Title", "Vignette Title" ] }, "seqTools": { "Package": "seqTools", "Version": "1.8.0", "Depends": [ "methods", "utils", "zlibbioc" ], "LinkingTo": [ "zlibbioc" ], "Suggests": [ "RUnit", "BiocGenerics" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "642d01b86c01479c4372acff32cd0383", "NeedsCompilation": "yes", "Title": "Analysis of nucleotide, sequence and quality content on fastq files.", "Description": "Analyze read length, phred scores and alphabet frequency and DNA k-mers on uncompressed and compressed fastq files.", "biocViews": [ "QualityControl", "Sequencing", "Software" ], "Author": "Wolfgang Kaisers", "Maintainer": "Wolfgang Kaisers ", "source.ver": "src/contrib/seqTools_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/seqTools_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/seqTools_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/seqTools_1.8.0.tgz", "vignettes": [ "vignettes/seqTools/inst/doc/seqTools_qual_report.pdf", "vignettes/seqTools/inst/doc/seqTools.pdf" ], "vignetteTitles": [ "seqTools_qual_report", "Introduction" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/seqTools/inst/doc/seqTools_qual_report.R", "vignettes/seqTools/inst/doc/seqTools.R" ] }, "SeqVarTools": { "Package": "SeqVarTools", "Version": "1.12.0", "Depends": [ "SeqArray (>= 1.11.17)" ], "Imports": [ "grDevices", "graphics", "stats", "methods", "stringr", "gdsfmt", "GenomicRanges", "IRanges", "S4Vectors", "GWASExactHW", "VariantAnnotation", "Biobase", "logistf" ], "Suggests": [ "BiocGenerics", "BiocStyle", "RUnit" ], "License": "GPL-3", "MD5sum": "7c09d4e63dc9350516782dd00a23ca90", "NeedsCompilation": "no", "Title": "Tools for variant data", "Description": "An interface to the fast-access storage format for VCF data provided in SeqArray, with tools for common operations and analysis.", "biocViews": [ "GeneticVariability", "Genetics", "SNP", "Sequencing", "Software" ], "Author": "Stephanie M. Gogarten, Xiuwen Zheng, Adrienne Stilp", "Maintainer": "Stephanie M. Gogarten , Xiuwen Zheng , Adrienne Stilp ", "source.ver": "src/contrib/SeqVarTools_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SeqVarTools_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SeqVarTools_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SeqVarTools_1.12.0.tgz", "vignettes": [ "vignettes/SeqVarTools/inst/doc/SeqVarTools.pdf" ], "vignetteTitles": [ "Introduction to SeqVarTools" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SeqVarTools/inst/doc/SeqVarTools.R" ], "importsMe": [ "GENESIS" ] }, "sevenbridges": { "Package": "sevenbridges", "Version": "1.4.9", "Depends": [ "methods", "utils", "stats" ], "Imports": [ "httr", "jsonlite", "yaml", "objectProperties", "stringr", "S4Vectors", "docopt", "curl", "liftr", "uuid", "dplyr", "shiny (>= 0.13)", "miniUI (>= 0.1.1)", "rstudioapi (>= 0.5)" ], "Suggests": [ "knitr", "rmarkdown", "testthat", "readr", "clipr" ], "License": "Apache License 2.0 | file LICENSE", "MD5sum": "46d6996a0d923b034f31ffbad17db69e", "NeedsCompilation": "no", "Title": "Seven Bridges Platform API Client and Common Workflow Language Tool Builder in R", "Description": "R client and utilities for Seven Bridges platform API, from Cancer Genomics Cloud to other Seven Bridges supported platforms.", "biocViews": [ "DataImport", "Software", "ThirdPartyClient" ], "Author": "Nan Xiao [aut, cre], Dusan Randjelovic [aut], Emile Young [ctb], Tengfei Yin [aut], Seven Bridges Genomics [cph]", "Maintainer": "Nan Xiao ", "URL": "https://www.sevenbridges.com, https://sbg.github.io/sevenbridges-r/, https://github.com/sbg/sevenbridges-r", "VignetteBuilder": "knitr", "BugReports": "https://github.com/sbg/sevenbridges-r/issues", "source.ver": "src/contrib/sevenbridges_1.4.9.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/sevenbridges_1.4.9.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/sevenbridges_1.4.9.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/sevenbridges_1.4.9.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/sevenbridges/inst/doc/api.R", "vignettes/sevenbridges/inst/doc/apps.R", "vignettes/sevenbridges/inst/doc/bioc-workflow.R", "vignettes/sevenbridges/inst/doc/cgc-sparql.R", "vignettes/sevenbridges/inst/doc/docker.R", "vignettes/sevenbridges/inst/doc/rstudio.R" ], "htmlDocs": [ "vignettes/sevenbridges/inst/doc/api.html", "vignettes/sevenbridges/inst/doc/apps.html", "vignettes/sevenbridges/inst/doc/bioc-workflow.html", "vignettes/sevenbridges/inst/doc/cgc-sparql.html", "vignettes/sevenbridges/inst/doc/docker.html", "vignettes/sevenbridges/inst/doc/rstudio.html" ], "htmlTitles": [ "Complete Guide for Seven Bridges API R Client", "Describe and Execute CWL Tools/Workflows in R", "Master Tutorial: Use R for Cancer Genomics Cloud", "Find Data on CGC via Data Exploerer, SPARQL, and Datasets API", "Creating Your Docker Container and Command Line Interface (with docopt)", "IDE Container: RStudio Server, Shiny Server, and More" ] }, "SGSeq": { "Package": "SGSeq", "Version": "1.8.1", "Depends": [ "IRanges", "GenomicRanges (>= 1.23.21)", "Rsamtools", "SummarizedExperiment", "methods" ], "Imports": [ "AnnotationDbi", "BiocGenerics", "Biostrings", "GenomicAlignments", "GenomicFeatures", "GenomeInfoDb", "RUnit", "S4Vectors (>= 0.9.39)", "grDevices", "graphics", "igraph", "parallel", "rtracklayer", "stats" ], "Suggests": [ "BiocStyle", "BSgenome.Hsapiens.UCSC.hg19", "TxDb.Hsapiens.UCSC.hg19.knownGene", "knitr", "rmarkdown" ], "License": "Artistic-2.0", "MD5sum": "28c53d733f974c453d07fa15966d5fdf", "NeedsCompilation": "no", "Title": "Splice event prediction and quantification from RNA-seq data", "Description": "SGSeq is a software package for analyzing splice events from RNA-seq data. Input data are sequence reads mapped to a reference genome in BAM format. Genes are represented as a genome-wide splice graph, which can be obtained from existing annotation or can be predicted from the data. Splice events are identified from the graph and are quantified locally using structurally compatible reads at the start or end of each splice variant. The package includes functions for splice event prediction, quantification, visualization and interpretation.", "biocViews": [ "AlternativeSplicing", "RNASeq", "Software", "Transcription" ], "Author": "Leonard Goldstein", "Maintainer": "Leonard Goldstein ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/SGSeq_1.8.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SGSeq_1.8.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SGSeq_1.8.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SGSeq_1.8.1.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SGSeq/inst/doc/SGSeq.R" ], "htmlDocs": [ "vignettes/SGSeq/inst/doc/SGSeq.html" ], "htmlTitles": [ "SGSeq" ] }, "shinyMethyl": { "Package": "shinyMethyl", "Version": "1.10.0", "Depends": [ "methods", "BiocGenerics (>= 0.3.2)", "shiny (>= 0.13.2)", "minfi (>= 1.18.2)", "IlluminaHumanMethylation450kmanifest", "matrixStats", "R (>= 3.0.0)" ], "Imports": [ "RColorBrewer" ], "Suggests": [ "shinyMethylData", "minfiData", "BiocStyle", "RUnit", "digest", "knitr" ], "License": "Artistic-2.0", "MD5sum": "93e712471cf35f44fc54b3a2fa0055a2", "NeedsCompilation": "no", "Title": "Interactive visualization for Illumina methylation arrays", "Description": "Interactive tool for visualizing Illumina methylation array data. Both the 450k and EPIC array are supported.", "biocViews": [ "DNAMethylation", "Microarray", "Preprocessing", "QualityControl", "Software", "TwoChannel" ], "Author": "Jean-Philippe Fortin [cre, aut], Kasper Daniel Hansen [aut]", "Maintainer": "Jean-Philippe Fortin ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/shinyMethyl_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/shinyMethyl_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/shinyMethyl_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/shinyMethyl_1.10.0.tgz", "vignettes": [ "vignettes/shinyMethyl/inst/doc/shinyMethyl.pdf" ], "vignetteTitles": [ "shinyMethyl: interactive visualization of Illumina 450K methylation arrays" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/shinyMethyl/inst/doc/shinyMethyl.R" ] }, "shinyTANDEM": { "Package": "shinyTANDEM", "Version": "1.12.0", "Depends": [ "rTANDEM (>= 1.3.5)", "shiny", "mixtools", "methods", "xtable" ], "License": "GPL-3", "MD5sum": "574e993c0f0aee7736f16eabd3c433fe", "NeedsCompilation": "no", "Title": "Provides a GUI for rTANDEM", "Description": "This package provides a GUI interface for rTANDEM. The GUI is primarily designed to visualize rTANDEM result object or result xml files. But it will also provides an interface for creating parameter objects, launching searches or performing conversions between R objects and xml files.", "biocViews": [ "MassSpectrometry", "Proteomics", "Software" ], "Author": "Frederic Fournier , Arnaud Droit ", "Maintainer": "Frederic Fournier ", "source.ver": "src/contrib/shinyTANDEM_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/shinyTANDEM_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/shinyTANDEM_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/shinyTANDEM_1.12.0.tgz", "vignettes": [ "vignettes/shinyTANDEM/inst/doc/shinyTANDEM.pdf" ], "vignetteTitles": [ "shinyTANDEM user guide" ], "hasREADME": true, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false }, "ShortRead": { "Package": "ShortRead", "Version": "1.32.1", "Depends": [ "BiocGenerics (>= 0.11.3)", "BiocParallel", "Biostrings (>= 2.37.1)", "Rsamtools (>= 1.21.4)", "GenomicAlignments (>= 1.5.4)" ], "Imports": [ "Biobase", "S4Vectors (>= 0.7.1)", "IRanges (>= 2.3.7)", "GenomeInfoDb (>= 1.1.19)", "GenomicRanges (>= 1.21.6)", "hwriter", "methods", "zlibbioc", "lattice", "latticeExtra" ], "LinkingTo": [ "S4Vectors", "IRanges", "XVector", "Biostrings" ], "Suggests": [ "BiocStyle", "RUnit", "biomaRt", "GenomicFeatures", "yeastNagalakshmi" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "471dc8d60988ff8de17e0c4c4d60ecfa", "NeedsCompilation": "yes", "Title": "FASTQ input and manipulation", "Description": "This package implements sampling, iteration, and input of FASTQ files. The package includes functions for filtering and trimming reads, and for generating a quality assessment report. Data are represented as DNAStringSet-derived objects, and easily manipulated for a diversity of purposes. The package also contains legacy support for early single-end, ungapped alignment formats.", "biocViews": [ "DataImport", "QualityControl", "Sequencing", "Software" ], "Author": "Martin Morgan, Michael Lawrence, Simon Anders", "Maintainer": "Bioconductor Package Maintainer ", "source.ver": "src/contrib/ShortRead_1.32.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ShortRead_1.32.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ShortRead_1.32.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ShortRead_1.32.1.tgz", "vignettes": [ "vignettes/ShortRead/inst/doc/Overview.pdf" ], "vignetteTitles": [ "An introduction to ShortRead" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ShortRead/inst/doc/Overview.R" ], "dependsOnMe": [ "chipseq", "EatonEtAlChIPseq", "EDASeq", "girafe", "HTSeqGenie", "nucleR", "OTUbase", "Rqc", "rSFFreader", "segmentSeq", "systemPipeR" ], "importsMe": [ "ArrayExpressHTS", "BEAT", "chipseq", "ChIPseqR", "ChIPsim", "dada2", "easyRNASeq", "GOTHiC", "IONiseR", "metagenomeFeatures", "QuasR", "R453Plus1Toolbox", "RSVSim" ], "suggestsMe": [ "BiocParallel", "CSAR", "DBChIP", "GenomicAlignments", "Genominator", "HiCDataLymphoblast", "PICS", "PING", "Repitools", "RnaSeqTutorial", "Rsamtools", "S4Vectors", "yeastRNASeq" ] }, "SICtools": { "Package": "SICtools", "Version": "1.4.0", "Depends": [ "R (>= 3.0.0)", "methods", "Rsamtools (>= 1.18.1)", "doParallel (>= 1.0.8)", "Biostrings (>= 2.32.1)", "stringr (>= 0.6.2)", "matrixStats (>= 0.10.0)", "plyr (>= 1.8.3)", "GenomicRanges (>= 1.22.4)", "IRanges (>= 2.4.8)" ], "Suggests": [ "knitr", "RUnit", "BiocGenerics" ], "License": "GPL (>=2)", "MD5sum": "3febcbd21bc0517c778c660326b277ff", "NeedsCompilation": "yes", "Title": "Find SNV/Indel differences between two bam files with near relationship", "Description": "This package is to find SNV/Indel differences between two bam files with near relationship in a way of pairwise comparison thourgh each base position across the genome region of interest. The difference is inferred by fisher test and euclidean distance, the input of which is the base count (A,T,G,C) in a given position and read counts for indels that span no less than 2bp on both sides of indel region.", "biocViews": [ "Alignment", "Coverage", "DataImport", "QualityControl", "SNP", "SequenceMatching", "Sequencing", "Software", "VariantDetection" ], "Author": "Xiaobin Xing, Wu Wei", "Maintainer": "Xiaobin Xing ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/SICtools_1.4.0.tar.gz", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SICtools_1.4.0.tgz", "vignettes": [ "vignettes/SICtools/inst/doc/SICtools.pdf" ], "vignetteTitles": [ "Using SICtools" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SICtools/inst/doc/SICtools.R" ] }, "sigaR": { "Package": "sigaR", "Version": "1.22.0", "Depends": [ "Biobase", "CGHbase", "methods", "mvtnorm" ], "Imports": [ "corpcor (>= 1.6.2)", "graphics", "igraph", "limma", "marray", "MASS", "penalized", "quadprog", "snowfall", "stats" ], "Suggests": [ "CGHcall" ], "License": "GPL (>= 2)", "MD5sum": "29779a98b5a8da70ddcb0f37a8473680", "NeedsCompilation": "no", "Title": "Statistics for Integrative Genomics Analyses in R", "Description": "Facilitates the joint analysis of high-throughput data from multiple molecular levels. Contains functions for manipulation of objects, various analysis types, and some visualization.", "biocViews": [ "DifferentialExpression", "GeneExpression", "Microarray", "Pathways", "Software", "aCGH" ], "Author": "Wessel N. van Wieringen ", "Maintainer": "Wessel N. van Wieringen ", "URL": "http://www.few.vu.nl/~wvanwie", "source.ver": "src/contrib/sigaR_1.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/sigaR_1.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/sigaR_1.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/sigaR_1.22.0.tgz", "vignettes": [ "vignettes/sigaR/inst/doc/sigaR.pdf" ], "vignetteTitles": [ "sigaR" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/sigaR/inst/doc/sigaR.R" ], "dependsOnMe": [ "HCsnip" ] }, "SigCheck": { "Package": "SigCheck", "Version": "2.6.0", "Depends": [ "R (>= 3.2.0)", "MLInterfaces", "Biobase", "e1071", "BiocParallel", "survival" ], "Imports": [ "graphics", "stats", "utils", "methods" ], "Suggests": [ "BiocStyle", "breastCancerNKI", "qusage" ], "License": "Artistic-2.0", "MD5sum": "21fd89535278cd85d37f726ef6349a95", "NeedsCompilation": "no", "Title": "Check a gene signature's prognostic performance against random signatures, known signatures, and permuted data/metadata", "Description": "While gene signatures are frequently used to predict phenotypes (e.g. predict prognosis of cancer patients), it it not always clear how optimal or meaningful they are (cf David Venet, Jacques E. Dumont, and Vincent Detours' paper \"Most Random Gene Expression Signatures Are Significantly Associated with Breast Cancer Outcome\"). Based on suggestions in that paper, SigCheck accepts a data set (as an ExpressionSet) and a gene signature, and compares its performance on survival and/or classification tasks against a) random gene signatures of the same length; b) known, related and unrelated gene signatures; and c) permuted data and/or metadata.", "biocViews": [ "Classification", "GeneExpression", "GeneSetEnrichment", "Software" ], "Author": "Rory Stark and Justin Norden", "Maintainer": "Rory Stark ", "source.ver": "src/contrib/SigCheck_2.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SigCheck_2.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SigCheck_2.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SigCheck_2.6.0.tgz", "vignettes": [ "vignettes/SigCheck/inst/doc/SigCheck.pdf" ], "vignetteTitles": [ "Checking gene expression signatures against random and known signatures with SigCheck" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SigCheck/inst/doc/SigCheck.R" ] }, "SigFuge": { "Package": "SigFuge", "Version": "1.12.0", "Depends": [ "R (>= 3.1.1)", "GenomicRanges" ], "Imports": [ "ggplot2", "matlab", "reshape", "sigclust" ], "Suggests": [ "org.Hs.eg.db", "prebsdata", "Rsamtools (>= 1.17.0)", "TxDb.Hsapiens.UCSC.hg19.knownGene", "BiocStyle" ], "License": "GPL-3", "MD5sum": "b35369ad06032b23aa8876a59ee89743", "NeedsCompilation": "no", "Title": "SigFuge", "Description": "Algorithm for testing significance of clustering in RNA-seq data.", "biocViews": [ "Clustering", "RNASeq", "Software", "Visualization" ], "Author": "Patrick Kimes, Christopher Cabanski", "Maintainer": "Patrick Kimes ", "source.ver": "src/contrib/SigFuge_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SigFuge_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SigFuge_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SigFuge_1.12.0.tgz", "vignettes": [ "vignettes/SigFuge/inst/doc/SigFuge.pdf" ], "vignetteTitles": [ "SigFuge Tutorial" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SigFuge/inst/doc/SigFuge.R" ] }, "siggenes": { "Package": "siggenes", "Version": "1.48.0", "Depends": [ "methods", "Biobase", "multtest", "splines", "graphics" ], "Imports": [ "stats4" ], "Suggests": [ "affy", "annotate", "genefilter", "KernSmooth", "scrime (>= 1.2.5)" ], "License": "LGPL (>= 2)", "MD5sum": "768b519560144ba058352bb58747f426", "NeedsCompilation": "no", "Title": "Multiple testing using SAM and Efron's empirical Bayes approaches", "Description": "Identification of differentially expressed genes and estimation of the False Discovery Rate (FDR) using both the Significance Analysis of Microarrays (SAM) and the Empirical Bayes Analyses of Microarrays (EBAM).", "biocViews": [ "DifferentialExpression", "ExonArray", "GeneExpression", "Microarray", "MultipleComparison", "SNP", "Software" ], "Author": "Holger Schwender", "Maintainer": "Holger Schwender ", "source.ver": "src/contrib/siggenes_1.48.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/siggenes_1.48.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/siggenes_1.48.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/siggenes_1.48.0.tgz", "vignettes": [ "vignettes/siggenes/inst/doc/siggenes.pdf" ], "vignetteTitles": [ "siggenes Manual" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/siggenes/inst/doc/siggenes.R" ], "dependsOnMe": [ "KCsmart", "oneChannelGUI" ], "importsMe": [ "charm", "DeSousa2013", "GeneSelector", "minfi" ], "suggestsMe": [ "GeneSelector", "logicFS", "trio", "XDE" ] }, "sights": { "Package": "sights", "Version": "1.0.0", "Depends": [ "R(>= 3.3)" ], "Imports": [ "MASS(>= 7.3)", "qvalue(>= 2.2)", "ggplot2(>= 2.0)", "reshape2(>= 1.4)", "lattice(>= 0.2)", "stats(>= 3.3)" ], "Suggests": [ "testthat", "knitr", "rmarkdown", "ggthemes", "gridExtra", "xlsx" ], "License": "GPL-3 | file LICENSE", "MD5sum": "0369de5c1689e91a55f1a4bd0d5d8592", "NeedsCompilation": "no", "Title": "Statistics and dIagnostic Graphs for HTS", "Description": "SIGHTS is a suite of normalization methods, statistical tests, and diagnostic graphical tools for high throughput screening (HTS) assays. HTS assays use microtitre plates to screen large libraries of compounds for their biological, chemical, or biochemical activity.", "biocViews": [ "BatchEffect", "CellBasedAssays", "MicrotitrePlateAssay", "MultipleComparison", "Normalization", "Preprocessing", "QualityControl", "Software", "Visualization" ], "Author": "Elika Garg [aut, cre], Carl Murie [aut], Heydar Ensha [ctb], Robert Nadon [aut]", "Maintainer": "Elika Garg ", "URL": "https://eg-r.github.io/sights/", "VignetteBuilder": "knitr", "BugReports": "https://github.com/eg-r/sights/issues", "source.ver": "src/contrib/sights_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/sights_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/sights_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/sights_1.0.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/sights/inst/doc/sights.R" ], "htmlDocs": [ "vignettes/sights/inst/doc/sights.html" ], "htmlTitles": [ "Using **SIGHTS** R-package" ] }, "signeR": { "Package": "signeR", "Version": "1.0.1", "Imports": [ "BiocGenerics", "Biostrings", "BSgenome (>= 1.36.3)", "class", "graphics", "grDevices", "GenomicRanges", "nloptr", "methods", "NMF", "stats", "utils", "VariantAnnotation", "PMCMR" ], "LinkingTo": [ "Rcpp", "RcppArmadillo" ], "Suggests": [ "knitr", "rtracklayer", "BSgenome.Hsapiens.UCSC.hg19" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "edc96646e9c9e8f88a0a147f4662095b", "NeedsCompilation": "yes", "Title": "Empirical Bayesian approach to mutational signature discovery", "Description": "The signeR package provides an empirical Bayesian approach to mutational signature discovery. It is designed to analyze single nucleotide variaton (SNV) counts in cancer genomes, but can also be applied to other features as well. Functionalities to characterize signatures or genome samples according to exposure patterns are also provided.", "biocViews": [ "GenomicVariation", "Software", "SomaticMutation", "StatisticalMethod", "Visualization" ], "Author": "Rafael Rosales, Rodrigo Drummond, Renan Valieris, Israel Tojal da Silva", "Maintainer": "Renan Valieris ", "SystemRequirements": "C++11", "VignetteBuilder": "knitr", "source.ver": "src/contrib/signeR_1.0.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/signeR_1.0.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/signeR_1.0.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/signeR_1.0.1.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/signeR/inst/doc/signeR-vignette.R" ], "htmlDocs": [ "vignettes/signeR/inst/doc/signeR-vignette.html" ], "htmlTitles": [ "signeR" ] }, "sigPathway": { "Package": "sigPathway", "Version": "1.42.0", "Depends": [ "R (>= 2.10)" ], "Suggests": [ "hgu133a.db (>= 1.10.0)", "XML (>= 1.6-3)", "AnnotationDbi (>= 1.3.12)" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "0a6d6d8eb343e207938bc1bc0d36ba81", "NeedsCompilation": "yes", "Title": "Pathway Analysis", "Description": "Conducts pathway analysis by calculating the NT_k and NE_k statistics as described in Tian et al. (2005)", "biocViews": [ "DifferentialExpression", "MultipleComparison", "Software" ], "Author": "Weil Lai (optimized R and C code), Lu Tian and Peter Park (algorithm development and initial R code)", "Maintainer": "Weil Lai ", "URL": "http://www.pnas.org/cgi/doi/10.1073/pnas.0506577102, http://www.chip.org/~ppark/Supplements/PNAS05.html", "source.ver": "src/contrib/sigPathway_1.42.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/sigPathway_1.42.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/sigPathway_1.42.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/sigPathway_1.42.0.tgz", "vignettes": [ "vignettes/sigPathway/inst/doc/sigPathway-vignette.pdf" ], "vignetteTitles": [ "sigPathway" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/sigPathway/inst/doc/sigPathway-vignette.R" ], "dependsOnMe": [ "tRanslatome" ] }, "sigsquared": { "Package": "sigsquared", "Version": "1.6.0", "Depends": [ "R (>= 3.2.0)", "methods" ], "Imports": [ "Biobase", "survival" ], "Suggests": [ "RUnit", "BiocGenerics" ], "License": "GPL version 3", "MD5sum": "4aca0ec23f094667ba526e06ef09d0b1", "NeedsCompilation": "no", "Title": "Gene signature generation for functionally validated signaling pathways", "Description": "By leveraging statistical properties (log-rank test for survival) of patient cohorts defined by binary thresholds, poor-prognosis patients are identified by the sigsquared package via optimization over a cost function reducing type I and II error.", "Author": "UnJin Lee", "Maintainer": "UnJin Lee ", "source.ver": "src/contrib/sigsquared_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/sigsquared_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/sigsquared_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/sigsquared_1.6.0.tgz", "vignettes": [ "vignettes/sigsquared/inst/doc/sigsquared.pdf" ], "vignetteTitles": [ "SigSquared" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/sigsquared/inst/doc/sigsquared.R" ], "biocViews": [ "Software" ] }, "SIM": { "Package": "SIM", "Version": "1.44.0", "Depends": [ "R (>= 2.4)", "quantreg" ], "Imports": [ "graphics", "stats", "globaltest", "quantsmooth" ], "Suggests": [ "biomaRt", "RColorBrewer" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "e79051e298b28ff3a6779dde94b220a1", "NeedsCompilation": "yes", "Title": "Integrated Analysis on two human genomic datasets", "Description": "Finds associations between two human genomic datasets.", "biocViews": [ "Microarray", "Software", "Visualization" ], "Author": "Renee X. de Menezes and Judith M. Boer", "Maintainer": "Renee X. de Menezes ", "source.ver": "src/contrib/SIM_1.44.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SIM_1.44.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SIM_1.44.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SIM_1.44.0.tgz", "vignettes": [ "vignettes/SIM/inst/doc/SIM.pdf" ], "vignetteTitles": [ "SIM vignette" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SIM/inst/doc/SIM.R" ] }, "SIMAT": { "Package": "SIMAT", "Version": "1.6.1", "Depends": [ "R (>= 3.3.0)", "Rcpp (>= 0.11.3)" ], "Imports": [ "mzR", "ggplot2", "grid", "reshape2" ], "Suggests": [ "RUnit", "BiocGenerics" ], "License": "GPL-2", "MD5sum": "4124f0d02af587eb447beefb34c8e0f0", "NeedsCompilation": "no", "Title": "GC-SIM-MS data processing and alaysis tool", "Description": "This package provides a pipeline for analysis of GC-MS data acquired in selected ion monitoring (SIM) mode. The tool also provides a guidance in choosing appropriate fragments for the targets of interest by using an optimization algorithm. This is done by considering overlapping peaks from a provided library by the user.", "biocViews": [ "MassSpectrometry", "Metabolomics", "Software" ], "Author": "Mo R. Nezami Ranjbar ", "Maintainer": "Mo R. Nezami Ranjbar ", "URL": "http://omics.georgetown.edu/SIMAT.html", "source.ver": "src/contrib/SIMAT_1.6.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SIMAT_1.6.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SIMAT_1.6.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SIMAT_1.6.1.tgz", "vignettes": [ "vignettes/SIMAT/inst/doc/SIMAT-vignette.pdf" ], "vignetteTitles": [ "SIMAT Usage" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SIMAT/inst/doc/SIMAT-vignette.R" ] }, "SimBindProfiles": { "Package": "SimBindProfiles", "Version": "1.12.0", "Depends": [ "R (>= 2.10)", "methods", "Ringo" ], "Imports": [ "limma", "mclust", "Biobase" ], "License": "GPL-3", "MD5sum": "6a34b39e22b970be8e68d14dcbb8e262", "NeedsCompilation": "no", "Title": "Similar Binding Profiles", "Description": "SimBindProfiles identifies common and unique binding regions in genome tiling array data. This package does not rely on peak calling, but directly compares binding profiles processed on the same array platform. It implements a simple threshold approach, thus allowing retrieval of commonly and differentially bound regions between datasets as well as events of compensation and increased binding.", "biocViews": [ "Microarray", "Software" ], "Author": "Bettina Fischer, Enrico Ferrero, Robert Stojnic, Steve Russell", "Maintainer": "Bettina Fischer ", "source.ver": "src/contrib/SimBindProfiles_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SimBindProfiles_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SimBindProfiles_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SimBindProfiles_1.12.0.tgz", "vignettes": [ "vignettes/SimBindProfiles/inst/doc/SimBindProfiles.pdf" ], "vignetteTitles": [ "SimBindProfiles: Similar Binding Profiles, identifies common and unique regions in array genome tiling array data" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SimBindProfiles/inst/doc/SimBindProfiles.R" ] }, "similaRpeak": { "Package": "similaRpeak", "Version": "1.6.0", "Depends": [ "R6 (>= 2.0)" ], "Imports": [ "rtracklayer", "GenomicAlignments", "Rsamtools", "stats" ], "Suggests": [ "RUnit", "BiocGenerics", "knitr", "BiocStyle" ], "License": "Artistic-2.0", "MD5sum": "7bf9a042deba74909e28ce5485ccc3b7", "NeedsCompilation": "no", "Title": "Metrics to estimate a level of similarity between two ChIP-Seq profiles", "Description": "This package calculates metrics which assign a level of similarity between ChIP-Seq profiles.", "biocViews": [ "BiologicalQuestion", "ChIPSeq", "DifferentialExpression", "Genetics", "MultipleComparison", "Software" ], "Author": "Astrid Deschenes [cre, aut], Elsa Bernatchez [aut], Charles Joly Beauparlant [aut], Fabien Claude Lamaze [aut], Rawane Samb [aut], Pascal Belleau [aut], Arnaud Droit [aut]", "Maintainer": "Astrid Louise Deschenes ", "URL": "https://github.com/adeschen/similaRpeak", "VignetteBuilder": "knitr", "BugReports": "https://github.com/adeschen/similaRpeak/issues", "source.ver": "src/contrib/similaRpeak_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/similaRpeak_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/similaRpeak_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/similaRpeak_1.6.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/similaRpeak/inst/doc/similaRpeak.R" ], "htmlDocs": [ "vignettes/similaRpeak/inst/doc/similaRpeak.html" ], "htmlTitles": [ "Similarity between two ChIP-Seq profiles" ], "suggestsMe": [ "metagene" ] }, "SIMLR": { "Package": "SIMLR", "Version": "1.0.1", "Depends": [ "R (>= 3.3)" ], "Imports": [ "parallel", "Matrix", "stats", "methods" ], "Suggests": [ "BiocGenerics", "BiocStyle", "testthat", "knitr", "igraph", "scran" ], "License": "file LICENSE", "Archs": "i386, x64", "MD5sum": "97454275a744a1a434694fbf73e4fc64", "NeedsCompilation": "yes", "Title": "SIMLR: Single-cell Interpretation via Multi-kernel LeaRning", "Description": "Single-cell RNA-seq technologies enable high throughput gene expression measurement of individual cells, and allow the discovery of heterogeneity within cell populations. Measurement of cell-to-cell gene expression similarity is critical to identification, visualization and analysis of cell populations. However, single-cell data introduce challenges to conventional measures of gene expression similarity because of the high level of noise, outliers and dropouts. We develop a novel similarity-learning framework, SIMLR (Single-cell Interpretation via Multi-kernel LeaRning), which learns an appropriate distance metric from the data for dimension reduction, clustering and visualization. SIMLR is capable of separating known subpopulations more accurately in single-cell data sets than do existing dimension reduction methods. Additionally, SIMLR demonstrates high sensitivity and accuracy on high-throughput peripheral blood mononuclear cells (PBMC) data sets generated by the GemCode single-cell technology from 10x Genomics.", "biocViews": [ "Clustering", "GeneExpression", "Sequencing", "SingleCell", "Software" ], "Author": "Bo Wang [aut], Daniele Ramazzotti [aut, cre], Luca De Sano [aut], Junjie Zhu [ctb], Emma Pierson [ctb], Serafim Batzoglou [ctb]", "Maintainer": "Daniele Ramazzotti ", "URL": "https://github.com/BatzoglouLabSU/SIMLR", "VignetteBuilder": "knitr", "BugReports": "https://github.com/BatzoglouLabSU/SIMLR", "source.ver": "src/contrib/SIMLR_1.0.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SIMLR_1.0.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SIMLR_1.0.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SIMLR_1.0.1.tgz", "vignettes": [ "vignettes/SIMLR/inst/doc/SIMLR.pdf" ], "vignetteTitles": [ "An R Package for todo" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/SIMLR/inst/doc/SIMLR.R" ] }, "simpleaffy": { "Package": "simpleaffy", "Version": "2.50.0", "Depends": [ "R (>= 2.0.0)", "methods", "utils", "grDevices", "graphics", "stats", "BiocGenerics (>= 0.1.12)", "Biobase", "affy (>= 1.33.6)", "genefilter", "gcrma" ], "Imports": [ "methods", "utils", "grDevices", "graphics", "stats", "BiocGenerics", "Biobase", "affy", "genefilter", "gcrma" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "128f6616c02f98c586bbf70d1ad1ce26", "NeedsCompilation": "yes", "Title": "Very simple high level analysis of Affymetrix data", "Description": "Provides high level functions for reading Affy .CEL files, phenotypic data, and then computing simple things with it, such as t-tests, fold changes and the like. Makes heavy use of the affy library. Also has some basic scatter plot functions and mechanisms for generating high resolution journal figures...", "biocViews": [ "Annotation", "DataImport", "DifferentialExpression", "Microarray", "OneChannel", "Preprocessing", "QualityControl", "ReportWriting", "Software", "Transcription", "Visualization" ], "Author": "Crispin J Miller", "Maintainer": "Crispin Miller ", "URL": "http://www.bioconductor.org, http://bioinformatics.picr.man.ac.uk/simpleaffy/", "source.ver": "src/contrib/simpleaffy_2.50.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/simpleaffy_2.50.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/simpleaffy_2.50.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/simpleaffy_2.50.0.tgz", "vignettes": [ "vignettes/simpleaffy/inst/doc/simpleAffy.pdf" ], "vignetteTitles": [ "simpleaffy primer" ], "hasREADME": true, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/simpleaffy/inst/doc/simpleAffy.R" ], "dependsOnMe": [ "yaqcaffy" ], "importsMe": [ "affyQCReport", "arrayMvout" ], "suggestsMe": [ "AffyExpress", "ArrayTools", "ELBOW" ] }, "simulatorZ": { "Package": "simulatorZ", "Version": "1.8.0", "Depends": [ "R (>= 3.1)", "methods", "BiocGenerics", "Biobase", "SummarizedExperiment", "survival", "CoxBoost" ], "Imports": [ "graphics", "stats", "gbm", "Hmisc", "S4Vectors", "IRanges", "GenomicRanges" ], "Suggests": [ "RUnit", "BiocStyle", "curatedOvarianData", "parathyroidSE", "superpc" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "52eff5823b7012165f556e7582ab84c4", "NeedsCompilation": "yes", "Title": "Simulator for Collections of Independent Genomic Data Sets", "Description": "simulatorZ is a package intended primarily to simulate collections of independent genomic data sets, as well as performing training and validation with predicting algorithms. It supports ExpressionSet and RangedSummarizedExperiment objects.", "biocViews": [ "Software", "Survival" ], "Author": "Yuqing Zhang, Christoph Bernau, Levi Waldron", "Maintainer": "Yuqing Zhang ", "URL": "https://github.com/zhangyuqing/simulatorZ", "BugReports": "https://github.com/zhangyuqing/simulatorZ", "source.ver": "src/contrib/simulatorZ_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/simulatorZ_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/simulatorZ_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/simulatorZ_1.8.0.tgz", "vignettes": [ "vignettes/simulatorZ/inst/doc/simulatorZ-vignette.pdf" ], "vignetteTitles": [ "SimulatorZ" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/simulatorZ/inst/doc/simulatorZ-vignette.R" ], "suggestsMe": [ "doppelgangR" ] }, "sincell": { "Package": "sincell", "Version": "1.6.0", "Depends": [ "R (>= 3.0.2)", "igraph" ], "Imports": [ "Rcpp (>= 0.11.2)", "entropy", "scatterplot3d", "MASS", "TSP", "ggplot2", "reshape2", "fields", "proxy", "parallel", "Rtsne", "fastICA", "cluster", "statmod" ], "LinkingTo": [ "Rcpp" ], "Suggests": [ "BiocStyle", "knitr", "biomaRt", "stringr", "monocle" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "232d71c7695eddcf1def9bd5c831f56f", "NeedsCompilation": "yes", "Title": "R package for the statistical assessment of cell state hierarchies from single-cell RNA-seq data", "Description": "Cell differentiation processes are achieved through a continuum of hierarchical intermediate cell-states that might be captured by single-cell RNA seq. Existing computational approaches for the assessment of cell-state hierarchies from single-cell data might be formalized under a general workflow composed of i) a metric to assess cell-to-cell similarities (combined or not with a dimensionality reduction step), and ii) a graph-building algorithm (optionally making use of a cells-clustering step). Sincell R package implements a methodological toolbox allowing flexible workflows under such framework. Furthermore, Sincell contributes new algorithms to provide cell-state hierarchies with statistical support while accounting for stochastic factors in single-cell RNA seq. Graphical representations and functional association tests are provided to interpret hierarchies.", "biocViews": [ "BiomedicalInformatics", "CellBiology", "Clustering", "FunctionalGenomics", "GeneExpression", "GeneSetEnrichment", "GraphAndNetwork", "RNASeq", "Sequencing", "Software", "SystemsBiology", "Visualization" ], "Author": "Miguel Julia , Amalio Telenti , Antonio Rausell ", "Maintainer": "Miguel Julia , Antonio Rausell", "URL": "http://bioconductor.org/", "VignetteBuilder": "knitr", "source.ver": "src/contrib/sincell_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/sincell_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/sincell_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/sincell_1.6.0.tgz", "vignettes": [ "vignettes/sincell/inst/doc/sincell-vignette.pdf" ], "vignetteTitles": [ "Sincell: Analysis of cell state hierarchies from single-cell RNA-seq" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/sincell/inst/doc/sincell-vignette.R" ] }, "SISPA": { "Package": "SISPA", "Version": "1.4.0", "Depends": [ "R (>= 3.2)", "genefilter", "GSVA", "changepoint" ], "Imports": [ "data.table", "plyr", "ggplot2" ], "Suggests": [ "knitr" ], "License": "GPL-2", "MD5sum": "3fd230d7cf47f0d638d8872c67d299f2", "NeedsCompilation": "no", "Title": "SISPA: Method for Sample Integrated Set Profile Analysis", "Description": "Sample Integrated Set Profile Analysis (SISPA) is a method designed to define sample groups with similar gene set enrichment profiles.", "biocViews": [ "GeneSetEnrichment", "GenomeWideAssociation", "Software" ], "Author": "Bhakti Dwivedi and Jeanne Kowalski", "Maintainer": "Bhakti Dwivedi ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/SISPA_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SISPA_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SISPA_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SISPA_1.4.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false }, "sizepower": { "Package": "sizepower", "Version": "1.44.0", "Depends": [ "stats" ], "License": "LGPL", "MD5sum": "a99d6780ebc4de677b8de589dcbd24f4", "NeedsCompilation": "no", "Title": "Sample Size and Power Calculation in Micorarray Studies", "Description": "This package has been prepared to assist users in computing either a sample size or power value for a microarray experimental study. The user is referred to the cited references for technical background on the methodology underpinning these calculations. This package provides support for five types of sample size and power calculations. These five types can be adapted in various ways to encompass many of the standard designs encountered in practice.", "biocViews": [ "Microarray", "Software" ], "Author": "Weiliang Qiu and Mei-Ling Ting Lee and George Alex Whitmore ", "Maintainer": "Weiliang Qiu ", "source.ver": "src/contrib/sizepower_1.44.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/sizepower_1.44.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/sizepower_1.44.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/sizepower_1.44.0.tgz", "vignettes": [ "vignettes/sizepower/inst/doc/sizepower.pdf" ], "vignetteTitles": [ "Sample Size and Power Calculation in Microarray Studies Using the \\Rpackage{sizepower} package" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/sizepower/inst/doc/sizepower.R" ], "suggestsMe": [ "oneChannelGUI" ] }, "skewr": { "Package": "skewr", "Version": "1.6.0", "Depends": [ "R (>= 3.1.1)", "methylumi", "wateRmelon", "mixsmsn", "IlluminaHumanMethylation450kmanifest" ], "Imports": [ "minfi", "IRanges", "RColorBrewer" ], "Suggests": [ "GEOquery", "knitr", "minfiData" ], "License": "GPL-2", "MD5sum": "5dcc49d863b92c01e61725360d6f204f", "NeedsCompilation": "no", "Title": "Visualize Intensities Produced by Illumina's Human Methylation 450k BeadChip", "Description": "The skewr package is a tool for visualizing the output of the Illumina Human Methylation 450k BeadChip to aid in quality control. It creates a panel of nine plots. Six of the plots represent the density of either the methylated intensity or the unmethylated intensity given by one of three subsets of the 485,577 total probes. These subsets include Type I-red, Type I-green, and Type II.The remaining three distributions give the density of the Beta-values for these same three subsets. Each of the nine plots optionally displays the distributions of the \"rs\" SNP probes and the probes associated with imprinted genes as series of 'tick' marks located above the x-axis.", "biocViews": [ "DNAMethylation", "Preprocessing", "QualityControl", "Software", "TwoChannel" ], "Author": "Ryan Putney [cre, aut], Steven Eschrich [aut], Anders Berglund [aut]", "Maintainer": "Ryan Putney ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/skewr_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/skewr_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/skewr_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/skewr_1.6.0.tgz", "vignettes": [ "vignettes/skewr/inst/doc/skewr.pdf" ], "vignetteTitles": [ "An Introduction to the skewr Package" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/skewr/inst/doc/skewr.R" ] }, "SLGI": { "Package": "SLGI", "Version": "1.34.0", "Depends": [ "R (>= 2.10)", "ScISI", "lattice" ], "Imports": [ "AnnotationDbi", "Biobase", "GO.db", "ScISI", "graphics", "lattice", "methods", "stats", "BiocGenerics" ], "Suggests": [ "GO.db", "org.Sc.sgd.db" ], "License": "Artistic-2.0", "MD5sum": "f4cdb630f665cd1048023dfe2bfc22c6", "NeedsCompilation": "no", "Title": "Synthetic Lethal Genetic Interaction", "Description": "A variety of data files and functions for the analysis of genetic interactions", "biocViews": [ "Genetics", "GraphAndNetwork", "Network", "Proteomics", "Software" ], "Author": "Nolwenn LeMeur, Zhen Jiang, Ting-Yuan Liu, Jess Mar and Robert Gentleman", "Maintainer": "Nolwenn Le Meur ", "source.ver": "src/contrib/SLGI_1.34.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SLGI_1.34.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SLGI_1.34.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SLGI_1.34.0.tgz", "vignettes": [ "vignettes/SLGI/inst/doc/SLGI.pdf" ], "vignetteTitles": [ "SLGI Vignette" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SLGI/inst/doc/SLGI.R" ], "dependsOnMe": [ "PCpheno" ] }, "SLqPCR": { "Package": "SLqPCR", "Version": "1.40.0", "Depends": [ "R(>= 2.4.0)" ], "Imports": [ "stats" ], "Suggests": [ "RColorBrewer" ], "License": "GPL (>= 2)", "MD5sum": "5747c5078125bb1ae0968e709b95a754", "NeedsCompilation": "no", "Title": "Functions for analysis of real-time quantitative PCR data at SIRS-Lab GmbH", "Description": "Functions for analysis of real-time quantitative PCR data at SIRS-Lab GmbH", "biocViews": [ "MicrotitrePlateAssay", "Software", "qPCR" ], "Author": "Matthias Kohl", "Maintainer": "Matthias Kohl ", "source.ver": "src/contrib/SLqPCR_1.40.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SLqPCR_1.40.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SLqPCR_1.40.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SLqPCR_1.40.0.tgz", "vignettes": [ "vignettes/SLqPCR/inst/doc/SLqPCR.pdf" ], "vignetteTitles": [ "SLqPCR" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SLqPCR/inst/doc/SLqPCR.R" ], "suggestsMe": [ "EasyqpcR" ] }, "SMAP": { "Package": "SMAP", "Version": "1.38.0", "Depends": [ "R (>= 2.10)", "methods" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "417f091f9fc8c877ffda4fea4557887a", "NeedsCompilation": "yes", "Title": "A Segmental Maximum A Posteriori Approach to Array-CGH Copy Number Profiling", "Description": "Functions and classes for DNA copy number profiling of array-CGH data", "biocViews": [ "CopyNumberVariation", "Microarray", "Software", "TwoChannel" ], "Author": "Robin Andersson ", "Maintainer": "Robin Andersson ", "source.ver": "src/contrib/SMAP_1.38.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SMAP_1.38.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SMAP_1.38.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SMAP_1.38.0.tgz", "vignettes": [ "vignettes/SMAP/inst/doc/SMAP.pdf" ], "vignetteTitles": [ "SMAP" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SMAP/inst/doc/SMAP.R" ] }, "SMITE": { "Package": "SMITE", "Version": "1.2.0", "Depends": [ "R (>= 3.3)", "GenomicRanges" ], "Imports": [ "scales", "plyr", "Hmisc", "AnnotationDbi", "org.Hs.eg.db", "ggplot2", "reactome.db", "KEGG.db", "BioNet", "goseq", "methods", "IRanges", "igraph", "Biobase", "tools", "S4Vectors", "geneLenDataBase", "grDevices", "graphics", "stats", "utils" ], "Suggests": [ "knitr" ], "License": "GPL (>=2)", "MD5sum": "54f540cd89ffdf18c957849910531797", "NeedsCompilation": "no", "Title": "Significance-based Modules Integrating the Transcriptome and Epigenome", "Description": "This package builds on the Epimods framework which facilitates finding weighted subnetworks (\"modules\") on Illumina Infinium 27k arrays using the SpinGlass algorithm, as implemented in the iGraph package. We have created a class of gene centric annotations associated with p-values and effect sizes and scores from any researchers prior statistical results to find functional modules.", "biocViews": [ "Coverage", "DifferentialExpression", "DifferentialMethylation", "GenomeAnnotation", "Network", "NetworkEnrichment", "RNASeq", "Sequencing", "Software", "SystemsBiology" ], "Author": "Neil Ari Wijetunga, Andrew Damon Johnston, John Murray Greally", "Maintainer": "Neil Ari Wijetunga , Andrew Damon Johnston ", "URL": "https://github.com/GreallyLab/SMITE", "VignetteBuilder": "knitr", "BugReports": "https://github.com/GreallyLab/SMITE/issues", "source.ver": "src/contrib/SMITE_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SMITE_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SMITE_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SMITE_1.2.0.tgz", "vignettes": [ "vignettes/SMITE/inst/doc/SMITE.pdf" ], "vignetteTitles": [ "SMITE Tutorial" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SMITE/inst/doc/SMITE.R" ] }, "SNAGEE": { "Package": "SNAGEE", "Version": "1.14.0", "Depends": [ "R (>= 2.6.0)", "SNAGEEdata" ], "Suggests": [ "ALL", "hgu95av2.db" ], "Enhances": [ "parallel" ], "License": "Artistic-2.0", "MD5sum": "c7a436033676da94295191c1e18349a9", "NeedsCompilation": "no", "Title": "Signal-to-Noise applied to Gene Expression Experiments", "Description": "Signal-to-Noise applied to Gene Expression Experiments. Signal-to-noise ratios can be used as a proxy for quality of gene expression studies and samples. The SNRs can be calculated on any gene expression data set as long as gene IDs are available, no access to the raw data files is necessary. This allows to flag problematic studies and samples in any public data set.", "biocViews": [ "Microarray", "OneChannel", "QualityControl", "Software", "TwoChannel" ], "Author": "David Venet ", "Maintainer": "David Venet ", "URL": "http://bioconductor.org/", "source.ver": "src/contrib/SNAGEE_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SNAGEE_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SNAGEE_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SNAGEE_1.14.0.tgz", "vignettes": [ "vignettes/SNAGEE/inst/doc/SNAGEE.pdf" ], "vignetteTitles": [ "SNAGEE Vignette" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SNAGEE/inst/doc/SNAGEE.R" ], "suggestsMe": [ "SNAGEEdata" ] }, "snapCGH": { "Package": "snapCGH", "Version": "1.44.0", "Depends": [ "limma", "DNAcopy", "methods" ], "Imports": [ "aCGH", "cluster", "DNAcopy", "GLAD", "graphics", "grDevices", "limma", "methods", "stats", "tilingArray", "utils" ], "License": "GPL", "Archs": "i386, x64", "MD5sum": "7497133fff5332ed6667af3a414da862", "NeedsCompilation": "yes", "Title": "Segmentation, normalisation and processing of aCGH data.", "Description": "Methods for segmenting, normalising and processing aCGH data; including plotting functions for visualising raw and segmented data for individual and multiple arrays.", "biocViews": [ "CopyNumberVariation", "Microarray", "Preprocessing", "Software", "TwoChannel" ], "Author": "Mike L. Smith, John C. Marioni, Steven McKinney, Thomas Hardcastle, Natalie P. Thorne", "Maintainer": "John Marioni ", "source.ver": "src/contrib/snapCGH_1.44.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/snapCGH_1.44.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/snapCGH_1.44.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/snapCGH_1.44.0.tgz", "vignettes": [ "vignettes/snapCGH/inst/doc/snapCGHguide.pdf" ], "vignetteTitles": [ "Segmentation Overview" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/snapCGH/inst/doc/snapCGHguide.R" ], "importsMe": [ "ADaCGH2" ], "suggestsMe": [ "beadarraySNP" ] }, "snm": { "Package": "snm", "Version": "1.22.0", "Depends": [ "R (>= 2.12.0)" ], "Imports": [ "corpcor", "lme4 (>= 1.0)", "splines" ], "License": "LGPL", "MD5sum": "24390ae2ada6cb97cbd0ba08171a04f7", "NeedsCompilation": "no", "Title": "Supervised Normalization of Microarrays", "Description": "SNM is a modeling strategy especially designed for normalizing high-throughput genomic data. The underlying premise of our approach is that your data is a function of what we refer to as study-specific variables. These variables are either biological variables that represent the target of the statistical analysis, or adjustment variables that represent factors arising from the experimental or biological setting the data is drawn from. The SNM approach aims to simultaneously model all study-specific variables in order to more accurately characterize the biological or clinical variables of interest.", "biocViews": [ "DifferentialExpression", "ExonArray", "GeneExpression", "Microarray", "MultiChannel", "MultipleComparison", "OneChannel", "Preprocessing", "QualityControl", "Software", "Transcription", "TwoChannel" ], "Author": "Brig Mecham and John D. Storey ", "Maintainer": "John D. Storey ", "source.ver": "src/contrib/snm_1.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/snm_1.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/snm_1.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/snm_1.22.0.tgz", "vignettes": [ "vignettes/snm/inst/doc/snm.pdf" ], "vignetteTitles": [ "snm Tutorial" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/snm/inst/doc/snm.R" ], "importsMe": [ "edge" ] }, "SNPchip": { "Package": "SNPchip", "Version": "2.20.0", "Depends": [ "R (>= 2.14.0)" ], "Imports": [ "methods", "graphics", "lattice", "grid", "foreach", "utils", "Biobase", "S4Vectors (>= 0.9.25)", "IRanges", "GenomeInfoDb", "GenomicRanges", "SummarizedExperiment", "oligoClasses (>= 1.31.1)" ], "Suggests": [ "crlmm (>= 1.17.14)", "RUnit" ], "Enhances": [ "doSNOW", "VanillaICE (>= 1.21.24)", "RColorBrewer" ], "License": "LGPL (>= 2)", "MD5sum": "3ad715bc239969c6ff4e690a71c58303", "NeedsCompilation": "no", "Title": "Visualizations for copy number alterations", "Description": "Functions for plotting SNP array data; maintained for historical reasons", "biocViews": [ "CopyNumberVariation", "GeneticVariability", "SNP", "Software", "Visualization" ], "Author": "Robert Scharpf and Ingo Ruczinski", "Maintainer": "Robert Scharpf ", "URL": "http://www.biostat.jhsph.edu/~iruczins/software/snpchip.html", "source.ver": "src/contrib/SNPchip_2.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SNPchip_2.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SNPchip_2.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SNPchip_2.20.0.tgz", "vignettes": [ "vignettes/SNPchip/inst/doc/PlottingIdiograms.pdf" ], "vignetteTitles": [ "Plotting Idiograms" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SNPchip/inst/doc/PlottingIdiograms.R" ], "dependsOnMe": [ "mBPCR" ], "importsMe": [ "crlmm", "phenoTest" ], "suggestsMe": [ "Category", "MinimumDistance", "oligoClasses", "VanillaICE" ] }, "SNPediaR": { "Package": "SNPediaR", "Version": "1.0.0", "Depends": [ "R (>= 3.0.0)" ], "Imports": [ "RCurl", "jsonlite" ], "Suggests": [ "BiocStyle", "knitr", "rmarkdown", "testthat" ], "License": "GPL-2", "MD5sum": "ba259fc9dd83f44322c53489a8f25116", "NeedsCompilation": "no", "Title": "Query data from SNPedia", "Description": "SNPediaR provides some tools for downloading and parsing data from the SNPedia web site . The implemented functions allow users to import the wiki text available in SNPedia pages and to extract the most relevant information out of them. If some information in the downloaded pages is not automatically processed by the library functions, users can easily implement their own parsers to access it in an efficient way.", "biocViews": [ "SNP", "Software", "VariantAnnotation" ], "Author": "David Montaner [aut, cre]", "Maintainer": "David Montaner ", "URL": "https://github.com/genometra/SNPediaR", "VignetteBuilder": "knitr", "BugReports": "https://github.com/genometra/SNPediaR/issues", "source.ver": "src/contrib/SNPediaR_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SNPediaR_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SNPediaR_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SNPediaR_1.0.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SNPediaR/inst/doc/SNPediaR.R" ], "htmlDocs": [ "vignettes/SNPediaR/inst/doc/SNPediaR.html" ], "htmlTitles": [ "Vignette Title" ] }, "SNPhood": { "Package": "SNPhood", "Version": "1.4.1", "Depends": [ "R (>= 3.2)", "GenomicRanges", "Rsamtools", "data.table", "checkmate" ], "Imports": [ "DESeq2", "cluster", "ggplot2", "lattice", "GenomeInfoDb", "BiocParallel", "VariantAnnotation", "BiocGenerics", "IRanges", "methods", "SummarizedExperiment", "RColorBrewer", "Biostrings", "grDevices", "gridExtra", "stats", "grid", "utils", "graphics", "reshape2", "scales", "S4Vectors" ], "Suggests": [ "BiocStyle", "knitr", "rmarkdown", "SNPhoodData", "corrplot", "pryr" ], "License": "LGPL (>= 3)", "MD5sum": "30c261d226f92dc14e50003ab0abaa17", "NeedsCompilation": "no", "Title": "SNPhood: Investigate, quantify and visualise the epigenomic neighbourhood of SNPs using NGS data", "Description": "To date, thousands of single nucleotide polymorphisms (SNPs) have been found to be associated with complex traits and diseases. However, the vast majority of these disease-associated SNPs lie in the non-coding part of the genome, and are likely to affect regulatory elements, such as enhancers and promoters, rather than function of a protein. Thus, to understand the molecular mechanisms underlying genetic traits and diseases, it becomes increasingly important to study the effect of a SNP on nearby molecular traits such as chromatin environment or transcription factor (TF) binding. Towards this aim, we developed SNPhood, a user-friendly *Bioconductor* R package to investigate and visualize the local neighborhood of a set of SNPs of interest for NGS data such as chromatin marks or transcription factor binding sites from ChIP-Seq or RNA- Seq experiments. SNPhood comprises a set of easy-to-use functions to extract, normalize and summarize reads for a genomic region, perform various data quality checks, normalize read counts using additional input files, and to cluster and visualize the regions according to the binding pattern. The regions around each SNP can be binned in a user-defined fashion to allow for analysis of very broad patterns as well as a detailed investigation of specific binding shapes. Furthermore, SNPhood supports the integration with genotype information to investigate and visualize genotype-specific binding patterns. Finally, SNPhood can be employed for determining, investigating, and visualizing allele-specific binding patterns around the SNPs of interest.", "biocViews": [ "Software" ], "Author": "Christian Arnold [aut, cre], Pooja Bhat [aut], Judith Zaugg [aut]", "Maintainer": "Christian Arnold ", "VignetteBuilder": "knitr", "BugReports": "christian.arnold@embl.de", "source.ver": "src/contrib/SNPhood_1.4.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SNPhood_1.4.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SNPhood_1.4.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SNPhood_1.4.1.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SNPhood/inst/doc/IntroductionToSNPhood.R", "vignettes/SNPhood/inst/doc/workflow.R" ], "htmlDocs": [ "vignettes/SNPhood/inst/doc/IntroductionToSNPhood.html", "vignettes/SNPhood/inst/doc/workflow.html" ], "htmlTitles": [ "Introduction and Methodological Details", "Workflow example" ] }, "SNPRelate": { "Package": "SNPRelate", "Version": "1.8.0", "Depends": [ "R (>= 2.15)", "gdsfmt (>= 1.8.3)" ], "LinkingTo": [ "gdsfmt" ], "Suggests": [ "parallel", "RUnit", "knitr", "MASS", "BiocGenerics" ], "Enhances": [ "SeqArray (>= 1.11.12)" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "7d88f57e0ae809251645fe408a8f797e", "NeedsCompilation": "yes", "Title": "Parallel Computing Toolset for Relatedness and Principal Component Analysis of SNP Data", "Description": "Genome-wide association studies (GWAS) are widely used to investigate the genetic basis of diseases and traits, but they pose many computational challenges. We developed an R package SNPRelate to provide a binary format for single-nucleotide polymorphism (SNP) data in GWAS utilizing CoreArray Genomic Data Structure (GDS) data files. The GDS format offers the efficient operations specifically designed for integers with two bits, since a SNP could occupy only two bits. SNPRelate is also designed to accelerate two key computations on SNP data using parallel computing for multi-core symmetric multiprocessing computer architectures: Principal Component Analysis (PCA) and relatedness analysis using Identity-By-Descent measures. The SNP GDS format is also used by the GWASTools package with the support of S4 classes and generic functions. The extended GDS format is implemented in the SeqArray package to support the storage of single nucleotide variations (SNVs), insertion/deletion polymorphism (indel) and structural variation calls.", "biocViews": [ "Genetics", "Infrastructure", "PrincipalComponent", "Software", "StatisticalMethod" ], "Author": "Xiuwen Zheng [aut, cre, cph], Stephanie Gogarten [ctb], Cathy Laurie [ctb], Bruce Weir [ctb, ths]", "Maintainer": "Xiuwen Zheng ", "URL": "http://github.com/zhengxwen/SNPRelate, http://corearray.sourceforge.net/tutorials/SNPRelate/", "VignetteBuilder": "knitr", "BugReports": "http://github.com/zhengxwen/SNPRelate/issues", "source.ver": "src/contrib/SNPRelate_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SNPRelate_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SNPRelate_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SNPRelate_1.8.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SNPRelate/inst/doc/SNPRelateTutorial.R" ], "htmlDocs": [ "vignettes/SNPRelate/inst/doc/SNPRelateTutorial.html" ], "htmlTitles": [ "SNPRelate Tutorial" ], "suggestsMe": [ "GENESIS", "GWASTools", "HIBAG", "SeqArray" ] }, "snpStats": { "Package": "snpStats", "Version": "1.24.0", "Depends": [ "R(>= 2.10.0)", "survival", "Matrix", "methods" ], "Imports": [ "graphics", "grDevices", "stats", "utils", "BiocGenerics", "zlibbioc" ], "Suggests": [ "hexbin" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "db0102d0889a6f6a3cfca4c17538baa5", "NeedsCompilation": "yes", "Title": "SnpMatrix and XSnpMatrix classes and methods", "Description": "Classes and statistical methods for large SNP association studies. This extends the earlier snpMatrix package, allowing for uncertainty in genotypes.", "biocViews": [ "GeneticVariability", "Microarray", "SNP", "Software" ], "Author": "David Clayton ", "Maintainer": "David Clayton ", "source.ver": "src/contrib/snpStats_1.24.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/snpStats_1.24.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/snpStats_1.24.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/snpStats_1.24.0.tgz", "vignettes": [ "vignettes/snpStats/inst/doc/data-input-vignette.pdf", "vignettes/snpStats/inst/doc/differences.pdf", "vignettes/snpStats/inst/doc/Fst-vignette.pdf", "vignettes/snpStats/inst/doc/imputation-vignette.pdf", "vignettes/snpStats/inst/doc/ld-vignette.pdf", "vignettes/snpStats/inst/doc/pca-vignette.pdf", "vignettes/snpStats/inst/doc/snpStats-vignette.pdf", "vignettes/snpStats/inst/doc/tdt-vignette.pdf" ], "vignetteTitles": [ "Data input", "snpMatrix-differences", "Fst", "Imputation and meta-analysis", "LD statistics", "Principal components analysis", "snpStats introduction", "TDT tests" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/snpStats/inst/doc/data-input-vignette.R", "vignettes/snpStats/inst/doc/Fst-vignette.R", "vignettes/snpStats/inst/doc/imputation-vignette.R", "vignettes/snpStats/inst/doc/ld-vignette.R", "vignettes/snpStats/inst/doc/pca-vignette.R", "vignettes/snpStats/inst/doc/snpStats-vignette.R", "vignettes/snpStats/inst/doc/tdt-vignette.R" ], "dependsOnMe": [ "GGBase", "GGdata" ], "importsMe": [ "FunciSNP", "GeneGeneInteR", "GGtools", "gQTLstats", "gwascat", "ldblock", "MEAL" ], "suggestsMe": [ "crlmm", "GWASTools", "VariantAnnotation" ] }, "soGGi": { "Package": "soGGi", "Version": "1.6.1", "Depends": [ "R (>= 3.2.0)", "BiocGenerics", "SummarizedExperiment" ], "Imports": [ "methods", "reshape2", "ggplot2", "S4Vectors", "IRanges", "GenomeInfoDb", "GenomicRanges", "Biostrings", "Rsamtools", "GenomicAlignments", "rtracklayer", "preprocessCore", "chipseq", "BiocParallel" ], "Suggests": [ "testthat", "BiocStyle", "knitr" ], "License": "GPL (>= 3)", "MD5sum": "fd00a859b27b40c298bc34f179f78c55", "NeedsCompilation": "no", "Title": "Visualise ChIP-seq, MNase-seq and motif occurrence as aggregate plots Summarised Over Grouped Genomic Intervals", "Description": "The soGGi package provides a toolset to create genomic interval aggregate/summary plots of signal or motif occurence from BAM and bigWig files as well as PWM, rlelist, GRanges and GAlignments Bioconductor objects. soGGi allows for normalisation, transformation and arithmetic operation on and between summary plot objects as well as grouping and subsetting of plots by GRanges objects and user supplied metadata. Plots are created using the GGplot2 libary to allow user defined manipulation of the returned plot object. Coupled together, soGGi features a broad set of methods to visualise genomics data in the context of groups of genomic intervals such as genes, superenhancers and transcription factor binding events.", "biocViews": [ "ChIPSeq", "Coverage", "Sequencing", "Software" ], "Author": "Gopuraja Dharmalingam, Tom Carroll", "Maintainer": "Tom Carroll ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/soGGi_1.6.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/soGGi_1.6.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/soGGi_1.6.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/soGGi_1.6.1.tgz", "vignettes": [ "vignettes/soGGi/inst/doc/soggi.pdf" ], "vignetteTitles": [ "soggi" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/soGGi/inst/doc/soggi.R" ], "importsMe": [ "DChIPRep" ] }, "SomaticSignatures": { "Package": "SomaticSignatures", "Version": "2.10.0", "Depends": [ "R (>= 3.1.0)", "VariantAnnotation", "GenomicRanges" ], "Imports": [ "S4Vectors", "IRanges", "GenomeInfoDb", "Biostrings", "ggplot2", "ggbio", "reshape2", "NMF", "pcaMethods", "Biobase", "methods", "proxy" ], "Suggests": [ "testthat", "knitr", "parallel", "BSgenome.Hsapiens.1000genomes.hs37d5", "SomaticCancerAlterations", "ggdendro", "fastICA", "sva" ], "License": "MIT + file LICENSE", "MD5sum": "e32c9e80fc4423bda8da51aca1372212", "NeedsCompilation": "no", "Title": "Somatic Signatures", "Description": "The SomaticSignatures package identifies mutational signatures of single nucleotide variants (SNVs). It provides a infrastructure related to the methodology described in Nik-Zainal (2012, Cell), with flexibility in the matrix decomposition algorithms.", "biocViews": [ "Clustering", "GenomicVariation", "Sequencing", "Software", "SomaticMutation", "StatisticalMethod", "Visualization" ], "Author": "Julian Gehring", "Maintainer": "Julian Gehring ", "URL": "https://github.com/juliangehring/SomaticSignatures", "VignetteBuilder": "knitr", "BugReports": "https://support.bioconductor.org", "source.ver": "src/contrib/SomaticSignatures_2.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SomaticSignatures_2.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SomaticSignatures_2.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SomaticSignatures_2.10.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/SomaticSignatures/inst/doc/SomaticSignatures-vignette.R" ], "htmlDocs": [ "vignettes/SomaticSignatures/inst/doc/SomaticSignatures-vignette.html" ], "htmlTitles": [ "SomaticSignatures" ], "importsMe": [ "Rariant", "YAPSA" ] }, "SpacePAC": { "Package": "SpacePAC", "Version": "1.12.0", "Depends": [ "R(>= 2.15)", "iPAC" ], "Suggests": [ "RUnit", "BiocGenerics", "rgl" ], "License": "GPL-2", "MD5sum": "6ff3d15b079f13977266acb882c7115a", "NeedsCompilation": "no", "Title": "Identification of Mutational Clusters in 3D Protein Space via Simulation.", "Description": "Identifies clustering of somatic mutations in proteins via a simulation approach while considering the protein's tertiary structure.", "biocViews": [ "Clustering", "Proteomics", "Software" ], "Author": "Gregory Ryslik, Hongyu Zhao", "Maintainer": "Gregory Ryslik ", "source.ver": "src/contrib/SpacePAC_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SpacePAC_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SpacePAC_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SpacePAC_1.12.0.tgz", "vignettes": [ "vignettes/SpacePAC/inst/doc/SpacePAC.pdf" ], "vignetteTitles": [ "SpacePAC: Identifying mutational clusters in 3D protein space using simulation" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SpacePAC/inst/doc/SpacePAC.R" ], "dependsOnMe": [ "QuartPAC" ] }, "specL": { "Package": "specL", "Version": "1.8.0", "Depends": [ "R (>= 3.3)", "methods", "DBI", "RSQLite", "seqinr", "protViz (>= 0.2.15)" ], "LinkingTo": [ "Rcpp (>= 0.12.4)" ], "Suggests": [ "RUnit", "BiocGenerics", "BiocStyle", "plotrix", "knitr", "msqc1 (>= 1.0.0)" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "41aac89afedb9a283537e594d1e37dec", "NeedsCompilation": "yes", "Title": "specL - Prepare Peptide Spectrum Matches for Use in Targeted Proteomics", "Description": "specL provides a function for generating spectra libraries which can be used for MRM SRM MS workflows in proteomics. The package provides a BiblioSpec reader, a function which can add the protein information using a FASTA formatted amino acid file, and an export method for using the created library in the Spectronaut software.", "biocViews": [ "MassSpectrometry", "Proteomics", "Software" ], "Author": "Christian Trachsel , Christian Panse , Jonas Grossmann , Witold E. Wolski ", "Maintainer": "Christian Panse , Witold E. Wolski ", "URL": "https://github.com/fgcz/specL", "VignetteBuilder": "knitr", "BugReports": "https://github.com/fgcz/specL/issues", "source.ver": "src/contrib/specL_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/specL_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/specL_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/specL_1.8.0.tgz", "vignettes": [ "vignettes/specL/inst/doc/specL.pdf" ], "vignetteTitles": [ "Introduction to specL" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/specL/inst/doc/cdsw.R", "vignettes/specL/inst/doc/specL.R", "vignettes/specL/inst/doc/ssrc.R" ], "htmlDocs": [ "vignettes/specL/inst/doc/cdsw.html", "vignettes/specL/inst/doc/ssrc.html" ], "htmlTitles": [ "Computing Dynamic SWATH Windows", "Retention Time Prediction using the ssrc Method" ], "suggestsMe": [ "msqc1" ] }, "SpeCond": { "Package": "SpeCond", "Version": "1.28.0", "Depends": [ "R (>= 2.10.0)", "mclust (>= 3.3.1)", "Biobase (>= 1.15.13)", "fields", "hwriter (>= 1.1)", "RColorBrewer", "methods" ], "License": "LGPL (>=2)", "MD5sum": "36ff570ce85171954428ef0c6b014559", "NeedsCompilation": "no", "Title": "Condition specific detection from expression data", "Description": "This package performs a gene expression data analysis to detect condition-specific genes. Such genes are significantly up- or down-regulated in a small number of conditions. It does so by fitting a mixture of normal distributions to the expression values. Conditions can be environmental conditions, different tissues, organs or any other sources that you wish to compare in terms of gene expression.", "biocViews": [ "Clustering", "DifferentialExpression", "Microarray", "MultipleComparison", "ReportWriting", "Software" ], "Author": "Florence Cavalli", "Maintainer": "Florence Cavalli ", "source.ver": "src/contrib/SpeCond_1.28.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SpeCond_1.28.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SpeCond_1.28.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SpeCond_1.28.0.tgz", "vignettes": [ "vignettes/SpeCond/inst/doc/SpeCond.pdf" ], "vignetteTitles": [ "SpeCond" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SpeCond/inst/doc/SpeCond.R" ] }, "SPEM": { "Package": "SPEM", "Version": "1.14.0", "Depends": [ "R (>= 2.15.1)", "Rsolnp", "Biobase", "methods" ], "License": "GPL-2", "MD5sum": "07ed1aad3fb29ec74956568acfde6776", "NeedsCompilation": "no", "Title": "S-system parameter estimation method", "Description": "This package can optimize the parameter in S-system models given time series data", "biocViews": [ "Network", "NetworkInference", "Software" ], "Author": "Xinyi YANG Developer, Jennifer E. DENT Developer and Christine NARDINI Supervisor", "Maintainer": "Xinyi YANG ", "source.ver": "src/contrib/SPEM_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SPEM_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SPEM_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SPEM_1.14.0.tgz", "vignettes": [ "vignettes/SPEM/inst/doc/SPEM-package.pdf" ], "vignetteTitles": [ "Vignette for SPEM" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SPEM/inst/doc/SPEM-package.R" ] }, "SPIA": { "Package": "SPIA", "Version": "2.26.0", "Depends": [ "R (>= 2.14.0)", "graphics", "KEGGgraph" ], "Imports": [ "graphics" ], "Suggests": [ "graph", "Rgraphviz", "hgu133plus2.db" ], "License": "file LICENSE", "License_restricts_use": "yes", "MD5sum": "ce40875578a8618b956b54bddff8f321", "NeedsCompilation": "no", "Title": "Signaling Pathway Impact Analysis (SPIA) using combined evidence of pathway over-representation and unusual signaling perturbations", "Description": "This package implements the Signaling Pathway Impact Analysis (SPIA) which uses the information form a list of differentially expressed genes and their log fold changes together with signaling pathways topology, in order to identify the pathways most relevant to the condition under the study.", "biocViews": [ "GraphAndNetwork", "Microarray", "Software" ], "Author": "Adi Laurentiu Tarca , Purvesh Kathri and Sorin Draghici ", "Maintainer": "Adi Laurentiu Tarca ", "URL": "http://bioinformatics.oxfordjournals.org/cgi/reprint/btn577v1", "source.ver": "src/contrib/SPIA_2.26.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SPIA_2.26.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SPIA_2.26.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SPIA_2.26.0.tgz", "vignettes": [ "vignettes/SPIA/inst/doc/SPIA.pdf" ], "vignetteTitles": [ "SPIA" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/SPIA/inst/doc/SPIA.R" ], "importsMe": [ "EnrichmentBrowser" ], "suggestsMe": [ "graphite", "KEGGgraph" ] }, "SpidermiR": { "Package": "SpidermiR", "Version": "1.4.8", "Depends": [ "R (>= 3.0.0)" ], "Imports": [ "networkD3", "httr", "igraph", "utils", "stats", "miRNAtap", "miRNAtap.db", "AnnotationDbi", "org.Hs.eg.db", "ggplot2", "gridExtra", "gplots", "grDevices", "lattice", "latticeExtra", "visNetwork", "TCGAbiolinks" ], "Suggests": [ "BiocStyle", "knitr", "rmarkdown", "testthat", "devtools", "roxygen2" ], "License": "GPL (>= 3)", "MD5sum": "3e3a368193712d70e7cbc03b042fc2dc", "NeedsCompilation": "no", "Title": "SpidermiR: An R/Bioconductor package for integrative network analysis with miRNA data", "Description": "The aims of SpidermiR are : i) facilitate the network open-access data retrieval from GeneMania data, ii) prepare the data using the appropriate gene nomenclature, iii) integration of miRNA data in a specific network, iv) provide different standard analyses and v) allow the user to visualize the results. In more detail, the package provides multiple methods for query, prepare and download network data (GeneMania), and the integration with validated and predicted miRNA data (mirWalk, miR2Disease,miRTar, miRandola,Pharmaco-miR,DIANA, Miranda, PicTar and TargetScan) and the use of standard analysis (igraph) and visualization methods (networkD3).", "biocViews": [ "GeneRegulation", "Network", "Software", "miRNA" ], "Author": "Claudia Cava, Antonio Colaprico, Alex Graudenzi, Gloria Bertoli, Tiago C. Silva, Catharina Olsen, Houtan Noushmehr, Gianluca Bontempi, Giancarlo Mauri, Isabella Castiglioni", "Maintainer": "Claudia Cava ", "URL": "https://github.com/claudiacava/SpidermiR", "VignetteBuilder": "knitr", "BugReports": "https://github.com/claudiacava/SpidermiR/issues", "source.ver": "src/contrib/SpidermiR_1.4.8.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SpidermiR_1.4.8.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SpidermiR_1.4.8.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SpidermiR_1.4.8.tgz", "vignettes": [ "vignettes/SpidermiR/inst/doc/SpidermiRcasestudy.pdf" ], "vignetteTitles": [ "SpidermiR examples" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SpidermiR/inst/doc/SpidermiR.R", "vignettes/SpidermiR/inst/doc/SpidermiRcasestudy.R" ], "htmlDocs": [ "vignettes/SpidermiR/inst/doc/SpidermiR.html" ], "htmlTitles": [ "Working with SpidermiR package" ], "importsMe": [ "StarBioTrek" ] }, "spikeLI": { "Package": "spikeLI", "Version": "2.34.0", "Imports": [ "graphics", "grDevices", "stats", "utils" ], "License": "GPL-2", "MD5sum": "664949ebd5c905b1de0a43e1e5f55d0d", "NeedsCompilation": "no", "Title": "Affymetrix Spike-in Langmuir Isotherm Data Analysis Tool", "Description": "SpikeLI is a package that performs the analysis of the Affymetrix spike-in data using the Langmuir Isotherm. The aim of this package is to show the advantages of a physical-chemistry based analysis of the Affymetrix microarray data compared to the traditional methods. The spike-in (or Latin square) data for the HGU95 and HGU133 chipsets have been downloaded from the Affymetrix web site. The model used in the spikeLI package is described in details in E. Carlon and T. Heim, Physica A 362, 433 (2006).", "biocViews": [ "Microarray", "QualityControl", "Software" ], "Author": "Delphine Baillon, Paul Leclercq , Sarah Ternisien, Thomas Heim, Enrico Carlon ", "Maintainer": "Enrico Carlon ", "source.ver": "src/contrib/spikeLI_2.34.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/spikeLI_2.34.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/spikeLI_2.34.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/spikeLI_2.34.0.tgz", "vignettes": [ "vignettes/spikeLI/inst/doc/spikeLI.pdf" ], "vignetteTitles": [ "spikeLI" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false }, "spkTools": { "Package": "spkTools", "Version": "1.30.0", "Depends": [ "R (>= 2.7.0)", "Biobase (>= 2.5.5)" ], "Imports": [ "Biobase (>= 2.5.5)", "graphics", "grDevices", "gtools", "methods", "RColorBrewer", "stats", "utils" ], "Suggests": [ "xtable" ], "License": "GPL (>= 2)", "MD5sum": "c0a1bc60070188895da00ba701d72417", "NeedsCompilation": "no", "Title": "Methods for Spike-in Arrays", "Description": "The package contains functions that can be used to compare expression measures on different array platforms.", "biocViews": [ "Microarray", "Software", "Technology" ], "Author": "Matthew N McCall , Rafael A Irizarry ", "Maintainer": "Matthew N McCall ", "URL": "http://bioconductor.org", "source.ver": "src/contrib/spkTools_1.30.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/spkTools_1.30.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/spkTools_1.30.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/spkTools_1.30.0.tgz", "vignettes": [ "vignettes/spkTools/inst/doc/spkDoc.pdf" ], "vignetteTitles": [ "spkTools: Spike-in Data Analysis and Visualization" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/spkTools/inst/doc/spkDoc.R" ] }, "splicegear": { "Package": "splicegear", "Version": "1.46.0", "Depends": [ "R (>= 2.6.0)", "methods", "Biobase(>= 2.5.5)" ], "Imports": [ "annotate", "Biobase", "graphics", "grDevices", "grid", "methods", "utils", "XML" ], "License": "LGPL", "MD5sum": "46f1d8bc68b582f3edb680c30e55e585", "NeedsCompilation": "no", "Title": "splicegear", "Description": "A set of tools to work with alternative splicing", "biocViews": [ "Infrastructure", "Software", "Transcription" ], "Author": "Laurent Gautier ", "Maintainer": "Laurent Gautier ", "source.ver": "src/contrib/splicegear_1.46.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/splicegear_1.46.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/splicegear_1.46.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/splicegear_1.46.0.tgz", "vignettes": [ "vignettes/splicegear/inst/doc/splicegear.pdf" ], "vignetteTitles": [ "splicegear Introduction" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/splicegear/inst/doc/splicegear.R" ] }, "spliceR": { "Package": "spliceR", "Version": "1.16.0", "Depends": [ "R (>= 2.15.0)", "methods", "cummeRbund", "rtracklayer", "VennDiagram", "RColorBrewer", "plyr" ], "Imports": [ "GenomicRanges", "IRanges" ], "Suggests": [ "BSgenome.Hsapiens.UCSC.hg19", "BSgenome" ], "License": "GPL (>=2)", "Archs": "i386, x64", "MD5sum": "3f64e08d4801b6aa92f969aa5ca5d7e8", "NeedsCompilation": "yes", "Title": "Classification of alternative splicing and prediction of coding potential from RNA-seq data.", "Description": "An R package for classification of alternative splicing and prediction of coding potential from RNA-seq data.", "biocViews": [ "AlternativeSplicing", "DifferentialExpression", "DifferentialSplicing", "GeneExpression", "Sequencing", "Software", "Transcription", "Visualization" ], "Author": "Johannes Waage , Kristoffer Vitting-Seerup ", "Maintainer": "Johannes Waage , Kristoffer Vitting-Seerup ", "source.ver": "src/contrib/spliceR_1.16.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/spliceR_1.16.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/spliceR_1.16.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/spliceR_1.16.0.tgz", "vignettes": [ "vignettes/spliceR/inst/doc/spliceR.pdf" ], "vignetteTitles": [ "spliceR Vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/spliceR/inst/doc/spliceR.R" ] }, "spliceSites": { "Package": "spliceSites", "Version": "1.22.1", "Depends": [ "methods", "rbamtools (>= 2.14.3)", "refGenome (>= 1.6.0)", "Biobase", "Biostrings (>= 2.28.0)" ], "Imports": [ "BiocGenerics", "doBy", "seqLogo", "IRanges" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "9198a7f031e0da2fcdecf103d1d820b7", "NeedsCompilation": "yes", "Title": "A bioconductor package for exploration of alignment gap positions from RNA-seq data", "Description": "Performs splice centered analysis on RNA-seq data.", "biocViews": [ "DifferentialExpression", "GeneExpression", "Proteomics", "RNAseq", "Software" ], "Author": "Wolfgang Kaisers", "Maintainer": "Wolfgang Kaisers ", "source.ver": "src/contrib/spliceSites_1.22.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/spliceSites_1.22.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/spliceSites_1.22.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/spliceSites_1.22.1.tgz", "vignettes": [ "vignettes/spliceSites/inst/doc/spliceSites.pdf" ], "vignetteTitles": [ "spliceSites" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/spliceSites/inst/doc/spliceSites.R" ] }, "SplicingGraphs": { "Package": "SplicingGraphs", "Version": "1.14.0", "Depends": [ "GenomicFeatures (>= 1.17.13)", "GenomicAlignments (>= 1.1.22)", "Rgraphviz (>= 2.3.7)" ], "Imports": [ "methods", "utils", "graphics", "igraph", "BiocGenerics", "S4Vectors (>= 0.9.25)", "IRanges (>= 2.3.21)", "GenomeInfoDb", "GenomicRanges (>= 1.23.21)", "GenomicFeatures", "Rsamtools", "GenomicAlignments", "graph", "Rgraphviz" ], "Suggests": [ "igraph", "Gviz", "TxDb.Hsapiens.UCSC.hg19.knownGene", "RNAseqData.HNRNPC.bam.chr14", "RUnit" ], "License": "Artistic-2.0", "MD5sum": "6a847ba065626289bca019f8858dc822", "NeedsCompilation": "no", "Title": "Create, manipulate, visualize splicing graphs, and assign RNA-seq reads to them", "Description": "This package allows the user to create, manipulate, and visualize splicing graphs and their bubbles based on a gene model for a given organism. Additionally it allows the user to assign RNA-seq reads to the edges of a set of splicing graphs, and to summarize them in different ways.", "biocViews": [ "AlternativeSplicing", "Annotation", "DataRepresentation", "GeneExpression", "Genetics", "RNASeq", "Sequencing", "Software", "Transcription", "Visualization" ], "Author": "D. Bindreither, M. Carlson, M. Morgan, H. Pagès", "Maintainer": "H. Pagès ", "source.ver": "src/contrib/SplicingGraphs_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SplicingGraphs_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SplicingGraphs_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SplicingGraphs_1.14.0.tgz", "vignettes": [ "vignettes/SplicingGraphs/inst/doc/SplicingGraphs.pdf" ], "vignetteTitles": [ "Splicing graphs and RNA-seq data" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SplicingGraphs/inst/doc/SplicingGraphs.R" ] }, "splineTimeR": { "Package": "splineTimeR", "Version": "1.2.0", "Depends": [ "R (>= 3.3)", "Biobase", "igraph", "limma", "GSEABase", "gtools", "splines", "GeneNet (>= 1.2.13)", "longitudinal (>= 1.1.12)", "FIs" ], "Suggests": [ "knitr" ], "License": "GPL-3", "MD5sum": "166c7babc3a5260a03c98def28ba1f9e", "NeedsCompilation": "no", "Title": "Time-course differential gene expression data analysis using spline regression models followed by gene association network reconstruction", "Description": "This package provides functions for differential gene expression analysis of gene expression time-course data. Natural cubic spline regression models are used. Identified genes may further be used for pathway enrichment analysis and/or the reconstruction of time dependent gene regulatory association networks.", "biocViews": [ "DifferentialExpression", "GeneExpression", "GeneSetEnrichment", "GraphAndNetwork", "NetworkEnrichment", "NetworkInference", "Regression", "Software", "TimeCourse" ], "Author": "Agata Michna", "Maintainer": "Herbert Braselmann ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/splineTimeR_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/splineTimeR_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/splineTimeR_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/splineTimeR_1.2.0.tgz", "vignettes": [ "vignettes/splineTimeR/inst/doc/splineTimeR.pdf" ], "vignetteTitles": [ "splineTimeR" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/splineTimeR/inst/doc/splineTimeR.R" ] }, "SPLINTER": { "Package": "SPLINTER", "Version": "1.0.0", "Depends": [ "R (>= 3.3.0)", "grDevices", "stats" ], "Imports": [ "graphics", "ggplot2", "seqLogo", "Biostrings", "biomaRt", "GenomicAlignments", "GenomicRanges", "GenomicFeatures", "Gviz", "IRanges", "S4Vectors", "GenomeInfoDb", "utils", "plyr", "BSgenome.Mmusculus.UCSC.mm9" ], "Suggests": [ "BiocStyle", "knitr", "rmarkdown" ], "License": "GPL-2", "MD5sum": "8979e82fb0591e0fb0f0e68a4c134d08", "NeedsCompilation": "no", "Title": "Splice Interpreter Of Transcripts", "Description": "SPLINTER provides tools to analyze alternative splicing sites, interpret outcomes based on sequence information, select and design primers for site validiation and give visual representation of the event to guide downstream experiments.", "biocViews": [ "AlternativeSplicing", "GeneExpression", "RNASeq", "Software", "Visualization" ], "Author": "Diana Low", "Maintainer": "Diana Low ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/SPLINTER_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SPLINTER_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SPLINTER_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SPLINTER_1.0.0.tgz", "vignettes": [ "vignettes/SPLINTER/inst/doc/vignette.pdf" ], "vignetteTitles": [ "SPLINTER" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SPLINTER/inst/doc/vignette.R" ] }, "splots": { "Package": "splots", "Version": "1.40.0", "Imports": [ "grid", "RColorBrewer" ], "License": "LGPL", "MD5sum": "71416bb7165374d5553b1397e1d4287e", "NeedsCompilation": "no", "Title": "Visualization of high-throughput assays in microtitre plate or slide format", "Description": "The splots package provides the plotScreen function for visualising data in microtitre plate or slide format.", "biocViews": [ "MicrotitrePlateAssay", "Sequencing", "Software", "Visualization" ], "Author": "Wolfgang Huber, Oleg Sklyar", "Maintainer": "Wolfgang Huber ", "source.ver": "src/contrib/splots_1.40.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/splots_1.40.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/splots_1.40.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/splots_1.40.0.tgz", "vignettes": [ "vignettes/splots/inst/doc/splotsHOWTO.pdf" ], "vignetteTitles": [ "Visualization of data from assays in microtitre plate or slide format" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/splots/inst/doc/splotsHOWTO.R" ], "dependsOnMe": [ "cellHTS2", "HD2013SGI", "PGPC" ], "importsMe": [ "RNAinteract", "RNAither" ] }, "spotSegmentation": { "Package": "spotSegmentation", "Version": "1.48.0", "Depends": [ "R (>= 2.10)", "mclust" ], "License": "GPL (>= 2)", "MD5sum": "2d13e762a6e1876820e188f8b685a510", "NeedsCompilation": "no", "Title": "Microarray Spot Segmentation and Gridding for Blocks of Microarray Spots", "Description": "Spot segmentation via model-based clustering and gridding for blocks within microarray slides, as described in Li et al, Robust Model-Based Segmentation of Microarray Images, Technical Report no. 473, Department of Statistics, University of Washington.", "biocViews": [ "Microarray", "Preprocessing", "QualityControl", "Software", "TwoChannel" ], "Author": "Qunhua Li, Chris Fraley, Adrian Raftery Department of Statistics, University of Washington", "Maintainer": "Chris Fraley ", "URL": "http://www.stat.washington.edu/fraley", "source.ver": "src/contrib/spotSegmentation_1.48.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/spotSegmentation_1.48.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/spotSegmentation_1.48.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/spotSegmentation_1.48.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false }, "SQUADD": { "Package": "SQUADD", "Version": "1.24.0", "Depends": [ "R (>= 2.11.0)" ], "Imports": [ "graphics", "grDevices", "methods", "RColorBrewer", "stats", "utils" ], "License": "GPL (>=2)", "MD5sum": "aee67954815ba1bca5b76fc0a9c05801", "NeedsCompilation": "no", "Title": "Add-on of the SQUAD Software", "Description": "This package SQUADD is a SQUAD add-on. It permits to generate SQUAD simulation matrix, prediction Heat-Map and Correlation Circle from PCA analysis.", "biocViews": [ "GraphAndNetwork", "Network", "Software", "Visualization" ], "Author": "Martial Sankar, supervised by Christian Hardtke and Ioannis Xenarios", "Maintainer": "Martial Sankar ", "URL": "http://www.unil.ch/dbmv/page21142_en.html", "source.ver": "src/contrib/SQUADD_1.24.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SQUADD_1.24.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SQUADD_1.24.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SQUADD_1.24.0.tgz", "vignettes": [ "vignettes/SQUADD/inst/doc/SQUADD_ERK.pdf", "vignettes/SQUADD/inst/doc/SQUADD.pdf" ], "vignetteTitles": [ "SQUADD package", "SQUADD package" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SQUADD/inst/doc/SQUADD_ERK.R", "vignettes/SQUADD/inst/doc/SQUADD.R" ] }, "SRAdb": { "Package": "SRAdb", "Version": "1.32.0", "Depends": [ "RSQLite", "graph", "RCurl" ], "Imports": [ "GEOquery" ], "Suggests": [ "Rgraphviz" ], "License": "Artistic-2.0", "MD5sum": "c71a15ded5e740dc953073bdfcfc6821", "NeedsCompilation": "no", "Title": "A compilation of metadata from NCBI SRA and tools", "Description": "The Sequence Read Archive (SRA) is the largest public repository of sequencing data from the next generation of sequencing platforms including Roche 454 GS System, Illumina Genome Analyzer, Applied Biosystems SOLiD System, Helicos Heliscope, and others. However, finding data of interest can be challenging using current tools. SRAdb is an attempt to make access to the metadata associated with submission, study, sample, experiment and run much more feasible. This is accomplished by parsing all the NCBI SRA metadata into a SQLite database that can be stored and queried locally. Fulltext search in the package make querying metadata very flexible and powerful. fastq and sra files can be downloaded for doing alignment locally. Beside ftp protocol, the SRAdb has funcitons supporting fastp protocol (ascp from Aspera Connect) for faster downloading large data files over long distance. The SQLite database is updated regularly as new data is added to SRA and can be downloaded at will for the most up-to-date metadata.", "biocViews": [ "DataImport", "Infrastructure", "Sequencing", "Software" ], "Author": "Jack Zhu and Sean Davis", "Maintainer": "Jack Zhu ", "URL": "http://gbnci.abcc.ncifcrf.gov/sra/", "BugReports": "https://github.com/seandavi/SRAdb/issues/new", "source.ver": "src/contrib/SRAdb_1.32.0.tar.gz", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SRAdb_1.32.0.tgz", "vignettes": [ "vignettes/SRAdb/inst/doc/SRAdb.pdf" ], "vignetteTitles": [ "Using SRAdb to Query the Sequence Read Archive" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SRAdb/inst/doc/SRAdb.R" ], "suggestsMe": [ "parathyroidSE" ] }, "sRAP": { "Package": "sRAP", "Version": "1.14.0", "Depends": [ "WriteXLS" ], "Imports": [ "gplots", "pls", "ROCR", "qvalue" ], "License": "GPL-3", "MD5sum": "21b249c77e1de7d3885d2e0d64c642eb", "NeedsCompilation": "no", "Title": "Simplified RNA-Seq Analysis Pipeline", "Description": "This package provides a pipeline for gene expression analysis (primarily for RNA-Seq data). The normalization function is specific for RNA-Seq analysis, but all other functions (Quality Control Figures, Differential Expression and Visualization, and Functional Enrichment via BD-Func) will work with any type of gene expression data.", "biocViews": [ "DifferentialExpression", "GO", "GeneExpression", "GeneSetEnrichment", "Microarray", "Preprocessing", "QualityControl", "RNAseq", "Software", "Statistics", "Visualization" ], "Author": "Charles Warden", "Maintainer": "Charles Warden ", "source.ver": "src/contrib/sRAP_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/sRAP_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/sRAP_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/sRAP_1.14.0.tgz", "vignettes": [ "vignettes/sRAP/inst/doc/sRAP.pdf" ], "vignetteTitles": [ "sRAP Vignette" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/sRAP/inst/doc/sRAP.R" ] }, "SRGnet": { "Package": "SRGnet", "Version": "1.0.0", "Depends": [ "R (>= 3.2.2)", "EBcoexpress", "MASS", "igraph", "pvclust (>= 2.0-0)", "RedeR", "gRain (>= 1.2-5)", "gbm (>= 2.1.1)", "limma", "DMwR (>= 0.4.1)", "matrixStats" ], "Suggests": [ "knitr", "rmarkdown" ], "License": "GPL-2", "MD5sum": "e39165e17188c31855093a80da07a349", "NeedsCompilation": "no", "Title": "SRGnet An R package for studying synergistic response genes from transcriptomics data", "Description": "We developed SRMnet to analyze synergistic regulatory mechanisms in transcriptome profiles that act to enhance the overall cell response to combination of mutations, drugs or environmental exposure. This package can be used to identify regulatory modules downstream of synergistic response genes, prioritize synergistic regulatory genes that may be potential intervention targets, and contextualize gene perturbation experiments.", "biocViews": [ "Regression", "Software", "StatisticalMethod" ], "Author": "Isar Nassiri [aut, cre], Matthew McCall [aut, cre]", "Maintainer": "Isar Nassiri ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/SRGnet_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SRGnet_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SRGnet_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SRGnet_1.0.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "htmlDocs": [ "vignettes/SRGnet/inst/doc/vignette.html" ], "htmlTitles": [ "SRGnet: An R package for studying synergistic response genes from transcriptomics data" ] }, "sscore": { "Package": "sscore", "Version": "1.46.0", "Depends": [ "R (>= 1.8.0)", "affy", "affyio" ], "Suggests": [ "affydata" ], "License": "GPL (>= 2)", "MD5sum": "68e03cd96c6047fd8a5404fd93a25d49", "NeedsCompilation": "no", "Title": "S-Score Algorithm for Affymetrix Oligonucleotide Microarrays", "Description": "This package contains an implementation of the S-Score algorithm as described by Zhang et al (2002).", "biocViews": [ "DifferentialExpression", "Software" ], "Author": "Richard Kennedy , based on C++ code from Li Zhang and Borland Delphi code from Robnet Kerns .", "Maintainer": "Richard Kennedy ", "URL": "http://home.att.net/~richard-kennedy/professional.html", "source.ver": "src/contrib/sscore_1.46.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/sscore_1.46.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/sscore_1.46.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/sscore_1.46.0.tgz", "vignettes": [ "vignettes/sscore/inst/doc/sscore.pdf" ], "vignetteTitles": [ "SScore primer" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/sscore/inst/doc/sscore.R" ] }, "sscu": { "Package": "sscu", "Version": "2.2.0", "Depends": [ "R (>= 3.3)" ], "Imports": [ "Biostrings (>= 2.36.4)", "seqinr (>= 3.1-3)", "BiocGenerics (>= 0.16.1)" ], "Suggests": [ "knitr", "rmarkdown" ], "License": "GPL (>= 2)", "MD5sum": "e637e1abed9702ae6ec1addb14ab3b66", "NeedsCompilation": "no", "Title": "Strength of Selected Codon Usage", "Description": "The package can calculate the indexes for selective stength in codon usage in bacteria species. (1) The package can calculate the strength of selected codon usage bias (sscu, also named as s_index) based on Paul Sharp's method. The method take into account of background mutation rate, and focus only on four pairs of codons with universal translational advantages in all bacterial species. Thus the sscu index is comparable among different species. (2) Translational accuracy selection can be inferred from Akashi's test. The test tabulating all codons into four categories with the feature as conserved/variable amino acids and optimal/non-optimal codons. (3) Optimal codon lists (selected codons) can be calculated by either op_highly function (by using the highly expressed genes compared with all genes to identify optimal codons biased used in the highly expressed genes), or op_corre_CodonW/op_corre_NCprime function (by correlative method developed by Hershberg & Petrov). Users will have a list of optimal codons for further analysis, such as input to the Akashi's test. (4) The detailed codon usage information, such as RSCU value, number of optimal codons in the highly/all gene set, as well as the genomic gc3 value, can be calculate by the optimal_codon_statistics and genomic_gc3 function. (5) Furthermore, we added one test function proportion_index in the package. The function focus on the proportion of optimal codon against its corresponding non-optimal codons for the the four and six codon boxes.", "biocViews": [ "GeneExpression", "Genetics", "Software", "WholeGenome" ], "Author": "Yu Sun", "Maintainer": "Yu Sun ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/sscu_2.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/sscu_2.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/sscu_2.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/sscu_2.2.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false }, "sSeq": { "Package": "sSeq", "Version": "1.12.0", "Depends": [ "R (>= 3.0)", "caTools", "RColorBrewer" ], "License": "GPL (>= 3)", "MD5sum": "a19688133bb3882b57969c67272cd425", "NeedsCompilation": "no", "Title": "Shrinkage estimation of dispersion in Negative Binomial models for RNA-seq experiments with small sample size", "Description": "The purpose of this package is to discover the genes that are differentially expressed between two conditions in RNA-seq experiments. Gene expression is measured in counts of transcripts and modeled with the Negative Binomial (NB) distribution using a shrinkage approach for dispersion estimation. The method of moment (MM) estimates for dispersion are shrunk towards an estimated target, which minimizes the average squared difference between the shrinkage estimates and the initial estimates. The exact per-gene probability under the NB model is calculated, and used to test the hypothesis that the expected expression of a gene in two conditions identically follow a NB distribution.", "biocViews": [ "RNASeq", "Software" ], "Author": "Danni Yu , Wolfgang Huber and Olga Vitek ", "Maintainer": "Danni Yu ", "source.ver": "src/contrib/sSeq_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/sSeq_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/sSeq_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/sSeq_1.12.0.tgz", "vignettes": [ "vignettes/sSeq/inst/doc/sSeq.pdf" ], "vignetteTitles": [ "sSeq" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/sSeq/inst/doc/sSeq.R" ] }, "ssize": { "Package": "ssize", "Version": "1.48.0", "Depends": [ "gdata", "xtable" ], "License": "LGPL", "MD5sum": "a640a7189f0bc5ee9f1403582810dcd0", "NeedsCompilation": "no", "Title": "Estimate Microarray Sample Size", "Description": "Functions for computing and displaying sample size information for gene expression arrays.", "biocViews": [ "DifferentialExpression", "Microarray", "Software" ], "Author": "Gregory R. Warnes, Peng Liu, and Fasheng Li", "Maintainer": "Gregory R. Warnes ", "source.ver": "src/contrib/ssize_1.48.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ssize_1.48.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ssize_1.48.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ssize_1.48.0.tgz", "vignettes": [ "vignettes/ssize/inst/doc/ssize.pdf" ], "vignetteTitles": [ "Sample Size Estimation for Microarray Experiments Using the \\code{ssize} package" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ssize/inst/doc/ssize.R" ], "suggestsMe": [ "oneChannelGUI" ] }, "SSPA": { "Package": "SSPA", "Version": "2.14.0", "Depends": [ "R (>= 2.12)", "methods", "qvalue", "lattice", "limma" ], "Imports": [ "graphics", "stats" ], "Suggests": [ "BiocStyle", "genefilter", "edgeR", "DESeq" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "776bc39b0f187432c29b8ecf60027220", "NeedsCompilation": "yes", "Title": "General Sample Size and Power Analysis for Microarray and Next-Generation Sequencing Data", "Description": "General Sample size and power analysis for microarray and next-generation sequencing data.", "biocViews": [ "GeneExpression", "Microarray", "RNASeq", "Software", "StatisticalMethod" ], "Author": "Maarten van Iterson", "Maintainer": "Maarten van Iterson ", "URL": "http://www.humgen.nl/MicroarrayAnalysisGroup.html", "source.ver": "src/contrib/SSPA_2.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SSPA_2.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SSPA_2.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SSPA_2.14.0.tgz", "vignettes": [ "vignettes/SSPA/inst/doc/SSPA.pdf" ], "vignetteTitles": [ "SSPA Overview" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SSPA/inst/doc/SSPA.R" ] }, "ssviz": { "Package": "ssviz", "Version": "1.8.0", "Depends": [ "R (>= 2.15.1)", "methods", "Rsamtools", "Biostrings", "reshape", "ggplot2", "RColorBrewer" ], "Suggests": [ "knitr" ], "License": "GPL-2", "MD5sum": "5f091a5fd980c60b7c3143e9927ba8f5", "NeedsCompilation": "no", "Title": "A small RNA-seq visualizer and analysis toolkit", "Description": "Small RNA sequencing viewer", "biocViews": [ "Genetics", "MultipleComparison", "RNASeq", "Sequencing", "Software", "Visualization" ], "Author": "Diana Low", "Maintainer": "Diana Low ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/ssviz_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ssviz_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ssviz_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ssviz_1.8.0.tgz", "vignettes": [ "vignettes/ssviz/inst/doc/ssviz.pdf" ], "vignetteTitles": [ "ssviz" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ssviz/inst/doc/ssviz.R" ] }, "STAN": { "Package": "STAN", "Version": "2.2.0", "Depends": [ "methods", "poilog", "parallel" ], "Imports": [ "GenomicRanges", "IRanges", "S4Vectors", "BiocGenerics", "GenomeInfoDb", "Gviz", "Rsolnp" ], "Suggests": [ "BiocStyle", "gplots", "knitr" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "18a938c1ef2f4617506b63ce18c2ff3c", "NeedsCompilation": "yes", "Title": "The genomic STate ANnotation package", "Description": "Genome segmentation with hidden Markov models has become a useful tool to annotate genomic elements, such as promoters and enhancers. STAN (genomic STate ANnotation) implements (bidirectional) hidden Markov models (HMMs) using a variety of different probability distributions, which can model a wide range of current genomic data (e.g. continuous, discrete, binary). STAN de novo learns and annotates the genome into a given number of 'genomic states'. The 'genomic states' may for instance reflect distinct genome-associated protein complexes (e.g. 'transcription states') or describe recurring patterns of chromatin features (referred to as 'chromatin states'). Unlike other tools, STAN also allows for the integration of strand-specific (e.g. RNA) and non-strand-specific data (e.g. ChIP).", "biocViews": [ "ChIPSeq", "ChipOnChip", "GenomeAnnotation", "HiddenMarkovModel", "Microarray", "RNASeq", "Sequencing", "Software", "Transcription" ], "Author": "Benedikt Zacher, Julia Ertl, Julien Gagneur, Achim Tresch", "Maintainer": "Benedikt Zacher ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/STAN_2.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/STAN_2.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/STAN_2.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/STAN_2.2.0.tgz", "vignettes": [ "vignettes/STAN/inst/doc/STAN.pdf" ], "vignetteTitles": [ "The genomic STate ANnotation package" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/STAN/inst/doc/STAN.R" ] }, "staRank": { "Package": "staRank", "Version": "1.16.0", "Depends": [ "methods", "cellHTS2", "R (>= 2.10)" ], "License": "GPL", "MD5sum": "cb125e7bc9e33d3ba700680d18416e12", "NeedsCompilation": "no", "Title": "Stability Ranking", "Description": "Detecting all relevant variables from a data set is challenging, especially when only few samples are available and data is noisy. Stability ranking provides improved variable rankings of increased robustness using resampling or subsampling.", "biocViews": [ "CellBasedAssays", "CellBiology", "MicrotitrePlateAssay", "MultipleComparison", "Software" ], "Author": "Juliane Siebourg, Niko Beerenwinkel", "Maintainer": "Juliane Siebourg ", "source.ver": "src/contrib/staRank_1.16.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/staRank_1.16.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/staRank_1.16.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/staRank_1.16.0.tgz", "vignettes": [ "vignettes/staRank/inst/doc/staRank.pdf" ], "vignetteTitles": [ "Using staRank" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/staRank/inst/doc/staRank.R" ] }, "StarBioTrek": { "Package": "StarBioTrek", "Version": "1.0.3", "Depends": [ "R (>= 3.3)" ], "Imports": [ "SpidermiR", "KEGGREST", "org.Hs.eg.db", "AnnotationDbi", "e1071", "ROCR", "grDevices", "igraph" ], "Suggests": [ "BiocStyle", "knitr", "rmarkdown", "testthat", "devtools", "roxygen2", "qgraph", "png", "grid" ], "License": "GPL (>= 3)", "MD5sum": "0941f2d2af5bd1bf484486b58d21690d", "NeedsCompilation": "no", "Title": "StarBioTrek", "Description": "This tool StarBioTrek presents some methodologies to measure pathway activity and cross-talk among pathways integrating also the information of network data.", "biocViews": [ "GeneRegulation", "KEGG", "Network", "Pathways", "Software" ], "Author": "Claudia Cava, Isabella Castiglioni", "Maintainer": "Claudia Cava ", "URL": "https://github.com/claudiacava/StarBioTrek", "VignetteBuilder": "knitr", "BugReports": "https://github.com/claudiacava/StarBioTrek/issues", "source.ver": "src/contrib/StarBioTrek_1.0.3.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/StarBioTrek_1.0.3.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/StarBioTrek_1.0.3.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/StarBioTrek_1.0.3.tgz", "vignettes": [ "vignettes/StarBioTrek/inst/doc/StarBioTrek_Application_Examples.pdf" ], "vignetteTitles": [ "StarBioTrek:Application Examples" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/StarBioTrek/inst/doc/StarBioTrek_Application_Examples.R", "vignettes/StarBioTrek/inst/doc/StarBioTrek.R" ], "htmlDocs": [ "vignettes/StarBioTrek/inst/doc/StarBioTrek.html" ], "htmlTitles": [ "Vignette Title" ] }, "Starr": { "Package": "Starr", "Version": "1.30.0", "Depends": [ "Ringo", "affy", "affxparser" ], "Imports": [ "pspline", "MASS", "zlibbioc" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "c15622ca6873530483644d694b87ce00", "NeedsCompilation": "yes", "Title": "Simple tiling array analysis of Affymetrix ChIP-chip data", "Description": "Starr facilitates the analysis of ChIP-chip data, in particular that of Affymetrix tiling arrays. The package provides functions for data import, quality assessment, data visualization and exploration. Furthermore, it includes high-level analysis features like association of ChIP signals with annotated features, correlation analysis of ChIP signals and other genomic data (e.g. gene expression), peak-finding with the CMARRT algorithm and comparative display of multiple clusters of ChIP-profiles. It uses the basic Bioconductor classes ExpressionSet and probeAnno for maximum compatibility with other software on Bioconductor. All functions from Starr can be used to investigate preprocessed data from the Ringo package, and vice versa. An important novel tool is the the automated generation of correct, up-to-date microarray probe annotation (bpmap) files, which relies on an efficient mapping of short sequences (e.g. the probe sequences on a microarray) to an arbitrary genome.", "biocViews": [ "ChIPchip", "DataImport", "Microarray", "OneChannel", "Preprocessing", "QualityControl", "Software" ], "Author": "Benedikt Zacher, Johannes Soeding, Pei Fen Kuan, Matthias Siebert, Achim Tresch", "Maintainer": "Benedikt Zacher ", "source.ver": "src/contrib/Starr_1.30.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Starr_1.30.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Starr_1.30.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Starr_1.30.0.tgz", "vignettes": [ "vignettes/Starr/inst/doc/Starr.pdf" ], "vignetteTitles": [ "Simple tiling array analysis" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Starr/inst/doc/Starr.R" ], "suggestsMe": [ "nucleR" ] }, "STATegRa": { "Package": "STATegRa", "Version": "1.8.0", "Depends": [ "R (>= 2.10)" ], "Imports": [ "Biobase", "gridExtra", "ggplot2", "methods", "stats", "grid", "MASS", "calibrate", "gplots", "edgeR", "limma", "foreach", "affy" ], "Suggests": [ "RUnit", "BiocGenerics", "knitr (>= 1.6)", "rmarkdown", "BiocStyle (>= 1.3)", "roxygen2", "doSNOW" ], "License": "GPL-2", "MD5sum": "093ca6bb9b0db52684d532ef1ca90bbb", "NeedsCompilation": "no", "Title": "Classes and methods for multi-omics data integration", "Description": "Classes and tools for multi-omics data integration.", "biocViews": [ "Clustering", "DimensionReduction", "PrincipalComponent", "Software", "StatisticalMethod" ], "Author": "STATegra Consortia", "Maintainer": "David Gomez-Cabrero , Patricia Sebastián-León , Gordon Ball ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/STATegRa_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/STATegRa_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/STATegRa_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/STATegRa_1.8.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/STATegRa/inst/doc/STATegRa.R" ], "htmlDocs": [ "vignettes/STATegRa/inst/doc/STATegRa.html" ], "htmlTitles": [ "STATegRa User's Guide" ] }, "statTarget": { "Package": "statTarget", "Version": "1.4.12", "Depends": [ "R (>= 3.3.0)" ], "Imports": [ "randomForest", "plyr", "pdist", "pROC", "utils", "grDevices", "graphics", "rrcov", "stats", "pls", "impute", "gWidgets2", "gWidgets2RGtk2" ], "Suggests": [ "testthat", "BiocStyle", "knitr", "rmarkdown" ], "License": "GPL (>= 2)", "MD5sum": "b801513abe4a0438c3aeca2c3e979e14", "NeedsCompilation": "no", "Title": "Statistical Analysis of Metabolite Profile", "Description": "An easy to use tool provides a graphical user interface for quality control based shift signal correction, integration of metabolomic data from multi-batch experiments, and the comprehensive statistic analysis in non-targeted or targeted metabolomics.", "biocViews": [ "BatchEffect", "DifferentialExpression", "GUI", "MassSpectrometry", "Metabolomics", "MultipleComparison", "Normalization", "Preprocessing", "QualityControl", "Software", "Visualization" ], "Author": "Hemi Luan", "Maintainer": "Hemi Luan ", "URL": "https://github.com/13479776/statTarget", "VignetteBuilder": "knitr", "source.ver": "src/contrib/statTarget_1.4.12.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/statTarget_1.4.12.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/statTarget_1.4.12.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/statTarget_1.4.12.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/statTarget/inst/doc/statTarget.R" ], "htmlDocs": [ "vignettes/statTarget/inst/doc/statTarget.html" ], "htmlTitles": [ "statTargetIntroduction" ] }, "stepNorm": { "Package": "stepNorm", "Version": "1.46.0", "Depends": [ "R (>= 1.8.0)", "marray", "methods" ], "Imports": [ "marray", "MASS", "methods", "stats" ], "License": "LGPL", "MD5sum": "f1ca8d3cb8357c883dfe6215dbbb7ec8", "NeedsCompilation": "no", "Title": "Stepwise normalization functions for cDNA microarrays", "Description": "Stepwise normalization functions for cDNA microarray data.", "biocViews": [ "Microarray", "Preprocessing", "Software", "TwoChannel" ], "Author": "Yuanyuan Xiao , Yee Hwa (Jean) Yang ", "Maintainer": "Yuanyuan Xiao ", "URL": "http://www.biostat.ucsf.edu/jean/", "source.ver": "src/contrib/stepNorm_1.46.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/stepNorm_1.46.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/stepNorm_1.46.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/stepNorm_1.46.0.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false }, "stepwiseCM": { "Package": "stepwiseCM", "Version": "1.20.0", "Depends": [ "R (>= 2.14)", "randomForest", "MAclinical", "tspair", "pamr", "snowfall", "glmpath", "penalized", "e1071", "Biobase" ], "License": "GPL (>2)", "MD5sum": "88fe5664bd08eec3e0d34ccbd5d39dc2", "NeedsCompilation": "no", "Title": "Stepwise Classification of Cancer Samples using High-dimensional Data Sets", "Description": "Stepwise classification of cancer samples using multiple data sets. This package implements the classification strategy using two heterogeneous data sets without actually combining them. Package uses the data type for which full measurements are available at the first stage, and the data type for which only partial measurements are available at the second stage. For incoming new samples package quantifies how much improvement will be obtained if covariates of new samples for the data types at the second stage are measured. This packages suits for the application where study goal is not only obtain high classification accuracy, but also requires economically cheap classifier.", "biocViews": [ "Classification", "Microarray", "Software" ], "Author": "Askar Obulkasim", "Maintainer": "Askar Obulkasim ", "source.ver": "src/contrib/stepwiseCM_1.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/stepwiseCM_1.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/stepwiseCM_1.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/stepwiseCM_1.20.0.tgz", "vignettes": [ "vignettes/stepwiseCM/inst/doc/stepwiseCM.pdf" ], "vignetteTitles": [ "stepwiseCM" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/stepwiseCM/inst/doc/stepwiseCM.R" ] }, "Streamer": { "Package": "Streamer", "Version": "1.20.0", "Imports": [ "methods", "graph", "RBGL", "parallel", "BiocGenerics" ], "Suggests": [ "RUnit", "Rsamtools (>= 1.5.53)", "GenomicAlignments", "Rgraphviz" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "a050bb74c17abbfd5fe7643b91efae04", "NeedsCompilation": "yes", "Title": "Enabling stream processing of large files", "Description": "Large data files can be difficult to work with in R, where data generally resides in memory. This package encourages a style of programming where data is 'streamed' from disk into R via a `producer' and through a series of `consumers' that, typically reduce the original data to a manageable size. The package provides useful Producer and Consumer stream components for operations such as data input, sampling, indexing, and transformation; see package?Streamer for details.", "biocViews": [ "DataImport", "Infrastructure", "Software" ], "Author": "Martin Morgan, Nishant Gopalakrishnan", "Maintainer": "Martin Morgan ", "source.ver": "src/contrib/Streamer_1.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Streamer_1.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Streamer_1.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Streamer_1.20.0.tgz", "vignettes": [ "vignettes/Streamer/inst/doc/Streamer.pdf" ], "vignetteTitles": [ "Streamer: A simple example" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Streamer/inst/doc/Streamer.R" ], "importsMe": [ "plethy" ] }, "STRINGdb": { "Package": "STRINGdb", "Version": "1.14.0", "Depends": [ "R (>= 2.14.0)" ], "Imports": [ "png", "sqldf", "plyr", "igraph", "RCurl", "methods", "RColorBrewer", "gplots", "hash", "plotrix" ], "Suggests": [ "RUnit", "BiocGenerics" ], "License": "GPL-2", "MD5sum": "0d8a03028b3e70f5bc712135be7c17ff", "NeedsCompilation": "no", "Title": "STRINGdb (Search Tool for the Retrieval of Interacting proteins database)", "Description": "The STRINGdb package provides a R interface to the STRING protein-protein interactions database (http://www.string-db.org).", "biocViews": [ "Network", "Software" ], "Author": "Andrea Franceschini ", "Maintainer": "Alexander Roth ", "source.ver": "src/contrib/STRINGdb_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/STRINGdb_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/STRINGdb_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/STRINGdb_1.14.0.tgz", "vignettes": [ "vignettes/STRINGdb/inst/doc/STRINGdb.pdf" ], "vignetteTitles": [ "STRINGdb Vignette" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/STRINGdb/inst/doc/STRINGdb.R" ], "dependsOnMe": [ "scsR" ], "importsMe": [ "pwOmics" ], "suggestsMe": [ "PCAN" ] }, "subSeq": { "Package": "subSeq", "Version": "1.4.0", "Depends": [ "R (>= 3.2)" ], "Imports": [ "data.table", "dplyr", "tidyr", "ggplot2", "magrittr", "qvalue (>= 1.99)", "digest", "Biobase" ], "Suggests": [ "limma", "edgeR", "DESeq2", "DEXSeq (>= 1.9.7)", "testthat", "knitr" ], "License": "MIT + file LICENSE", "MD5sum": "beb617ccaa7563d31418c1a3be9c3ba2", "NeedsCompilation": "no", "Title": "Subsampling of high-throughput sequencing count data", "Description": "Subsampling of high throughput sequencing count data for use in experiment design and analysis.", "biocViews": [ "DifferentialExpression", "GeneExpression", "RNASeq", "Sequencing", "Software", "Transcription" ], "Author": "David Robinson, John D. Storey, with contributions from Andrew J. Bass", "Maintainer": "Andrew J. Bass , John D. Storey ", "URL": "http://github.com/StoreyLab/subSeq", "VignetteBuilder": "knitr", "source.ver": "src/contrib/subSeq_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/subSeq_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/subSeq_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/subSeq_1.4.0.tgz", "vignettes": [ "vignettes/subSeq/inst/doc/subSeq.pdf" ], "vignetteTitles": [ "subSeq Example" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/subSeq/inst/doc/subSeq.R" ] }, "SummarizedExperiment": { "Package": "SummarizedExperiment", "Version": "1.4.0", "Depends": [ "R (>= 3.2)", "methods", "GenomicRanges (>= 1.23.15)", "Biobase" ], "Imports": [ "utils", "stats", "Matrix", "BiocGenerics (>= 0.15.3)", "S4Vectors (>= 0.11.7)", "IRanges (>= 2.7.2)", "GenomeInfoDb" ], "Suggests": [ "annotate", "AnnotationDbi", "hgu95av2.db", "GenomicFeatures", "TxDb.Hsapiens.UCSC.hg19.knownGene", "BiocStyle", "knitr", "rmarkdown", "digest", "jsonlite", "rhdf5", "airway", "RUnit" ], "License": "Artistic-2.0", "MD5sum": "35159a339981efa22e96db639dadc850", "NeedsCompilation": "no", "Title": "SummarizedExperiment container", "Description": "The SummarizedExperiment container contains one or more assays, each represented by a matrix-like object of numeric or other mode. The rows typically represent genomic ranges of interest and the columns represent samples.", "biocViews": [ "Annotation", "Coverage", "Genetics", "GenomeAnnotation", "Infrastructure", "Sequencing", "Software" ], "Author": "Martin Morgan, Valerie Obenchain, Jim Hester, Hervé Pagès", "Maintainer": "Bioconductor Package Maintainer ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/SummarizedExperiment_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SummarizedExperiment_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SummarizedExperiment_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SummarizedExperiment_1.4.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SummarizedExperiment/inst/doc/SummarizedExperiment.R" ], "htmlDocs": [ "vignettes/SummarizedExperiment/inst/doc/SummarizedExperiment.html" ], "htmlTitles": [ "SummarizedExperiment" ], "dependsOnMe": [ "airway", "AllelicImbalance", "anamiR", "BiSeq", "bsseq", "clusterExperiment", "csaw", "deepSNV", "DESeq2", "DEXSeq", "DiffBind", "diffHic", "DREAM4", "dsQTL", "epigenomix", "ExpressionAtlas", "fission", "GenoGAM", "GenomicAlignments", "GenomicFiles", "genoset", "geuvPack", "GRmetrics", "HelloRanges", "InteractionSet", "isomiRs", "JunctionSeq", "MAST", "MBASED", "methylPipe", "minfi", "parathyroidSE", "recount", "RIPSeeker", "scRNAseq", "SGSeq", "simulatorZ", "soGGi", "VanillaICE", "VariantAnnotation", "yamss", "yriMulti" ], "importsMe": [ "ALDEx2", "alpine", "anamiR", "BBCAnalyzer", "biovizBase", "BiSeq", "ChIPpeakAnno", "CNPBayes", "COSMIC.67", "DChIPRep", "debrowser", "DEFormats", "easyRNASeq", "EnrichmentBrowser", "ensemblVEP", "epivizrData", "erma", "FourCSeq", "GGBase", "ggbio", "gQTLBase", "gQTLstats", "GreyListChIP", "gwascat", "HTSeqGenie", "IHWpaper", "M3D", "MADSEQ", "methyAnalysis", "methylumi", "MinimumDistance", "MoonlightR", "MultiAssayExperiment", "MultiDataSet", "MutationalPatterns", "oligoClasses", "pcaExplorer", "PureCN", "R453Plus1Toolbox", "readat", "regionReport", "regsplice", "rgsepd", "roar", "SeqArray", "SNPchip", "SNPhood", "SVAPLSseq", "systemPipeR", "TCGAbiolinks", "ToPASeq", "TVTB", "VariantFiltering" ], "suggestsMe": [ "AnnotationHub", "biobroom", "epivizr", "esetVis", "GenomicRanges", "globalSeq", "HDF5Array", "interactiveDisplay", "podkat", "RiboProfiling" ] }, "supraHex": { "Package": "supraHex", "Version": "1.12.0", "Depends": [ "R (>= 3.0.2)", "hexbin" ], "Imports": [ "ape", "MASS" ], "License": "GPL-2", "MD5sum": "54fe52f84e30678a2071db727a1fd66f", "NeedsCompilation": "no", "Title": "supraHex: a supra-hexagonal map for analysing tabular omics data", "Description": "A supra-hexagonal map is a giant hexagon on a 2-dimensional grid seamlessly consisting of smaller hexagons. It is supposed to train, analyse and visualise a high-dimensional omics input data. The supraHex is able to carry out gene clustering/meta-clustering and sample correlation, plus intuitive visualisations to facilitate exploratory analysis. More importantly, it allows for overlaying additional data onto the trained map to explore relations between input and additional data. So with supraHex, it is also possible to carry out multilayer omics data comparisons. Newly added utilities are advanced heatmap visualisation and tree-based analysis of sample relationships. Uniquely to this package, users can ultrafastly understand any tabular omics data, both scientifically and artistically, especially in a sample-specific fashion but without loss of information on large genes.", "biocViews": [ "Clustering", "GeneExpression", "Software", "Visualization" ], "Author": "Hai Fang and Julian Gough", "Maintainer": "Hai Fang ", "URL": "http://suprahex.r-forge.r-project.org", "source.ver": "src/contrib/supraHex_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/supraHex_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/supraHex_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/supraHex_1.12.0.tgz", "vignettes": [ "vignettes/supraHex/inst/doc/supraHex_vignettes.pdf" ], "vignetteTitles": [ "supraHex User Manual" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/supraHex/inst/doc/supraHex_vignettes.R" ], "importsMe": [ "Pi", "TCGAbiolinks" ] }, "survcomp": { "Package": "survcomp", "Version": "1.24.0", "Depends": [ "survival", "prodlim", "R (>= 2.10)" ], "Imports": [ "ipred", "SuppDists", "KernSmooth", "survivalROC", "bootstrap", "grid", "rmeta" ], "Suggests": [ "Hmisc", "CPE", "clinfun", "Biobase" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "2eb9284a8369312d6fcc837494f80a63", "NeedsCompilation": "yes", "Title": "Performance Assessment and Comparison for Survival Analysis", "Description": "R package providing functions to assess and to compare the performance of risk prediction (survival) models.", "biocViews": [ "DifferentialExpression", "GeneExpression", "Software", "Visualization" ], "Author": "Benjamin Haibe-Kains, Markus Schroeder, Catharina Olsen, Christos Sotiriou, Gianluca Bontempi, John Quackenbush", "Maintainer": "Benjamin Haibe-Kains , Markus Schroeder , Catharina Olsen ", "URL": "http://www.pmgenomics.ca/bhklab/", "source.ver": "src/contrib/survcomp_1.24.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/survcomp_1.24.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/survcomp_1.24.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/survcomp_1.24.0.tgz", "vignettes": [ "vignettes/survcomp/inst/doc/survcomp.pdf" ], "vignetteTitles": [ "SurvComp: a package for performance assessment and comparison for survival analysis" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/survcomp/inst/doc/survcomp.R" ], "dependsOnMe": [ "genefu" ], "importsMe": [ "GenRank" ], "suggestsMe": [ "breastCancerMAINZ", "breastCancerNKI", "breastCancerTRANSBIG", "breastCancerUNT", "breastCancerUPP", "breastCancerVDX", "metaseqR" ] }, "Sushi": { "Package": "Sushi", "Version": "1.12.0", "Depends": [ "R (>= 2.10)", "zoo", "biomaRt" ], "Imports": [ "graphics", "grDevices" ], "License": "GPL (>= 2)", "MD5sum": "f1c0321bd94b6749fcd1d4437d9b2a79", "NeedsCompilation": "no", "Title": "Tools for visualizing genomics data", "Description": "Flexible, quantitative, and integrative genomic visualizations for publication-quality multi-panel figures", "biocViews": [ "DataRepresentation", "Genetics", "HiC", "Infrastructure", "Sequencing", "Software", "Visualization" ], "Author": "Douglas H Phanstiel ", "Maintainer": "Douglas H Phanstiel ", "source.ver": "src/contrib/Sushi_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Sushi_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Sushi_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Sushi_1.12.0.tgz", "vignettes": [ "vignettes/Sushi/inst/doc/Sushi.pdf" ], "vignetteTitles": [ "Sushi" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Sushi/inst/doc/Sushi.R" ], "importsMe": [ "diffloop", "psichomics" ] }, "sva": { "Package": "sva", "Version": "3.22.0", "Depends": [ "R (>= 2.8)", "mgcv", "genefilter" ], "Suggests": [ "limma", "pamr", "bladderbatch", "BiocStyle", "zebrafishRNASeq", "testthat" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "21715175f74be20918e8499b3e427ba4", "NeedsCompilation": "yes", "Title": "Surrogate Variable Analysis", "Description": "The sva package contains functions for removing batch effects and other unwanted variation in high-throughput experiment. Specifically, the sva package contains functions for the identifying and building surrogate variables for high-dimensional data sets. Surrogate variables are covariates constructed directly from high-dimensional data (like gene expression/RNA sequencing/methylation/brain imaging data) that can be used in subsequent analyses to adjust for unknown, unmodeled, or latent sources of noise. The sva package can be used to remove artifacts in three ways: (1) identifying and estimating surrogate variables for unknown sources of variation in high-throughput experiments (Leek and Storey 2007 PLoS Genetics,2008 PNAS), (2) directly removing known batch effects using ComBat (Johnson et al. 2007 Biostatistics) and (3) removing batch effects with known control probes (Leek 2014 biorXiv). Removing batch effects and using surrogate variables in differential expression analysis have been shown to reduce dependence, stabilize error rate estimates, and improve reproducibility, see (Leek and Storey 2007 PLoS Genetics, 2008 PNAS or Leek et al. 2011 Nat. Reviews Genetics).", "biocViews": [ "BatchEffect", "Microarray", "MultipleComparison", "Normalization", "Preprocessing", "RNASeq", "Sequencing", "Software", "StatisticalMethod" ], "Author": "Jeffrey T. Leek , W. Evan Johnson , Hilary S. Parker , Elana J. Fertig , Andrew E. Jaffe , John D. Storey ", "Maintainer": "Jeffrey T. Leek , John D. Storey , W. Evan Johnson ", "source.ver": "src/contrib/sva_3.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/sva_3.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/sva_3.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/sva_3.22.0.tgz", "vignettes": [ "vignettes/sva/inst/doc/sva.pdf" ], "vignetteTitles": [ "sva tutorial" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/sva/inst/doc/sva.R" ], "dependsOnMe": [ "SCAN.UPC" ], "importsMe": [ "ballgown", "BatchQC", "ChAMP", "charm", "crossmeta", "debrowser", "DeSousa2013", "doppelgangR", "edge", "ENmix", "LINC", "MEAL", "PAA", "trigger" ], "suggestsMe": [ "curatedBladderData", "curatedCRCData", "curatedOvarianData", "Harman", "RnBeads", "SomaticSignatures" ] }, "SVAPLSseq": { "Package": "SVAPLSseq", "Version": "1.0.0", "Depends": [ "R (>= 3.3)" ], "Imports": [ "methods", "stats", "SummarizedExperiment", "edgeR", "ggplot2", "limma", "lmtest", "parallel", "pls" ], "Suggests": [ "BiocStyle" ], "License": "GPL-3", "MD5sum": "d5b2ab50175945af859bd09eba0ef0d7", "NeedsCompilation": "no", "Title": "SVAPLSseq-An R package to adjust for the hidden factors of variability in differential gene expression studies based on RNAseq data", "Description": "The package contains functions that are intended for the identification of differentially expressed genes between two groups of samples from RNAseq data after adjusting for various hidden biological and technical factors of variability.", "biocViews": [ "BatchEffect", "GeneExpression", "Normalization", "RNASeq", "Software" ], "Author": "Sutirtha Chakraborty", "Maintainer": "Sutirtha Chakraborty ", "source.ver": "src/contrib/SVAPLSseq_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SVAPLSseq_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SVAPLSseq_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SVAPLSseq_1.0.0.tgz", "vignettes": [ "vignettes/SVAPLSseq/inst/doc/SVAPLSseq.pdf" ], "vignetteTitles": [ "SVAPLSseq tutorial" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SVAPLSseq/inst/doc/SVAPLSseq.R" ] }, "SVM2CRM": { "Package": "SVM2CRM", "Version": "1.6.0", "Depends": [ "R (>= 3.2.0)", "LiblineaR", "SVM2CRMdata" ], "Imports": [ "AnnotationDbi", "mclust", "GenomicRanges", "IRanges", "zoo", "squash", "pls", "rtracklayer", "ROCR", "verification" ], "License": "GPL-3", "MD5sum": "b96bb7923165b6b1eec3e6503045c034", "NeedsCompilation": "no", "Title": "SVM2CRM: support vector machine for cis-regulatory elements detections", "Description": "Detection of cis-regulatory elements using svm implemented in LiblineaR.", "biocViews": [ "ChIPSeq", "ChipOnChip", "Preprocessing", "Software", "SupportVectorMachine" ], "Author": "Guidantonio Malagoli Tagliazucchi ", "Maintainer": "Guidantonio Malagoli Tagliazucchi ", "source.ver": "src/contrib/SVM2CRM_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SVM2CRM_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SVM2CRM_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SVM2CRM_1.6.0.tgz", "vignettes": [ "vignettes/SVM2CRM/inst/doc/SVM2CRM.pdf" ], "vignetteTitles": [ "The \\Rpackage{SVM2CRM} Package" ], "hasREADME": true, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SVM2CRM/inst/doc/SVM2CRM.R" ] }, "SWATH2stats": { "Package": "SWATH2stats", "Version": "1.4.1", "Depends": [ "R(>= 2.10.0)" ], "Imports": [ "data.table", "reshape2", "grid", "ggplot2", "stats", "grDevices", "graphics", "utils" ], "Suggests": [ "testthat", "aLFQ", "knitr" ], "Enhances": [ "imsbInfer", "MSstats" ], "License": "GPL-3", "MD5sum": "ef242b9c95003f5f9acbc5ae504a2b65", "NeedsCompilation": "no", "Title": "Transform and Filter SWATH Data for Statistical Packages", "Description": "This package is intended to transform SWATH data from the OpenSWATH software into a format readable by other statistics packages while performing filtering, annotation and FDR estimation.", "biocViews": [ "Annotation", "ExperimentalDesign", "MassSpectrometry", "Preprocessing", "Proteomics", "Software" ], "Author": "Peter Blattmann, Moritz Heusel and Ruedi Aebersold", "Maintainer": "Peter Blattmann ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/SWATH2stats_1.4.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SWATH2stats_1.4.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SWATH2stats_1.4.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SWATH2stats_1.4.1.tgz", "vignettes": [ "vignettes/SWATH2stats/inst/doc/SWATH2stats_example_script.pdf", "vignettes/SWATH2stats/inst/doc/SWATH2stats_vignette.pdf" ], "vignetteTitles": [ "SWATH2stats example script", "SWATH2stats package Vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SWATH2stats/inst/doc/SWATH2stats_example_script.R", "vignettes/SWATH2stats/inst/doc/SWATH2stats_vignette.R" ] }, "SwathXtend": { "Package": "SwathXtend", "Version": "1.2.0", "Depends": [ "e1071", "openxlsx", "VennDiagram", "lattice" ], "License": "GPL-2", "MD5sum": "00dbc03735f0135ab56112bc51e8ccf5", "NeedsCompilation": "no", "Title": "SWATH extended library generation and satistical data analysis", "Description": "It contains utility functions for integrating spectral libraries for SWATH and statistical data analysis for SWATH generated data.", "biocViews": [ "Software" ], "Author": "J WU and D Pascovici", "Maintainer": "Jemma Wu ", "source.ver": "src/contrib/SwathXtend_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SwathXtend_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SwathXtend_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SwathXtend_1.2.0.tgz", "vignettes": [ "vignettes/SwathXtend/inst/doc/SwathXtend_vignette.pdf" ], "vignetteTitles": [ "SwathXtend" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SwathXtend/inst/doc/SwathXtend_vignette.R" ] }, "SwimR": { "Package": "SwimR", "Version": "1.12.0", "Depends": [ "R (>= 3.0.0)", "methods", "gplots (>= 2.10.1)", "heatmap.plus (>= 1.3)", "signal (>= 0.7)", "R2HTML (>= 2.2.1)" ], "Imports": [ "methods" ], "License": "LGPL-2", "MD5sum": "4bbe1f3403595ef76a139d78e43bee21", "NeedsCompilation": "no", "Title": "SwimR: A Suite of Analytical Tools for Quantification of C. elegans Swimming Behavior", "Description": "SwimR is an R-based suite that calculates, analyses, and plots the frequency of C. elegans swimming behavior over time. It places a particular emphasis on identifying paralysis and quantifying the kinetic elements of paralysis during swimming. Data is input to SwipR from a custom built program that fits a 5 point morphometric spine to videos of single worms swimming in a buffer called Worm Tracker.", "biocViews": [ "Software", "Visualization" ], "Author": "Jing Wang , Andrew Hardaway and Bing Zhang ", "Maintainer": "Randy Blakely ", "source.ver": "src/contrib/SwimR_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/SwimR_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/SwimR_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/SwimR_1.12.0.tgz", "vignettes": [ "vignettes/SwimR/inst/doc/SwimR.pdf" ], "vignetteTitles": [ "SwimR" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/SwimR/inst/doc/SwimR.R" ] }, "switchBox": { "Package": "switchBox", "Version": "1.10.0", "Depends": [ "R (>= 2.13.1)", "pROC", "gplots" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "3320c3c14013341f2023d9e3fa4cc649", "NeedsCompilation": "yes", "Title": "Utilities to train and validate classifiers based on pair switching using the K-Top-Scoring-Pair (KTSP) algorithm", "Description": "The package offer different classifiers based on comparisons of pair of features (TSP), using various decision rules (e.g., majority wins principle).", "biocViews": [ "Classification", "Software", "StatisticalMethod" ], "Author": "Bahman Afsari , Luigi Marchionni , Wikum Dinalankara ", "Maintainer": "Bahman Afsari , Luigi Marchionni , Wikum Dinalankara ", "source.ver": "src/contrib/switchBox_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/switchBox_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/switchBox_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/switchBox_1.10.0.tgz", "vignettes": [ "vignettes/switchBox/inst/doc/switchBox.pdf" ], "vignetteTitles": [ "Working with the switchBox package" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/switchBox/inst/doc/switchBox.R" ] }, "switchde": { "Package": "switchde", "Version": "1.0.0", "Depends": [ "R (>= 3.3)" ], "Imports": [ "Biobase", "dplyr", "ggplot2", "methods", "stats" ], "Suggests": [ "knitr", "rmarkdown", "BiocStyle", "testthat", "numDeriv", "tidyr", "scater" ], "License": "GPL (>= 2)", "MD5sum": "bfaedd3a185c5768aeb801e169d3f579", "NeedsCompilation": "no", "Title": "Switch-like differential expression across single-cell trajectories", "Description": "Inference and detection of switch-like differential expression across single-cell RNA-seq trajectories.", "biocViews": [ "DifferentialExpression", "GeneExpression", "RNASeq", "Regression", "Software", "Transcriptomics" ], "Author": "Kieran Campbell [aut, cre]", "Maintainer": "Kieran Campbell ", "URL": "https://github.com/kieranrcampbell/switchde", "VignetteBuilder": "knitr", "BugReports": "https://github.com/kieranrcampbell/switchde", "source.ver": "src/contrib/switchde_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/switchde_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/switchde_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/switchde_1.0.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/switchde/inst/doc/switchde_vignette.R" ], "htmlDocs": [ "vignettes/switchde/inst/doc/switchde_vignette.html" ], "htmlTitles": [ "An overview of the switchde package" ] }, "synapter": { "Package": "synapter", "Version": "1.16.0", "Depends": [ "R (>= 2.15)", "methods", "MSnbase" ], "Imports": [ "hwriter", "RColorBrewer", "lattice", "qvalue", "multtest", "utils", "Biobase", "knitr", "Biostrings", "cleaver", "BiocParallel" ], "Suggests": [ "synapterdata", "xtable", "tcltk", "BiocStyle" ], "License": "GPL-2", "MD5sum": "608b8548a532019258b5a00d65809123", "NeedsCompilation": "no", "Title": "Label-free data analysis pipeline for optimal identification and quantitation", "Description": "The synapter package provides functionality to reanalyse label-free proteomics data acquired on a Synapt G2 mass spectrometer. One or several runs, possibly processed with additional ion mobility separation to increase identification accuracy can be combined to other quantitation files to maximise identification and quantitation accuracy.", "biocViews": [ "GUI", "MassSpectrometry", "Proteomics", "Software" ], "Author": "Laurent Gatto, Nick J. Bond and Pavel V. Shliaha and Sebastian Gibb.", "Maintainer": "Laurent Gatto and Sebastian Gibb ", "URL": "http://lgatto.github.com/synapter/", "VignetteBuilder": "knitr", "source.ver": "src/contrib/synapter_1.16.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/synapter_1.16.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/synapter_1.16.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/synapter_1.16.0.tgz", "vignettes": [ "vignettes/synapter/inst/doc/synapter.pdf" ], "vignetteTitles": [ "Combining HDMSe/MSe data using 'synapter' to optimise identification and quantitation" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/synapter/inst/doc/synapter.R" ], "suggestsMe": [ "pRoloc", "RforProteomics" ], "dependsOnMe": [ "synapterdata" ] }, "synergyfinder": { "Package": "synergyfinder", "Version": "1.0.0", "Imports": [ "drc (>= 2.5-12)", "reshape2 (>= 1.4.1)", "kriging (>= 1.1)", "ggplot2 (>= 2.1.0)", "gridBase (>= 0.4-7)", "grid (>= 3.2.4)", "lattice (>= 0.20-33)", "gplots (>= 3.0.0)", "nleqslv(>= 3.0)", "stats (>= 3.3.0)", "graphics (>= 3.3.0)", "grDevices (>= 3.3.0)" ], "Suggests": [ "knitr", "rmarkdown" ], "License": "Artistic License 2.0", "MD5sum": "852030bc8660e6d8da014dcb0d6c20dd", "NeedsCompilation": "no", "Title": "Calculate and Visualize Synergy Scores for Drug Combinations", "Description": "Efficient implementations for all the popular synergy scoring models for drug combinations, including HSA, Loewe, Bliss and ZIP and visualization of the synergy scores as either a two-dimensional or a three-dimensional interaction surface over the dose matrix.", "biocViews": [ "Software", "Statistical Method" ], "Author": "Liye He , Jing Tang ", "Maintainer": "Liye He ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/synergyfinder_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/synergyfinder_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/synergyfinder_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/synergyfinder_1.0.0.tgz", "vignettes": [ "vignettes/synergyfinder/inst/doc/synergyfinder.pdf" ], "vignetteTitles": [ "synergyfinder" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/synergyfinder/inst/doc/synergyfinder.R" ] }, "synlet": { "Package": "synlet", "Version": "1.4.0", "Depends": [ "R (>= 3.2.0)", "ggplot2" ], "Imports": [ "doBy", "dplyr", "grid", "magrittr", "RColorBrewer", "RankProd", "reshape2" ], "Suggests": [ "knitr", "testthat" ], "License": "GPL-3", "MD5sum": "c08d5273d398b7eb9693a868f48c87db", "NeedsCompilation": "no", "Title": "Hits Selection for Synthetic Lethal RNAi Screen Data", "Description": "Select hits from synthetic lethal RNAi screen data. For example, there are two identical celllines except one gene is knocked-down in one cellline. The interest is to find genes that lead to stronger lethal effect when they are knocked-down further by siRNA. Quality control and various visualisation tools are implemented. Four different algorithms could be used to pick up the interesting hits. This package is designed based on 384 wells plates, but may apply to other platforms with proper configuration.", "biocViews": [ "CellBasedAssays", "FeatureExtraction", "Preprocessing", "QualityControl", "Software", "Visualization" ], "Author": "Chunxuan Shao ", "Maintainer": "Chunxuan Shao ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/synlet_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/synlet_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/synlet_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/synlet_1.4.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/synlet/inst/doc/synlet-vignette.R" ], "htmlDocs": [ "vignettes/synlet/inst/doc/synlet-vignette.html" ], "htmlTitles": [ "A working Demo for synlet" ] }, "systemPipeR": { "Package": "systemPipeR", "Version": "1.8.1", "Depends": [ "Rsamtools", "Biostrings", "ShortRead", "methods" ], "Imports": [ "BiocGenerics", "GenomicRanges", "GenomicFeatures", "SummarizedExperiment", "VariantAnnotation", "rjson", "ggplot2", "grid", "limma", "edgeR", "DESeq2", "GOstats", "GO.db", "annotate", "pheatmap", "BatchJobs" ], "Suggests": [ "ape", "RUnit", "BiocStyle", "knitr", "rmarkdown", "biomaRt", "BiocParallel" ], "License": "Artistic-2.0", "MD5sum": "e9b8c86f1ba8ebc82dc2e88a664ca6f9", "NeedsCompilation": "no", "Title": "systemPipeR: NGS workflow and report generation environment", "Description": "R package for building and running automated end-to-end analysis workflows for a wide range of next generation sequence (NGS) applications such as RNA-Seq, ChIP-Seq, VAR-Seq and Ribo-Seq. Important features include a uniform workflow interface across different NGS applications, automated report generation, and support for running both R and command-line software, such as NGS aligners or peak/variant callers, on local computers or compute clusters. Efficient handling of complex sample sets and experimental designs is facilitated by a consistently implemented sample annotation infrastructure. Instructions for using systemPipeR are given in the Overview Vignette (HTML). The remaining Vignettes, linked below, are workflow templates for common NGS use cases.", "biocViews": [ "Alignment", "ChIPSeq", "Coverage", "DataImport", "GeneExpression", "GeneSetEnrichment", "Genetics", "Infrastructure", "MethylSeq", "QualityControl", "RNASeq", "RiboSeq", "SNP", "Sequencing", "Software" ], "Author": "Thomas Girke", "Maintainer": "Thomas Girke ", "URL": "https://github.com/tgirke/systemPipeR", "SystemRequirements": "systemPipeR can be used to run external command-line software (e.g. short read aligners), but the corresponding tool needs to be installed on a system.", "VignetteBuilder": "knitr", "source.ver": "src/contrib/systemPipeR_1.8.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/systemPipeR_1.8.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/systemPipeR_1.8.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/systemPipeR_1.8.1.tgz", "vignettes": [ "vignettes/systemPipeR/inst/doc/systemPipeChIPseq.pdf", "vignettes/systemPipeR/inst/doc/systemPipeRIBOseq.pdf", "vignettes/systemPipeR/inst/doc/systemPipeRNAseq.pdf", "vignettes/systemPipeR/inst/doc/systemPipeVARseq.pdf" ], "vignetteTitles": [ "ChIP-Seq Workflow Template", "Ribo-Seq Workflow Template", "RNA-Seq Workflow Template", "VAR-Seq Workflow Template" ], "hasREADME": true, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/systemPipeR/inst/doc/systemPipeChIPseq.R", "vignettes/systemPipeR/inst/doc/systemPipeR.R", "vignettes/systemPipeR/inst/doc/systemPipeRIBOseq.R", "vignettes/systemPipeR/inst/doc/systemPipeRNAseq.R", "vignettes/systemPipeR/inst/doc/systemPipeVARseq.R" ], "htmlDocs": [ "vignettes/systemPipeR/inst/doc/systemPipeR.html" ], "htmlTitles": [ "Overview Vignette" ], "importsMe": [ "DiffBind" ], "suggestsMe": [ "systemPipeRdata" ] }, "TargetScore": { "Package": "TargetScore", "Version": "1.12.0", "Depends": [ "pracma", "Matrix" ], "Suggests": [ "TargetScoreData", "gplots", "Biobase", "GEOquery" ], "License": "GPL-2", "MD5sum": "6cd2503dda7cd6fec7f82826aa868987", "NeedsCompilation": "no", "Title": "TargetScore: Infer microRNA targets using microRNA-overexpression data and sequence information", "Description": "Infer the posterior distributions of microRNA targets by probabilistically modelling the likelihood microRNA-overexpression fold-changes and sequence-based scores. Variaitonal Bayesian Gaussian mixture model (VB-GMM) is applied to log fold-changes and sequence scores to obtain the posteriors of latent variable being the miRNA targets. The final targetScore is computed as the sigmoid-transformed fold-change weighted by the averaged posteriors of target components over all of the features.", "biocViews": [ "Software", "miRNA" ], "Author": "Yue Li", "Maintainer": "Yue Li ", "URL": "http://www.cs.utoronto.ca/~yueli/software.html", "source.ver": "src/contrib/TargetScore_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/TargetScore_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/TargetScore_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/TargetScore_1.12.0.tgz", "vignettes": [ "vignettes/TargetScore/inst/doc/TargetScore.pdf" ], "vignetteTitles": [ "TargetScore: Infer microRNA targets using microRNA-overexpression data and sequence information" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/TargetScore/inst/doc/TargetScore.R" ], "suggestsMe": [ "TargetScoreData" ] }, "TargetSearch": { "Package": "TargetSearch", "Version": "1.30.0", "Depends": [ "ncdf4" ], "Imports": [ "graphics", "grDevices", "methods", "stats", "tcltk", "utils" ], "Suggests": [ "TargetSearchData" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "2dc7b0ad63c4b70f3eb6e5152ebfd665", "NeedsCompilation": "yes", "Title": "A package for the analysis of GC-MS metabolite profiling data", "Description": "This packages provides a targeted pre-processing method for GC-MS data.", "biocViews": [ "DecisionTree", "MassSpectrometry", "Preprocessing", "Software" ], "Author": "Alvaro Cuadros-Inostroza , Jan Lisec , Henning Redestig , Matt Hannah ", "Maintainer": "Alvaro Cuadros-Inostroza ", "source.ver": "src/contrib/TargetSearch_1.30.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/TargetSearch_1.30.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/TargetSearch_1.30.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/TargetSearch_1.30.0.tgz", "vignettes": [ "vignettes/TargetSearch/inst/doc/RICorrection.pdf", "vignettes/TargetSearch/inst/doc/TargetSearch.pdf" ], "vignetteTitles": [ "RI correction", "The TargetSearch Package" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/TargetSearch/inst/doc/RICorrection.R", "vignettes/TargetSearch/inst/doc/TargetSearch.R" ], "dependsOnMe": [ "TargetSearchData" ] }, "TarSeqQC": { "Package": "TarSeqQC", "Version": "1.4.1", "Depends": [ "R (>= 3.2.1)", "methods", "GenomicRanges", "Rsamtools (>= 1.20.4)", "ggplot2", "plyr", "openxlsx" ], "Imports": [ "grDevices", "stats", "utils", "S4Vectors", "IRanges", "BiocGenerics", "reshape2", "GenomeInfoDb", "BiocParallel", "Biostrings", "cowplot", "graphics", "GenomicAlignments", "Hmisc" ], "Suggests": [ "RUnit" ], "License": "GPL (>=2)", "MD5sum": "db86c32097a196c620ee80ce3e56bf99", "NeedsCompilation": "no", "Title": "TARgeted SEQuencing Experiment Quality Control", "Description": "The package allows the representation of targeted experiment in R. This is based on current packages and incorporates functions to do a quality control over this kind of experiments and a fast exploration of the sequenced regions. An xlsx file is generated as output.", "biocViews": [ "Alignment", "Coverage", "DataImport", "QualityControl", "Sequencing", "Software", "TargetedResequencing", "Visualization" ], "Author": "Gabriela A. Merino, Cristobal Fresno, Yanina Murua, Andrea S. Llera and Elmer A. Fernandez", "Maintainer": "Gabriela Merino ", "URL": "http://www.bdmg.com.ar", "source.ver": "src/contrib/TarSeqQC_1.4.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/TarSeqQC_1.4.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/TarSeqQC_1.4.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/TarSeqQC_1.4.1.tgz", "vignettes": [ "vignettes/TarSeqQC/inst/doc/TarSeqQC-vignette.pdf" ], "vignetteTitles": [ "TarSeqQC: Targeted Sequencing Experiment Quality Control" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/TarSeqQC/inst/doc/TarSeqQC-vignette.R" ] }, "TCC": { "Package": "TCC", "Version": "1.14.0", "Depends": [ "R (>= 2.15)", "methods", "DESeq", "DESeq2", "edgeR", "baySeq", "ROC" ], "Imports": [ "samr" ], "Suggests": [ "RUnit", "BiocGenerics" ], "Enhances": [ "snow" ], "License": "GPL-2", "MD5sum": "d5c172f62e76240ffe1d649c054ec4ac", "NeedsCompilation": "no", "Title": "TCC: Differential expression analysis for tag count data with robust normalization strategies", "Description": "This package provides a series of functions for performing differential expression analysis from RNA-seq count data using robust normalization strategy (called DEGES). The basic idea of DEGES is that potential differentially expressed genes or transcripts (DEGs) among compared samples should be removed before data normalization to obtain a well-ranked gene list where true DEGs are top-ranked and non-DEGs are bottom ranked. This can be done by performing a multi-step normalization strategy (called DEGES for DEG elimination strategy). A major characteristic of TCC is to provide the robust normalization methods for several kinds of count data (two-group with or without replicates, multi-group/multi-factor, and so on) by virtue of the use of combinations of functions in depended packages.", "biocViews": [ "DifferentialExpression", "RNASeq", "Sequencing", "Software" ], "Author": "Jianqiang Sun, Tomoaki Nishiyama, Kentaro Shimizu, and Koji Kadota", "Maintainer": "Jianqiang Sun , Tomoaki Nishiyama ", "source.ver": "src/contrib/TCC_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/TCC_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/TCC_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/TCC_1.14.0.tgz", "vignettes": [ "vignettes/TCC/inst/doc/TCC.pdf" ], "vignetteTitles": [ "TCC" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/TCC/inst/doc/TCC.R" ], "suggestsMe": [ "compcodeR" ] }, "TCGAbiolinks": { "Package": "TCGAbiolinks", "Version": "2.2.10", "Depends": [ "R (>= 3.2)" ], "Imports": [ "downloader (>= 0.4)", "survminer", "grDevices", "gridExtra", "graphics", "tibble", "GenomicRanges", "XML (>= 3.98.0)", "Biobase", "affy", "xtable", "data.table", "EDASeq (>= 2.0.0)", "edgeR (>= 3.0.0)", "jsonlite (>= 1.0.0)", "plyr", "c3net", "minet", "knitr", "methods", "biomaRt", "gplots", "ggplot2", "ggthemes", "survival", "stringr (>= 1.0.0)", "IRanges", "scales", "rvest (>= 0.3.0)", "stats", "utils", "dnet", "igraph", "selectr", "supraHex", "S4Vectors", "ComplexHeatmap (>= 1.10.2)", "R.utils", "SummarizedExperiment (>= 1.4.0)", "limma", "genefilter", "ConsensusClusterPlus", "readr", "RColorBrewer", "doParallel", "dplyr", "clusterProfiler", "pathview", "parallel", "xml2", "httr (>= 1.2.1)", "parmigene", "matlab", "circlize", "ggrepel (>= 0.6.3)" ], "Suggests": [ "testthat", "png", "BiocStyle", "rmarkdown", "devtools" ], "License": "GPL (>= 3)", "MD5sum": "0e3d4f1018ae2d8eeb3d30048534aa28", "NeedsCompilation": "no", "Title": "TCGAbiolinks: An R/Bioconductor package for integrative analysis with TCGA data", "Description": "The aim of TCGAbiolinks is : i) facilitate the TCGA open-access data retrieval, ii) prepare the data using the appropriate pre-processing strategies, iii) provide the means to carry out different standard analyses and iv) allow the user to download a specific version of the data and thus to easily reproduce earlier research results. In more detail, the package provides multiple methods for analysis (e.g., differential expression analysis, identifying differentially methylated regions) and methods for visualization (e.g., survival plots, volcano plots, starburst plots) in order to easily develop complete analysis pipelines.", "biocViews": [ "DNAMethylation", "DifferentialExpression", "DifferentialMethylation", "GeneExpression", "GeneRegulation", "MethylationArray", "Network", "Pathways", "Sequencing", "Software", "Survival" ], "Author": "Antonio Colaprico, Tiago Chedraoui Silva, Catharina Olsen, Luciano Garofano, Davide Garolini, Claudia Cava, Thais Sabedot, Tathiane Malta, Stefano M. Pagnotta, Isabella Castiglioni, Michele Ceccarelli, Gianluca Bontempi, Houtan Noushmehr", "Maintainer": "Antonio Colaprico , Tiago Chedraoui Silva ", "URL": "https://github.com/BioinformaticsFMRP/TCGAbiolinks", "VignetteBuilder": "knitr", "BugReports": "https://github.com/BioinformaticsFMRP/TCGAbiolinks/issues", "source.ver": "src/contrib/TCGAbiolinks_2.2.10.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/TCGAbiolinks_2.2.10.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/TCGAbiolinks_2.2.10.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/TCGAbiolinks_2.2.10.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/TCGAbiolinks/inst/doc/clinical.R", "vignettes/TCGAbiolinks/inst/doc/download_prepare.R", "vignettes/TCGAbiolinks/inst/doc/index.R", "vignettes/TCGAbiolinks/inst/doc/mutation.R", "vignettes/TCGAbiolinks/inst/doc/query.R", "vignettes/TCGAbiolinks/inst/doc/tcgaBiolinks.R" ], "htmlDocs": [ "vignettes/TCGAbiolinks/inst/doc/clinical.html", "vignettes/TCGAbiolinks/inst/doc/download_prepare.html", "vignettes/TCGAbiolinks/inst/doc/index.html", "vignettes/TCGAbiolinks/inst/doc/mutation.html", "vignettes/TCGAbiolinks/inst/doc/query.html", "vignettes/TCGAbiolinks/inst/doc/tcgaBiolinks.html" ], "htmlTitles": [ "\"TCGAbiolinks: Clinical data\"", "\"TCGAbiolinks: Downloading and preparing files for analysis\"", "\"Introduction\"", "\"TCGAbiolinks: Mutation data\"", "\"TCGAbiolinks: Searching GDC database\"", "Working with TCGAbiolinks package" ], "importsMe": [ "MoonlightR", "SpidermiR" ] }, "TDARACNE": { "Package": "TDARACNE", "Version": "1.24.0", "Depends": [ "GenKern", "Rgraphviz", "Biobase" ], "License": "GPL-2", "MD5sum": "0b37553d793cc271172706dbb0ce3a3a", "NeedsCompilation": "no", "Title": "Network reverse engineering from time course data.", "Description": "To infer gene networks from time-series measurements is a current challenge into bioinformatics research area. In order to detect dependencies between genes at different time delays, we propose an approach to infer gene regulatory networks from time-series measurements starting from a well known algorithm based on information theory. The proposed algorithm is expected to be useful in reconstruction of small biological directed networks from time course data.", "biocViews": [ "Microarray", "Software", "TimeCourse" ], "Author": "Zoppoli P.,Morganella S., Ceccarelli M.", "Maintainer": "Zoppoli Pietro ", "source.ver": "src/contrib/TDARACNE_1.24.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/TDARACNE_1.24.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/TDARACNE_1.24.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/TDARACNE_1.24.0.tgz", "vignettes": [ "vignettes/TDARACNE/inst/doc/TDARACNE.pdf" ], "vignetteTitles": [ "TDARACNE" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/TDARACNE/inst/doc/TDARACNE.R" ] }, "TEQC": { "Package": "TEQC", "Version": "3.14.0", "Depends": [ "methods", "BiocGenerics (>= 0.1.0)", "IRanges (>= 1.13.5)", "Rsamtools", "hwriter" ], "Imports": [ "Biobase (>= 2.15.1)" ], "License": "GPL (>= 2)", "MD5sum": "457a51c9cd4767c02315d7acd7be3b69", "NeedsCompilation": "no", "Title": "Quality control for target capture experiments", "Description": "Target capture experiments combine hybridization-based (in solution or on microarrays) capture and enrichment of genomic regions of interest (e.g. the exome) with high throughput sequencing of the captured DNA fragments. This package provides functionalities for assessing and visualizing the quality of the target enrichment process, like specificity and sensitivity of the capture, per-target read coverage and so on.", "biocViews": [ "Genetics", "Microarray", "QualityControl", "Sequencing", "Software" ], "Author": "M. Hummel, S. Bonnin, E. Lowy, G. Roma", "Maintainer": "Manuela Hummel ", "source.ver": "src/contrib/TEQC_3.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/TEQC_3.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/TEQC_3.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/TEQC_3.14.0.tgz", "vignettes": [ "vignettes/TEQC/inst/doc/TEQC.pdf" ], "vignetteTitles": [ "TEQC" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/TEQC/inst/doc/TEQC.R" ] }, "ternarynet": { "Package": "ternarynet", "Version": "1.18.0", "Depends": [ "R (>= 2.10.0)", "methods" ], "Imports": [ "utils", "igraph" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "64d4ab58e4aeed86ebff75e26062d251", "NeedsCompilation": "yes", "Title": "Ternary Network Estimation", "Description": "A computational Bayesian approach to ternary gene regulatory network estimation from gene perturbation experiments.", "biocViews": [ "CellBiology", "GraphAndNetwork", "Software" ], "Author": "Matthew N. McCall , Anthony Almudevar ", "Maintainer": "Matthew N. McCall ", "source.ver": "src/contrib/ternarynet_1.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/ternarynet_1.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/ternarynet_1.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/ternarynet_1.18.0.tgz", "vignettes": [ "vignettes/ternarynet/inst/doc/ternarynet.pdf" ], "vignetteTitles": [ "ternarynet: A Computational Bayesian Approach to Ternary Network Estimation" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ternarynet/inst/doc/ternarynet.R" ] }, "TFBSTools": { "Package": "TFBSTools", "Version": "1.12.2", "Depends": [ "R (>= 3.2.2)" ], "Imports": [ "Biobase(>= 2.28)", "Biostrings(>= 2.36.4)", "BiocGenerics(>= 0.14.0)", "BiocParallel(>= 1.2.21)", "BSgenome(>= 1.36.3)", "caTools(>= 1.17.1)", "CNEr(>= 1.4.0)", "DirichletMultinomial(>= 1.10.0)", "GenomeInfoDb(>= 1.6.1)", "GenomicRanges(>= 1.20.6)", "gtools(>= 3.5.0)", "grid", "IRanges(>= 2.2.7)", "methods", "RSQLite(>= 1.0.0)", "rtracklayer(>= 1.28.10)", "seqLogo(>= 1.34.0)", "S4Vectors(>= 0.9.25)", "TFMPvalue(>= 0.0.5)", "XML(>= 3.98-1.3)", "XVector(>= 0.8.0)" ], "Suggests": [ "BiocStyle(>= 1.7.7)", "JASPAR2014(>= 1.4.0)", "knitr(>= 1.11)", "testthat", "JASPAR2016(>= 1.0.0)" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "66b2600a18baef085dea3d6fa25ad684", "NeedsCompilation": "yes", "Title": "Software Package for Transcription Factor Binding Site (TFBS) Analysis", "Description": "TFBSTools is a package for the analysis and manipulation of transcription factor binding sites. It includes matrices conversion between Position Frequency Matirx (PFM), Position Weight Matirx (PWM) and Information Content Matrix (ICM). It can also scan putative TFBS from sequence/alignment, query JASPAR database and provides a wrapper of de novo motif discovery software.", "biocViews": [ "Alignment", "GeneRegulation", "MotifAnnotation", "MotifDiscovery", "Software", "Transcription" ], "Author": "Ge Tan [aut, cre]", "Maintainer": "Ge Tan ", "URL": "https://github.com/ge11232002/TFBSTools", "VignetteBuilder": "knitr", "BugReports": "https://github.com/ge11232002/TFBSTools/issues", "source.ver": "src/contrib/TFBSTools_1.12.2.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/TFBSTools_1.12.2.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/TFBSTools_1.12.2.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/TFBSTools_1.12.2.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/TFBSTools/inst/doc/TFBSTools.R" ], "htmlDocs": [ "vignettes/TFBSTools/inst/doc/TFBSTools.html" ], "htmlTitles": [ "Transcription factor binding site (TFBS) analysis with the \"TFBSTools\" package" ], "importsMe": [ "MatrixRider" ] }, "tigre": { "Package": "tigre", "Version": "1.28.1", "Depends": [ "R (>= 2.11.0)", "BiocGenerics", "Biobase" ], "Imports": [ "methods", "AnnotationDbi", "gplots", "graphics", "stats", "utils", "annotate", "DBI", "RSQLite" ], "Suggests": [ "drosgenome1.db", "puma", "lumi", "BiocStyle" ], "License": "AGPL-3", "Archs": "i386, x64", "MD5sum": "fbe346e19cc6b8e86686bb21352ada55", "NeedsCompilation": "yes", "Title": "Transcription factor Inference through Gaussian process Reconstruction of Expression", "Description": "The tigre package implements our methodology of Gaussian process differential equation models for analysis of gene expression time series from single input motif networks. The package can be used for inferring unobserved transcription factor (TF) protein concentrations from expression measurements of known target genes, or for ranking candidate targets of a TF.", "biocViews": [ "Bayesian", "GeneExpression", "GeneRegulation", "Microarray", "NetworkInference", "Software", "TimeCourse", "Transcription" ], "Author": "Antti Honkela, Pei Gao, Jonatan Ropponen, Miika-Petteri Matikainen, Magnus Rattray, Neil D. Lawrence", "Maintainer": "Antti Honkela ", "URL": "https://github.com/ahonkela/tigre", "BugReports": "https://github.com/ahonkela/tigre/issues", "source.ver": "src/contrib/tigre_1.28.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/tigre_1.28.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/tigre_1.28.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/tigre_1.28.1.tgz", "vignettes": [ "vignettes/tigre/inst/doc/tigre_quick.pdf", "vignettes/tigre/inst/doc/tigre.pdf" ], "vignetteTitles": [ "tigre Quick Guide", "tigre User Guide" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/tigre/inst/doc/tigre_quick.R", "vignettes/tigre/inst/doc/tigre.R" ] }, "tilingArray": { "Package": "tilingArray", "Version": "1.52.0", "Depends": [ "R (>= 2.11.0)", "Biobase", "methods", "pixmap" ], "Imports": [ "strucchange", "affy", "vsn", "genefilter", "RColorBrewer", "grid", "stats4" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "95caedcd19de18a38f526b357d66c00a", "NeedsCompilation": "yes", "Title": "Transcript mapping with high-density oligonucleotide tiling arrays", "Description": "The package provides functionality that can be useful for the analysis of high-density tiling microarray data (such as from Affymetrix genechips) for measuring transcript abundance and architecture. The main functionalities of the package are: 1. the class 'segmentation' for representing partitionings of a linear series of data; 2. the function 'segment' for fitting piecewise constant models using a dynamic programming algorithm that is both fast and exact; 3. the function 'confint' for calculating confidence intervals using the strucchange package; 4. the function 'plotAlongChrom' for generating pretty plots; 5. the function 'normalizeByReference' for probe-sequence dependent response adjustment from a (set of) reference hybridizations.", "biocViews": [ "Microarray", "OneChannel", "Preprocessing", "Software", "Visualization" ], "Author": "Wolfgang Huber, Zhenyu Xu, Joern Toedling with contributions from Matt Ritchie", "Maintainer": "Zhenyu Xu ", "source.ver": "src/contrib/tilingArray_1.52.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/tilingArray_1.52.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/tilingArray_1.52.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/tilingArray_1.52.0.tgz", "vignettes": [ "vignettes/tilingArray/inst/doc/assessNorm.pdf", "vignettes/tilingArray/inst/doc/costMatrix.pdf", "vignettes/tilingArray/inst/doc/findsegments.pdf", "vignettes/tilingArray/inst/doc/plotAlongChrom.pdf", "vignettes/tilingArray/inst/doc/segmentation.pdf" ], "vignetteTitles": [ "Normalisation with the normalizeByReference function in the tilingArray package", "Supplement. Calculation of the cost matrix", "Introduction to using the segment function to fit a piecewise constant curve", "Introduction to the plotAlongChrom function", "Segmentation demo" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/tilingArray/inst/doc/findsegments.R", "vignettes/tilingArray/inst/doc/plotAlongChrom.R" ], "importsMe": [ "ADaCGH2", "snapCGH" ], "dependsOnMe": [ "davidTiling" ] }, "timecourse": { "Package": "timecourse", "Version": "1.46.0", "Depends": [ "R (>= 2.1.1)", "MASS", "methods" ], "Imports": [ "Biobase", "graphics", "limma (>= 1.8.6)", "MASS", "marray", "methods", "stats" ], "License": "LGPL", "MD5sum": "631555dff4cc9a6bc14267e4187cc533", "NeedsCompilation": "no", "Title": "Statistical Analysis for Developmental Microarray Time Course Data", "Description": "Functions for data analysis and graphical displays for developmental microarray time course data.", "biocViews": [ "DifferentialExpression", "Microarray", "Software", "TimeCourse" ], "Author": "Yu Chuan Tai", "Maintainer": "Yu Chuan Tai ", "URL": "http://www.bioconductor.org", "source.ver": "src/contrib/timecourse_1.46.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/timecourse_1.46.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/timecourse_1.46.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/timecourse_1.46.0.tgz", "vignettes": [ "vignettes/timecourse/inst/doc/timecourse.pdf" ], "vignetteTitles": [ "timecourse manual" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/timecourse/inst/doc/timecourse.R" ] }, "TIN": { "Package": "TIN", "Version": "1.6.0", "Depends": [ "R (>= 2.12.0)", "data.table", "impute", "aroma.affymetrix" ], "Imports": [ "WGCNA", "squash", "stringr" ], "Suggests": [ "knitr", "aroma.light", "affxparser", "RUnit", "BiocGenerics" ], "License": "Artistic-2.0", "MD5sum": "07de3229b35dddac0f3766b7b11f8069", "NeedsCompilation": "no", "Title": "Transcriptome instability analysis", "Description": "The TIN package implements a set of tools for transcriptome instability analysis based on exon expression profiles. Deviating exon usage is studied in the context of splicing factors to analyse to what degree transcriptome instability is correlated to splicing factor expression. In the transcriptome instability correlation analysis, the data is compared to both random permutations of alternative splicing scores and expression of random gene sets.", "biocViews": [ "AlternativeSplicing", "DifferentialSplicing", "ExonArray", "GeneExpression", "Genetics", "Microarray", "Software" ], "Author": "Bjarne Johannessen, Anita Sveen and Rolf I. Skotheim", "Maintainer": "Bjarne Johannessen ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/TIN_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/TIN_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/TIN_1.6.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/TIN_1.6.0.tgz", "vignettes": [ "vignettes/TIN/inst/doc/TIN.pdf" ], "vignetteTitles": [ "Introduction to the TIN package" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/TIN/inst/doc/TIN.R" ] }, "TitanCNA": { "Package": "TitanCNA", "Version": "1.12.0", "Depends": [ "R (>= 3.2.0)", "foreach (>= 1.4.2)", "IRanges (>= 2.2.4)", "GenomicRanges (>= 1.20.5)", "Rsamtools (>= 1.20.4)", "GenomeInfoDb (>= 1.4.0)" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "97095648ce826ef6d7c01c9d014f4459", "NeedsCompilation": "yes", "Title": "Subclonal copy number and LOH prediction from whole genome sequencing of tumours", "Description": "Hidden Markov model to segment and predict regions of subclonal copy number alterations (CNA) and loss of heterozygosity (LOH), and estimate cellular prevalenece of clonal clusters in tumour whole genome sequencing data.", "biocViews": [ "CopyNumberVariation", "DNASeq", "ExomeSeq", "Genetics", "GenomicVariation", "HiddenMarkovModel", "Sequencing", "Software", "StatisticalMethod", "WholeGenome" ], "Author": "Gavin Ha, Sohrab P Shah", "Maintainer": "Gavin Ha , Sohrab P Shah ", "URL": "https://github.com/gavinha/TitanCNA", "source.ver": "src/contrib/TitanCNA_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/TitanCNA_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/TitanCNA_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/TitanCNA_1.12.0.tgz", "vignettes": [ "vignettes/TitanCNA/inst/doc/TitanCNA.pdf" ], "vignetteTitles": [ "TitanCNA" ], "hasREADME": true, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/TitanCNA/inst/doc/TitanCNA.R" ] }, "tkWidgets": { "Package": "tkWidgets", "Version": "1.52.0", "Depends": [ "R (>= 2.0.0)", "methods", "widgetTools (>= 1.1.7)", "DynDoc (>= 1.3.0)", "tools" ], "Suggests": [ "Biobase", "hgu95av2" ], "License": "Artistic-2.0", "MD5sum": "760213ef99136478dcfdd497e6431094", "NeedsCompilation": "no", "Title": "R based tk widgets", "Description": "Widgets to provide user interfaces. tcltk should have been installed for the widgets to run.", "biocViews": [ "Infrastructure", "Software" ], "Author": "J. Zhang ", "Maintainer": "J. Zhang ", "source.ver": "src/contrib/tkWidgets_1.52.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/tkWidgets_1.52.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/tkWidgets_1.52.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/tkWidgets_1.52.0.tgz", "vignettes": [ "vignettes/tkWidgets/inst/doc/importWizard.pdf", "vignettes/tkWidgets/inst/doc/tkWidgets.pdf" ], "vignetteTitles": [ "tkWidgets importWizard", "tkWidgets contents" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/tkWidgets/inst/doc/importWizard.R", "vignettes/tkWidgets/inst/doc/tkWidgets.R" ], "dependsOnMe": [ "oneChannelGUI" ], "importsMe": [ "Mfuzz", "OLINgui" ], "suggestsMe": [ "affy", "affyQCReport", "annotate", "Biobase", "genefilter", "marray" ] }, "tofsims": { "Package": "tofsims", "Version": "1.2.0", "Depends": [ "R (>= 3.3.0)", "methods", "utils", "ProtGenerics" ], "Imports": [ "Rcpp (>= 0.11.2)", "ALS", "ChemometricsWithR", "signal", "KernSmooth", "graphics", "grDevices", "stats" ], "LinkingTo": [ "Rcpp", "RcppArmadillo" ], "Suggests": [ "EBImage", "knitr", "rmarkdown", "testthat", "tofsimsData", "BiocParallel", "RColorBrewer" ], "Enhances": [ "parallel" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "35da698acd9aeb58e1cd77452484b5ea", "NeedsCompilation": "yes", "Title": "Import, process and analysis of Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS) imaging data", "Description": "This packages offers a pipeline for import, processing and analysis of ToF-SIMS 2D image data. Import of Iontof and Ulvac-Phi raw or preprocessed data is supported. For rawdata, mass calibration, peak picking and peak integration exist. General funcionality includes data binning, scaling, image subsetting and visualization. A range of multivariate tools common in the ToF-SIMS community are implemented (PCA, MCR, MAF, MNF). An interface to the bioconductor image processing package EBImage offers image segmentation functionality.", "biocViews": [ "DataImport", "ImagingMassSpectrometry", "Infrastructure", "MassSpectrometry", "Metabolomics", "Proteomics", "Software" ], "Author": "Lorenz Gerber, Viet Mai Hoang", "Maintainer": "Lorenz Gerber ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/tofsims_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/tofsims_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/tofsims_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/tofsims_1.2.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/tofsims/inst/doc/workflow.R" ], "htmlDocs": [ "vignettes/tofsims/inst/doc/workflow.html" ], "htmlTitles": [ "Workflow with the `tofsims` package" ] }, "ToPASeq": { "Package": "ToPASeq", "Version": "1.8.0", "Depends": [ "graphite (>= 1.16)", "gRbase", "graph", "locfit", "Rgraphviz" ], "Imports": [ "R.utils", "methods", "Biobase", "parallel", "edgeR", "DESeq2", "SummarizedExperiment", "RBGL", "DESeq", "fields", "limma", "TeachingDemos", "KEGGgraph", "qpgraph", "clipper", "AnnotationDbi", "doParallel" ], "LinkingTo": [ "Rcpp" ], "Suggests": [ "RUnit", "BiocGenerics", "gageData", "DEGraph", "plotrix", "org.Hs.eg.db" ], "License": "AGPL-3", "MD5sum": "14a72a3acfd08b945927623687072475", "NeedsCompilation": "yes", "Title": "Package for Topology-based Pathway Analysis of RNASeq data", "Description": "Implementation of seven methods for topology-based pathway analysis of both RNASeq and microarray data: SPIA, DEGraph, TopologyGSA, TAPPA, PRS, PWEA and a visualization tool for a single pathway.", "biocViews": [ "DifferentialExpression", "GeneExpression", "GraphAndNetwork", "Microarray", "NetworkEnrichment", "Pathways", "RNASeq", "Software", "Visualization" ], "Author": "Ivana Ihnatova, Eva Budinska", "Maintainer": "Ivana Ihnatova ", "source.ver": "src/contrib/ToPASeq_1.8.0.tar.gz", "vignettes": [ "vignettes/ToPASeq/inst/doc/ToPASeq.pdf" ], "vignetteTitles": [ "An R Package for topology-based pathway analysis of microaray and RNA-Seq data" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/ToPASeq/inst/doc/ToPASeq.R" ] }, "topGO": { "Package": "topGO", "Version": "2.26.0", "Depends": [ "R (>= 2.10.0)", "methods", "BiocGenerics (>= 0.13.6)", "graph (>= 1.14.0)", "Biobase (>= 2.0.0)", "GO.db (>= 2.3.0)", "AnnotationDbi (>= 1.7.19)", "SparseM (>= 0.73)" ], "Imports": [ "lattice", "matrixStats", "DBI" ], "Suggests": [ "ALL", "hgu95av2.db", "hgu133a.db", "genefilter", "xtable", "multtest", "Rgraphviz", "globaltest" ], "License": "LGPL", "MD5sum": "7604873b748d0fa2c2825e814eec46bf", "NeedsCompilation": "no", "Title": "Enrichment Analysis for Gene Ontology", "Description": "topGO package provides tools for testing GO terms while accounting for the topology of the GO graph. Different test statistics and different methods for eliminating local similarities and dependencies between GO terms can be implemented and applied.", "biocViews": [ "Microarray", "Software", "Visualization" ], "Author": "Adrian Alexa, Jorg Rahnenfuhrer", "Maintainer": "Adrian Alexa ", "source.ver": "src/contrib/topGO_2.26.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/topGO_2.26.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/topGO_2.26.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/topGO_2.26.0.tgz", "vignettes": [ "vignettes/topGO/inst/doc/topGO.pdf" ], "vignetteTitles": [ "topGO" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/topGO/inst/doc/topGO.R" ], "dependsOnMe": [ "BgeeDB", "ccTutorial", "cellTree", "compEpiTools", "EGSEA", "RCAS", "RNAither", "tRanslatome" ], "importsMe": [ "cellity", "EnrichmentBrowser", "GOSim", "mvGST", "pcaExplorer", "psygenet2r", "SEPA" ], "suggestsMe": [ "clusterProfiler", "FGNet", "miRNAtap", "Ringo" ] }, "TPP": { "Package": "TPP", "Version": "3.0.3", "Depends": [ "R (>= 3.3)", "dplyr", "magrittr", "tidyr" ], "Imports": [ "Biobase", "doParallel", "foreach", "ggplot2", "gridExtra", "grid", "limma", "MASS", "nls2", "openxlsx (>= 2.4.0)", "parallel", "plyr", "RColorBrewer", "RCurl", "reshape2", "sme", "splines", "VennDiagram", "VGAM", "knitr", "rmarkdown", "grDevices", "stats", "utils" ], "Suggests": [ "BiocStyle", "testthat" ], "License": "Artistic-2.0", "MD5sum": "d49d19771b802b96b5d00b3aae42da26", "NeedsCompilation": "no", "Title": "Analyze thermal proteome profiling (TPP) experiments", "Description": "Analyze thermal proteome profiling (TPP) experiments with varying temperatures (TR) or compound concentrations (CCR).", "biocViews": [ "MassSpectrometry", "Proteomics", "Software" ], "Author": "Dorothee Childs, Nils Kurzawa, Holger Franken, Carola Doce, Mikhail Savitski and Wolfgang Huber", "Maintainer": "Dorothee Childs ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/TPP_3.0.3.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/TPP_3.0.3.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/TPP_3.0.3.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/TPP_3.0.3.tgz", "vignettes": [ "vignettes/TPP/inst/doc/NPARC_analysis_of_TPP_TR_data.pdf", "vignettes/TPP/inst/doc/TPP_introduction_1D.pdf", "vignettes/TPP/inst/doc/TPP_introduction_2D.pdf" ], "vignetteTitles": [ "TPP_introduction", "TPP_introduction_1D", "TPP_introduction_2D" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/TPP/inst/doc/NPARC_analysis_of_TPP_TR_data.R", "vignettes/TPP/inst/doc/TPP_introduction_1D.R", "vignettes/TPP/inst/doc/TPP_introduction_2D.R" ] }, "tracktables": { "Package": "tracktables", "Version": "1.8.1", "Depends": [ "R (>= 3.0.0)" ], "Imports": [ "IRanges", "GenomicRanges", "XVector", "Rsamtools", "XML", "tractor.base", "stringr", "RColorBrewer", "methods" ], "Suggests": [ "knitr", "BiocStyle" ], "License": "GPL (>= 3)", "MD5sum": "10ca3cfe2ebdebc931bd518e1433f3a2", "NeedsCompilation": "no", "Title": "Build IGV tracks and HTML reports", "Description": "Methods to create complex IGV genome browser sessions and dynamic IGV reports in HTML pages.", "biocViews": [ "ReportWriting", "Sequencing", "Software" ], "Author": "Tom Carroll, Sanjay Khadayate, Anne Pajon, Ziwei Liang", "Maintainer": "Tom Carroll ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/tracktables_1.8.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/tracktables_1.8.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/tracktables_1.8.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/tracktables_1.8.1.tgz", "vignettes": [ "vignettes/tracktables/inst/doc/tracktables.pdf" ], "vignetteTitles": [ "Creating IGV HTML reports with tracktables" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/tracktables/inst/doc/tracktables.R" ], "htmlDocs": [ "vignettes/tracktables/inst/doc/EBFGI.html", "vignettes/tracktables/inst/doc/IGV_Example.html", "vignettes/tracktables/inst/doc/IGVEx3.html", "vignettes/tracktables/inst/doc/index.html", "vignettes/tracktables/inst/doc/markdownexample.html" ], "htmlTitles": [ "EBFGI.html", "IGV_Example.html", "IGVEx3.html", "index.html", "Supplementary Materials" ] }, "trackViewer": { "Package": "trackViewer", "Version": "1.10.2", "Depends": [ "R (>= 3.1.0)", "grDevices", "methods", "GenomicRanges", "grid" ], "Imports": [ "GenomicAlignments", "GenomicFeatures", "Gviz", "pbapply", "Rsamtools", "rtracklayer", "S4Vectors", "scales", "tools", "IRanges", "AnnotationDbi", "grImport" ], "Suggests": [ "biomaRt", "TxDb.Hsapiens.UCSC.hg19.knownGene", "RUnit", "org.Hs.eg.db", "BiocGenerics", "BiocStyle", "knitr", "VariantAnnotation" ], "License": "GPL (>= 2)", "MD5sum": "6821d2ab9a433a6cd419b9f02c0af780", "NeedsCompilation": "no", "Title": "A bioconductor package with minimalist design for drawing elegant tracks or lollipop plot", "Description": "Visualize mapped reads along with annotation as track layers for NGS dataset such as ChIP-seq, RNA-seq, miRNA-seq, DNA-seq, SNPs and methylation data.", "biocViews": [ "Software", "Visualization" ], "Author": "Jianhong Ou, Yong-Xu Wang, Lihua Julie Zhu", "Maintainer": "Jianhong Ou ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/trackViewer_1.10.2.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/trackViewer_1.10.2.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/trackViewer_1.10.2.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/trackViewer_1.10.2.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/trackViewer/inst/doc/trackViewer.R" ], "htmlDocs": [ "vignettes/trackViewer/inst/doc/trackViewer.html" ], "htmlTitles": [ "trackViewer Vignette" ], "dependsOnMe": [ "coMET" ], "suggestsMe": [ "ChIPpeakAnno" ] }, "transcriptR": { "Package": "transcriptR", "Version": "1.2.0", "Depends": [ "methods", "R (>= 3.3)" ], "Imports": [ "BiocGenerics", "caret", "chipseq", "e1071", "GenomicAlignments", "GenomicRanges", "GenomicFeatures", "GenomeInfoDb", "ggplot2", "graphics", "grDevices", "IRanges", "pROC", "reshape2", "Rsamtools", "rtracklayer", "S4Vectors", "stats", "utils" ], "Suggests": [ "BiocStyle", "knitr", "rmarkdown", "TxDb.Hsapiens.UCSC.hg19.knownGene", "testthat" ], "License": "GPL-3", "MD5sum": "89c295ef60def07411a77d9afb22b87b", "NeedsCompilation": "no", "Title": "An Integrative Tool for ChIP- And RNA-Seq Based Primary Transcripts Detection and Quantification", "Description": "The differences in the RNA types being sequenced have an impact on the resulting sequencing profiles. mRNA-seq data is enriched with reads derived from exons, while GRO-, nucRNA- and chrRNA-seq demonstrate a substantial broader coverage of both exonic and intronic regions. The presence of intronic reads in GRO-seq type of data makes it possible to use it to computationally identify and quantify all de novo continuous regions of transcription distributed across the genome. This type of data, however, is more challenging to interpret and less common practice compared to mRNA-seq. One of the challenges for primary transcript detection concerns the simultaneous transcription of closely spaced genes, which needs to be properly divided into individually transcribed units. The R package transcriptR combines RNA-seq data with ChIP-seq data of histone modifications that mark active Transcription Start Sites (TSSs), such as, H3K4me3 or H3K9/14Ac to overcome this challenge. The advantage of this approach over the use of, for example, gene annotations is that this approach is data driven and therefore able to deal also with novel and case specific events. Furthermore, the integration of ChIP- and RNA-seq data allows the identification all known and novel active transcription start sites within a given sample.", "biocViews": [ "Coverage", "RNASeq", "Sequencing", "Software", "Transcription" ], "Author": "Armen R. Karapetyan ", "Maintainer": "Armen R. Karapetyan ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/transcriptR_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/transcriptR_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/transcriptR_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/transcriptR_1.2.0.tgz", "vignettes": [ "vignettes/transcriptR/inst/doc/transcriptR.pdf" ], "vignetteTitles": [ "transcriptR: an integrative tool for ChIP- and RNA-seq based primary transcripts detection and quantification" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/transcriptR/inst/doc/transcriptR.R" ] }, "tRanslatome": { "Package": "tRanslatome", "Version": "1.12.0", "Depends": [ "R (>= 2.15.0)", "methods", "limma", "sigPathway", "samr", "anota", "DESeq", "edgeR", "RankProd", "topGO", "org.Hs.eg.db", "GOSemSim", "Heatplus", "gplots", "plotrix", "Biobase" ], "License": "GPL-3", "MD5sum": "884e8e2ba5d827048b1f87588bcc1767", "NeedsCompilation": "no", "Title": "Comparison between multiple levels of gene expression", "Description": "Detection of differentially expressed genes (DEGs) from the comparison of two biological conditions (treated vs. untreated, diseased vs. normal, mutant vs. wild-type) among different levels of gene expression (transcriptome ,translatome, proteome), using several statistical methods: Rank Product, Translational Efficiency, t-test, SAM, Limma, ANOTA, DESeq, edgeR. Possibility to plot the results with scatterplots, histograms, MA plots, standard deviation (SD) plots, coefficient of variation (CV) plots. Detection of significantly enriched post-transcriptional regulatory factors (RBPs, miRNAs, etc) and Gene Ontology terms in the lists of DEGs previously identified for the two expression levels. Comparison of GO terms enriched only in one of the levels or in both. Calculation of the semantic similarity score between the lists of enriched GO terms coming from the two expression levels. Visual examination and comparison of the enriched terms with heatmaps, radar plots and barplots.", "biocViews": [ "Bioinformatics", "CellBiology", "DifferentialExpression", "GO", "GeneExpression", "GeneRegulation", "HighThroughputSequencing", "Microarray", "MultipleComparisons", "QualityControl", "Regulation", "Software" ], "Author": "Toma Tebaldi, Erik Dassi, Galena Kostoska", "Maintainer": "Toma Tebaldi , Erik Dassi ", "source.ver": "src/contrib/tRanslatome_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/tRanslatome_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/tRanslatome_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/tRanslatome_1.12.0.tgz", "vignettes": [ "vignettes/tRanslatome/inst/doc/tRanslatome_package.pdf" ], "vignetteTitles": [ "tRanslatome" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/tRanslatome/inst/doc/tRanslatome_package.R" ] }, "TransView": { "Package": "TransView", "Version": "1.18.0", "Depends": [ "methods", "GenomicRanges" ], "Imports": [ "BiocGenerics", "S4Vectors (>= 0.9.25)", "IRanges", "Rsamtools (>= 1.19.38)", "zlibbioc", "gplots" ], "LinkingTo": [ "Rsamtools" ], "Suggests": [ "RUnit", "pasillaBamSubset" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "ae4b3494b24f807cfc54022da4e9f919", "NeedsCompilation": "yes", "Title": "Read density map construction and accession. Visualization of ChIPSeq and RNASeq data sets", "Description": "This package provides efficient tools to generate, access and display read densities of sequencing based data sets such as from RNA-Seq and ChIP-Seq.", "biocViews": [ "ChIPSeq", "Clustering", "DNAMethylation", "DataImport", "GeneExpression", "MethylSeq", "Microarray", "MultipleComparison", "RNASeq", "Sequencing", "Software", "Transcription", "Visualization" ], "Author": "Julius Muller", "Maintainer": "Julius Muller ", "URL": "http://bioconductor.org/packages/release/bioc/html/TransView.html", "source.ver": "src/contrib/TransView_1.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/TransView_1.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/TransView_1.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/TransView_1.18.0.tgz", "vignettes": [ "vignettes/TransView/inst/doc/TransView.pdf" ], "vignetteTitles": [ "An introduction to TransView" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/TransView/inst/doc/TransView.R" ] }, "traseR": { "Package": "traseR", "Version": "1.4.0", "Depends": [ "R (>= 3.2.0)", "GenomicRanges", "IRanges", "BSgenome.Hsapiens.UCSC.hg19" ], "Suggests": [ "BiocStyle", "RUnit", "BiocGenerics" ], "License": "GPL", "MD5sum": "5e1eb5dd843b78b16908b8e8b80fc06f", "NeedsCompilation": "no", "Title": "GWAS trait-associated SNP enrichment analyses in genomic intervals", "Description": "traseR performs GWAS trait-associated SNP enrichment analyses in genomic intervals using different hypothesis testing approaches, also provides various functionalities to explore and visualize the results.", "biocViews": [ "Alignment", "Coverage", "DataImport", "Genetics", "QualityControl", "Sequencing", "Software" ], "Author": "Li Chen, Zhaohui S.Qin", "Maintainer": "li chen", "source.ver": "src/contrib/traseR_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/traseR_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/traseR_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/traseR_1.4.0.tgz", "vignettes": [ "vignettes/traseR/inst/doc/traseR.pdf" ], "vignetteTitles": [ "Perform GWAS trait-associated SNP enrichment analyses in genomic intervals" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/traseR/inst/doc/traseR.R" ] }, "triform": { "Package": "triform", "Version": "1.16.0", "Depends": [ "R (>= 2.11.0)", "IRanges", "yaml" ], "Imports": [ "BiocGenerics", "IRanges (>= 2.5.27)", "yaml" ], "Suggests": [ "RUnit" ], "License": "GPL-2", "MD5sum": "f2f95f438028c074d048f095cb09e402", "NeedsCompilation": "no", "Title": "Triform finds enriched regions (peaks) in transcription factor ChIP-sequencing data", "Description": "The Triform algorithm uses model-free statistics to identify peak-like distributions of TF ChIP sequencing reads, taking advantage of an improved peak definition in combination with known profile characteristics.", "biocViews": [ "ChIPSeq", "Sequencing", "Software" ], "Author": "Karl Kornacker Developer [aut], Tony Handstad Developer [aut, cre]", "Maintainer": "Thomas Carroll ", "source.ver": "src/contrib/triform_1.16.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/triform_1.16.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/triform_1.16.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/triform_1.16.0.tgz", "vignettes": [ "vignettes/triform/inst/doc/triform.pdf" ], "vignetteTitles": [ "Triform users guide" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/triform/inst/doc/triform.R" ] }, "trigger": { "Package": "trigger", "Version": "1.20.0", "Depends": [ "R (>= 2.14.0)", "corpcor", "qtl" ], "Imports": [ "qvalue", "methods", "graphics", "sva" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "218e1fbee2e421fb65e2b652039e0403", "NeedsCompilation": "yes", "Title": "Transcriptional Regulatory Inference from Genetics of Gene ExpRession", "Description": "This R package provides tools for the statistical analysis of integrative genomic data that involve some combination of: genotypes, high-dimensional intermediate traits (e.g., gene expression, protein abundance), and higher-order traits (phenotypes). The package includes functions to: (1) construct global linkage maps between genetic markers and gene expression; (2) analyze multiple-locus linkage (epistasis) for gene expression; (3) quantify the proportion of genome-wide variation explained by each locus and identify eQTL hotspots; (4) estimate pair-wise causal gene regulatory probabilities and construct gene regulatory networks; and (5) identify causal genes for a quantitative trait of interest.", "biocViews": [ "GeneExpression", "GeneticVariability", "Genetics", "Microarray", "SNP", "Software" ], "Author": "Lin S. Chen , Dipen P. Sangurdekar and John D. Storey ", "Maintainer": "John D. Storey ", "source.ver": "src/contrib/trigger_1.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/trigger_1.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/trigger_1.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/trigger_1.20.0.tgz", "vignettes": [ "vignettes/trigger/inst/doc/trigger.pdf" ], "vignetteTitles": [ "Trigger Tutorial" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/trigger/inst/doc/trigger.R" ] }, "trio": { "Package": "trio", "Version": "3.12.0", "Depends": [ "R (>= 3.0.1)" ], "Suggests": [ "survival", "haplo.stats", "mcbiopi", "siggenes", "splines", "LogicReg (>= 1.5.3)", "logicFS (>= 1.28.1)", "KernSmooth", "VariantAnnotation" ], "License": "LGPL-2", "MD5sum": "cf5c1400f4071400fe95ffb39129ac59", "NeedsCompilation": "no", "Title": "Testing of SNPs and SNP Interactions in Case-Parent Trio Studies", "Description": "Testing SNPs and SNP interactions with a genotypic TDT. This package furthermore contains functions for computing pairwise values of LD measures and for identifying LD blocks, as well as functions for setting up matched case pseudo-control genotype data for case-parent trios in order to run trio logic regression, for imputing missing genotypes in trios, for simulating case-parent trios with disease risk dependent on SNP interaction, and for power and sample size calculation in trio data.", "biocViews": [ "GeneticVariability", "Genetics", "Microarray", "SNP", "Software" ], "Author": "Holger Schwender, Qing Li, Philipp Berger, Christoph Neumann, Margaret Taub, Ingo Ruczinski", "Maintainer": "Holger Schwender ", "source.ver": "src/contrib/trio_3.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/trio_3.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/trio_3.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/trio_3.12.0.tgz", "vignettes": [ "vignettes/trio/inst/doc/trio.pdf" ], "vignetteTitles": [ "Trio Logic Regression and genotypic TDT" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/trio/inst/doc/trio.R" ] }, "triplex": { "Package": "triplex", "Version": "1.14.0", "Depends": [ "R (>= 2.15.0)", "S4Vectors (>= 0.5.14)", "IRanges (>= 2.5.27)", "XVector (>= 0.11.6)", "Biostrings (>= 2.39.10)" ], "Imports": [ "methods", "grid", "GenomicRanges" ], "LinkingTo": [ "S4Vectors", "IRanges", "XVector", "Biostrings" ], "Suggests": [ "rgl (>= 0.93.932)", "BSgenome.Celegans.UCSC.ce10", "rtracklayer", "GenomeGraphs" ], "License": "BSD_2_clause + file LICENSE", "Archs": "i386, x64", "MD5sum": "e45e4a372661b45cdebd65ec7240b579", "NeedsCompilation": "yes", "Title": "Search and visualize intramolecular triplex-forming sequences in DNA", "Description": "This package provides functions for identification and visualization of potential intramolecular triplex patterns in DNA sequence. The main functionality is to detect the positions of subsequences capable of folding into an intramolecular triplex (H-DNA) in a much larger sequence. The potential H-DNA (triplexes) should be made of as many cannonical nucleotide triplets as possible. The package includes visualization showing the exact base-pairing in 1D, 2D or 3D.", "biocViews": [ "GeneRegulation", "SequenceMatching", "Software" ], "Author": "Jiri Hon, Matej Lexa, Tomas Martinek and Kamil Rajdl with contributions from Daniel Kopecek", "Maintainer": "Jiri Hon ", "URL": "http://www.fi.muni.cz/~lexa/triplex/", "source.ver": "src/contrib/triplex_1.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/triplex_1.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/triplex_1.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/triplex_1.14.0.tgz", "vignettes": [ "vignettes/triplex/inst/doc/triplex.pdf" ], "vignetteTitles": [ "Triplex User Guide" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/triplex/inst/doc/triplex.R" ] }, "TRONCO": { "Package": "TRONCO", "Version": "2.6.1", "Depends": [ "R (>= 3.3)" ], "Imports": [ "bnlearn", "Rgraphviz", "gtools", "parallel", "foreach", "doParallel", "iterators", "RColorBrewer", "circlize", "cgdsr", "igraph", "grid", "gridExtra", "xtable", "gtable", "scales", "R.matlab", "gRapHD", "grDevices", "graphics", "stats", "utils" ], "Suggests": [ "BiocGenerics", "BiocStyle", "testthat", "knitr" ], "License": "file LICENSE", "MD5sum": "5e442d1a7700b49c8feadee1681d67b0", "NeedsCompilation": "no", "Title": "TRONCO, an R package for TRanslational ONCOlogy", "Description": "The TRONCO (TRanslational ONCOlogy) R package collects algorithms to infer progression models via the approach of Suppes-Bayes Causal Network, both from an ensemble of tumors (cross-sectional samples) and within an individual patient (multi-region or single-cell samples). The package provides parallel implementation of algorithms that process binary matrices where each row represents a tumor sample and each column a single-nucleotide or a structural variant driving the progression; a 0/1 value models the absence/presence of that alteration in the sample. The tool can import data from plain, MAF or GISTIC format files, and can fetch it from the cBioPortal for cancer genomics. Functions for data manipulation and visualization are provided, as well as functions to import/export such data to other bioinformatics tools for, e.g, clustering or detection of mutually exclusive alterations. Inferred models can be visualized and tested for their confidence via bootstrap and cross-validation. TRONCO is used for the implementation of the Pipeline for Cancer Inference.", "biocViews": [ "Bayesian", "BiomedicalInformatics", "Clustering", "DataImport", "GraphAndNetwork", "Network", "NetworkInference", "Software", "SomaticMutation" ], "Author": "Marco Antoniotti [ctb], Giulio Caravagna [aut, cre], Luca De Sano [aut], Alex Graudenzi [aut], Giancarlo Mauri [ctb], Bud Mishra [ctb], Daniele Ramazzotti [aut]", "Maintainer": "BIMIB Group ", "URL": "https://sites.google.com/site/troncopackage/", "VignetteBuilder": "knitr", "BugReports": "https://github.com/BIMIB-DISCo/TRONCO", "source.ver": "src/contrib/TRONCO_2.6.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/TRONCO_2.6.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/TRONCO_2.6.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/TRONCO_2.6.1.tgz", "vignettes": [ "vignettes/TRONCO/inst/doc/vignette.pdf" ], "vignetteTitles": [ "An R Package for TRanslational ONCOlogy" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/TRONCO/inst/doc/vignette.R" ] }, "TSCAN": { "Package": "TSCAN", "Version": "1.12.0", "Depends": [ "R(>= 2.10.0)" ], "Imports": [ "ggplot2", "shiny", "plyr", "grid", "fastICA", "igraph", "combinat", "mgcv", "mclust", "gplots" ], "Suggests": [ "knitr" ], "License": "GPL(>=2)", "MD5sum": "db4b187af3d7bfb1821ff14c5cef1aab", "NeedsCompilation": "no", "Title": "TSCAN: Tools for Single-Cell ANalysis", "Description": "TSCAN enables users to easily construct and tune pseudotemporal cell ordering as well as analyzing differentially expressed genes. TSCAN comes with a user-friendly GUI written in shiny. More features will come in the future.", "biocViews": [ "GUI", "GeneExpression", "Software", "Visualization" ], "Author": "Zhicheng Ji, Hongkai Ji", "Maintainer": "Zhicheng Ji ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/TSCAN_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/TSCAN_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/TSCAN_1.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/TSCAN_1.12.0.tgz", "vignettes": [ "vignettes/TSCAN/inst/doc/TSCAN.pdf" ], "vignetteTitles": [ "TSCAN: Tools for Single-Cell ANalysis" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/TSCAN/inst/doc/TSCAN.R" ] }, "tspair": { "Package": "tspair", "Version": "1.32.0", "Depends": [ "R (>= 2.10)", "Biobase (>= 2.4.0)" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "ba932fdbaac798a4eaef434cd499fc9a", "NeedsCompilation": "yes", "Title": "Top Scoring Pairs for Microarray Classification", "Description": "These functions calculate the pair of genes that show the maximum difference in ranking between two user specified groups. This \"top scoring pair\" maximizes the average of sensitivity and specificity over all rank based classifiers using a pair of genes in the data set. The advantage of classifying samples based on only the relative rank of a pair of genes is (a) the classifiers are much simpler and often more interpretable than more complicated classification schemes and (b) if arrays can be classified using only a pair of genes, PCR based tests could be used for classification of samples. See the references for the tspcalc() function for references regarding TSP classifiers.", "biocViews": [ "Microarray", "Software" ], "Author": "Jeffrey T. Leek ", "Maintainer": "Jeffrey T. Leek ", "source.ver": "src/contrib/tspair_1.32.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/tspair_1.32.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/tspair_1.32.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/tspair_1.32.0.tgz", "vignettes": [ "vignettes/tspair/inst/doc/tsp.pdf" ], "vignetteTitles": [ "tspTutorial" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/tspair/inst/doc/tsp.R" ], "dependsOnMe": [ "stepwiseCM" ] }, "TSSi": { "Package": "TSSi", "Version": "1.20.0", "Depends": [ "R (>= 2.13.2)" ], "Imports": [ "methods", "BiocGenerics (>= 0.3.2)", "S4Vectors", "Hmisc", "minqa", "stats", "Biobase (>= 0.3.2)", "plyr", "IRanges" ], "Suggests": [ "rtracklayer" ], "Enhances": [ "parallel" ], "License": "GPL-3", "Archs": "i386, x64", "MD5sum": "f865aa1b2c88714ae171914cc043f158", "NeedsCompilation": "yes", "Title": "Transcription Start Site Identification", "Description": "Identify and normalize transcription start sites in high-throughput sequencing data.", "biocViews": [ "Genetics", "Preprocessing", "RNASeq", "Sequencing", "Software" ], "Author": "Julian Gehring, Clemens Kreutz", "Maintainer": "Julian Gehring ", "source.ver": "src/contrib/TSSi_1.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/TSSi_1.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/TSSi_1.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/TSSi_1.20.0.tgz", "vignettes": [ "vignettes/TSSi/inst/doc/TSSi.pdf" ], "vignetteTitles": [ "Introduction to the TSSi package: Identification of Transcription Start Sites" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/TSSi/inst/doc/TSSi.R" ] }, "TurboNorm": { "Package": "TurboNorm", "Version": "1.22.0", "Depends": [ "R (>= 2.12.0)", "convert", "limma (>= 1.7.0)", "marray" ], "Imports": [ "stats", "grDevices", "affy", "lattice" ], "Suggests": [ "BiocStyle", "affydata" ], "License": "LGPL", "Archs": "i386, x64", "MD5sum": "529d5d9f70cc8a90fb1a28d60e2c5f5e", "NeedsCompilation": "yes", "Title": "A fast scatterplot smoother suitable for microarray normalization", "Description": "A fast scatterplot smoother based on B-splines with second-order difference penalty. Functions for microarray normalization of single-colour data i.e. Affymetrix/Illumina and two-colour data supplied as marray MarrayRaw-objects or limma RGList-objects are available.", "biocViews": [ "CpGIsland", "DNAMethylation", "MethylationArray", "Microarray", "Normalization", "OneChannel", "Preprocessing", "Software", "TwoChannel" ], "Author": "Maarten van Iterson and Chantal van Leeuwen", "Maintainer": "Maarten van Iterson ", "URL": "http://www.humgen.nl/MicroarrayAnalysisGroup.html", "source.ver": "src/contrib/TurboNorm_1.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/TurboNorm_1.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/TurboNorm_1.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/TurboNorm_1.22.0.tgz", "vignettes": [ "vignettes/TurboNorm/inst/doc/turbonorm.pdf" ], "vignetteTitles": [ "TurboNorm Overview" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/TurboNorm/inst/doc/turbonorm.R" ] }, "TVTB": { "Package": "TVTB", "Version": "1.0.2", "Depends": [ "R (>= 3.3)", "methods", "utils", "stats" ], "Imports": [ "BiocGenerics (>= 0.19.1)", "BiocParallel", "Biostrings", "ensembldb", "ensemblVEP", "GenomeInfoDb", "GenomicRanges", "ggplot2", "IRanges (>= 2.7.1)", "reshape2", "Rsamtools", "S4Vectors (>= 0.11.11)", "SummarizedExperiment", "VariantAnnotation (>= 1.19.9)" ], "Suggests": [ "EnsDb.Hsapiens.v75 (>= 0.99.7)", "shiny (>= 0.13.2.9005)", "DT (>= 0.1.67)", "rtracklayer", "BiocStyle (>= 2.1.23)", "knitr (>= 1.12)", "rmarkdown", "testthat", "covr" ], "License": "Artistic-2.0", "MD5sum": "8f0e2e96a499c0a2b06ee44ba2f1380a", "NeedsCompilation": "no", "Title": "TVTB: The VCF Tool Box", "Description": "The package provides S4 classes and methods to filter, summarise and visualise genetic variation data stored in VCF files. In particular, the package extends the FilterRules class (S4Vectors package) to define news classes of filter rules applicable to the various slots of VCF objects. Functionalities are integrated and demonstrated in a Shiny web-application, the Shiny Variant Explorer (tSVE).", "biocViews": [ "Alignment", "Coverage", "DNASeq", "DataImport", "DataRepresentation", "GUI", "GeneticVariability", "Genetics", "GenomicVariation", "MultipleComparison", "SequenceMatching", "Sequencing", "Software", "VariantAnnotation", "Visualization", "WholeGenome" ], "Author": "Kevin Rue-Albrecht [aut, cre]", "Maintainer": "Kevin Rue-Albrecht ", "URL": "https://github.com/kevinrue/TVTB", "VignetteBuilder": "knitr", "BugReports": "https://github.com/kevinrue/TVTB/issues", "source.ver": "src/contrib/TVTB_1.0.2.tar.gz", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/TVTB_1.0.2.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/TVTB/inst/doc/Introduction.R", "vignettes/TVTB/inst/doc/tSVE.R", "vignettes/TVTB/inst/doc/VcfFilterRules.R" ], "htmlDocs": [ "vignettes/TVTB/inst/doc/Introduction.html", "vignettes/TVTB/inst/doc/tSVE.html", "vignettes/TVTB/inst/doc/VcfFilterRules.html" ], "htmlTitles": [ "Introduction to TVTB", "The Shiny Variant Explorer", "VCF filter rules" ] }, "tweeDEseq": { "Package": "tweeDEseq", "Version": "1.20.0", "Depends": [ "R (>= 2.12.0)" ], "Imports": [ "MASS", "limma", "edgeR", "parallel", "cqn" ], "Suggests": [ "tweeDEseqCountData", "xtable" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "dea8c9478eb7241962a438913be10b5c", "NeedsCompilation": "yes", "Title": "RNA-seq data analysis using the Poisson-Tweedie family of distributions", "Description": "Differential expression analysis of RNA-seq using the Poisson-Tweedie family of distributions.", "biocViews": [ "DifferentialExpression", "RNASeq", "Sequencing", "Software", "StatisticalMethod" ], "Author": "Juan R Gonzalez and Mikel Esnaola (with contributions from Robert Castelo )", "Maintainer": "Juan R Gonzalez ", "URL": "http://www.creal.cat/jrgonzalez/software.htm", "source.ver": "src/contrib/tweeDEseq_1.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/tweeDEseq_1.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/tweeDEseq_1.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/tweeDEseq_1.20.0.tgz", "vignettes": [ "vignettes/tweeDEseq/inst/doc/tweeDEseq.pdf" ], "vignetteTitles": [ "tweeDEseq: analysis of RNA-seq data using the Poisson-Tweedie family of distributions" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/tweeDEseq/inst/doc/tweeDEseq.R" ] }, "twilight": { "Package": "twilight", "Version": "1.50.0", "Depends": [ "R (>= 2.10)", "splines (>= 2.2.0)", "stats (>= 2.2.0)", "Biobase(>= 1.12.0)" ], "Imports": [ "Biobase", "graphics", "grDevices", "stats" ], "Suggests": [ "golubEsets (>= 1.4.2)", "vsn (>= 1.7.2)" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "2d2439e3b473289434eff5ffc8ee8301", "NeedsCompilation": "yes", "Title": "Estimation of local false discovery rate", "Description": "In a typical microarray setting with gene expression data observed under two conditions, the local false discovery rate describes the probability that a gene is not differentially expressed between the two conditions given its corrresponding observed score or p-value level. The resulting curve of p-values versus local false discovery rate offers an insight into the twilight zone between clear differential and clear non-differential gene expression. Package 'twilight' contains two main functions: Function twilight.pval performs a two-condition test on differences in means for a given input matrix or expression set and computes permutation based p-values. Function twilight performs a stochastic downhill search to estimate local false discovery rates and effect size distributions. The package further provides means to filter for permutations that describe the null distribution correctly. Using filtered permutations, the influence of hidden confounders could be diminished.", "biocViews": [ "DifferentialExpression", "Microarray", "MultipleComparison", "Software" ], "Author": "Stefanie Scheid ", "Maintainer": "Stefanie Scheid ", "URL": "http://compdiag.molgen.mpg.de/software/twilight.shtml", "source.ver": "src/contrib/twilight_1.50.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/twilight_1.50.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/twilight_1.50.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/twilight_1.50.0.tgz", "vignettes": [ "vignettes/twilight/inst/doc/tr_2004_01.pdf" ], "vignetteTitles": [ "Estimation of Local False Discovery Rates" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/twilight/inst/doc/tr_2004_01.R" ], "dependsOnMe": [ "OrderedList" ], "importsMe": [ "OrderedList" ] }, "tximport": { "Package": "tximport", "Version": "1.2.0", "Imports": [ "utils" ], "Suggests": [ "knitr", "testthat", "tximportData", "TxDb.Hsapiens.UCSC.hg19.knownGene", "readr (>= 0.2.2)", "limma", "edgeR", "DESeq2 (>= 1.11.6)" ], "License": "GPL (>=2)", "MD5sum": "5bb24b273adce6467083b4078337531d", "NeedsCompilation": "no", "Title": "Import and summarize transcript-level estimates for gene-level analysis", "Description": "Imports transcript-level abundance, estimated counts and transcript lengths, and summarizes into matrices for use with downstream gene-level analysis packages. Average transcript length, weighted by sample-specific transcript abundance estimates, is provided as a matrix which can be used as an offset for different expression of gene-level counts.", "biocViews": [ "DataImport", "GeneExpression", "RNASeq", "Software", "Transcription" ], "Author": "Michael Love, Charlotte Soneson, Mark Robinson", "Maintainer": "Michael Love ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/tximport_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/tximport_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/tximport_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/tximport_1.2.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/tximport/inst/doc/tximport.R" ], "htmlDocs": [ "vignettes/tximport/inst/doc/tximport.html" ], "htmlTitles": [ "tximport" ], "importsMe": [ "scater" ], "suggestsMe": [ "DESeq2", "variancePartition" ] }, "TypeInfo": { "Package": "TypeInfo", "Version": "1.40.0", "Depends": [ "methods" ], "Suggests": [ "Biobase" ], "License": "BSD", "MD5sum": "b2f4ca9b00d635dd2521d07756e1ffd0", "NeedsCompilation": "no", "Title": "Optional Type Specification Prototype", "Description": "A prototype for a mechanism for specifying the types of parameters and the return value for an R function. This is meta-information that can be used to generate stubs for servers and various interfaces to these functions. Additionally, the arguments in a call to a typed function can be validated using the type specifications. We allow types to be specified as either i) by class name using either inheritance - is(x, className), or strict instance of - class(x) %in% className, or ii) a dynamic test given as an R expression which is evaluated at run-time. More precise information and interesting tests can be done via ii), but it is harder to use this information as meta-data as it requires more effort to interpret it and it is of course run-time information. It is typically more meaningful.", "biocViews": [ "Infrastructure", "Software" ], "Author": "Duncan Temple Lang Robert Gentleman ()", "Maintainer": "Duncan Temple Lang ", "source.ver": "src/contrib/TypeInfo_1.40.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/TypeInfo_1.40.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/TypeInfo_1.40.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/TypeInfo_1.40.0.tgz", "vignettes": [ "vignettes/TypeInfo/inst/doc/TypeInfoNews.pdf" ], "vignetteTitles": [ "TypeInfo R News" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/TypeInfo/inst/doc/TypeInfoNews.R" ] }, "UNDO": { "Package": "UNDO", "Version": "1.16.0", "Depends": [ "R (>= 2.15.2)", "methods", "BiocGenerics", "Biobase" ], "Imports": [ "MASS", "boot", "nnls", "stats", "utils" ], "License": "GPL-2", "MD5sum": "0f5423ed0b68fa6df1b7f03b3dbd9de5", "NeedsCompilation": "no", "Title": "Unsupervised Deconvolution of Tumor-Stromal Mixed Expressions", "Description": "UNDO is an R package for unsupervised deconvolution of tumor and stromal mixed expression data. It detects marker genes and deconvolutes the mixing expression data without any prior knowledge.", "biocViews": [ "Software" ], "Author": "Niya Wang ", "Maintainer": "Niya Wang ", "source.ver": "src/contrib/UNDO_1.16.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/UNDO_1.16.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/UNDO_1.16.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/UNDO_1.16.0.tgz", "vignettes": [ "vignettes/UNDO/inst/doc/UNDO-vignette.pdf" ], "vignetteTitles": [ "UNDO Usage" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/UNDO/inst/doc/UNDO-vignette.R" ] }, "unifiedWMWqPCR": { "Package": "unifiedWMWqPCR", "Version": "1.10.0", "Depends": [ "methods" ], "Imports": [ "BiocGenerics", "stats", "graphics", "HTqPCR" ], "License": "GPL (>=2)", "MD5sum": "7cb36ef6deecc85cbe66d2de3c2d5fee", "NeedsCompilation": "no", "Title": "Unified Wilcoxon-Mann Whitney Test for testing differential expression in qPCR data", "Description": "This packages implements the unified Wilcoxon-Mann-Whitney Test for qPCR data. This modified test allows for testing differential expression in qPCR data.", "biocViews": [ "DifferentialExpression", "GeneExpression", "MicrotitrePlateAssay", "MultipleComparison", "QualityControl", "Software", "Visualization", "qPCR" ], "Author": "Jan R. De Neve & Joris Meys", "Maintainer": "Joris Meys ", "source.ver": "src/contrib/unifiedWMWqPCR_1.10.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/unifiedWMWqPCR_1.10.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/unifiedWMWqPCR_1.10.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/unifiedWMWqPCR_1.10.0.tgz", "vignettes": [ "vignettes/unifiedWMWqPCR/inst/doc/unifiedWMWqPCR.pdf" ], "vignetteTitles": [ "Using unifiedWMWqPCR" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/unifiedWMWqPCR/inst/doc/unifiedWMWqPCR.R" ] }, "UniProt.ws": { "Package": "UniProt.ws", "Version": "2.14.0", "Depends": [ "methods", "utils", "RSQLite", "RCurl", "BiocGenerics (>= 0.13.8)" ], "Imports": [ "AnnotationDbi" ], "Suggests": [ "RUnit" ], "License": "Artistic License 2.0", "MD5sum": "01d63e23eff86d35cdd507136aa5ff44", "NeedsCompilation": "no", "Title": "R Interface to UniProt Web Services", "Description": "A collection of functions for retrieving, processing and repackaging the UniProt web services.", "biocViews": [ "Annotation", "BioCarta", "GO", "Infrastructure", "KEGG", "Software" ], "Author": "Marc Carlson", "Maintainer": "Bioconductor Package Maintainer ", "source.ver": "src/contrib/UniProt.ws_2.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/UniProt.ws_2.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/UniProt.ws_2.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/UniProt.ws_2.14.0.tgz", "vignettes": [ "vignettes/UniProt.ws/inst/doc/UniProt.ws.pdf" ], "vignetteTitles": [ "UniProt.ws: A package for retrieving data from the UniProt web service" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/UniProt.ws/inst/doc/UniProt.ws.R" ], "suggestsMe": [ "cleaver", "dagLogo" ] }, "Uniquorn": { "Package": "Uniquorn", "Version": "1.2.0", "Depends": [ "R (>= 3.3)" ], "Imports": [ "DBI", "stringr", "RSQLite", "R.utils", "WriteXLS", "stats" ], "Suggests": [ "testthat", "knitr", "rmarkdown", "BiocGenerics", "RUnit" ], "License": "Artistic-2.0", "MD5sum": "512308e87022aec9bbde6a8ec9f8fa3c", "NeedsCompilation": "no", "Title": "Identification of cancer cell lines based on their weighted mutational/ variational fingerprint", "Description": "This packages enables users to identify cancer cell lines. Cancer cell line misidentification and cross-contamination reprents a significant challenge for cancer researchers. The identification is vital and in the frame of this package based on the locations/ loci of somatic and germline mutations/ variations. The input format is vcf/ vcf.gz and the files have to contain a single cancer cell line sample (i.e. a single member/genotype/gt column in the vcf file). The implemented method is optimized for the Next-generation whole exome and whole genome DNA-sequencing technology. RNA-seq data is very likely to work as well but hasn't been rigiously tested yet. Panel-seq will require manual adjustment of thresholds", "biocViews": [ "ExomeSeq", "Software", "StatisticalMethod", "WholeGenome" ], "Author": "Raik Otto", "Maintainer": "'Raik Otto' ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/Uniquorn_1.2.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Uniquorn_1.2.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Uniquorn_1.2.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Uniquorn_1.2.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Uniquorn/inst/doc/Uniquorn.R" ], "htmlDocs": [ "vignettes/Uniquorn/inst/doc/Uniquorn.html" ], "htmlTitles": [ "Vignette Title" ] }, "uSORT": { "Package": "uSORT", "Version": "1.0.0", "Depends": [ "R (>= 3.3.0)", "tcltk" ], "Imports": [ "igraph", "Matrix", "RANN", "RSpectra", "VGAM", "gplots", "parallel", "plyr", "methods", "cluster", "Biobase", "fpc", "BiocGenerics", "monocle", "grDevices", "graphics", "stats", "utils" ], "Suggests": [ "knitr", "RUnit", "testthat", "ggplot2" ], "License": "Artistic-2.0", "MD5sum": "22f609851d44d4429a4b22c31bb9bb59", "NeedsCompilation": "no", "Title": "uSORT: A self-refining ordering pipeline for gene selection", "Description": "This package is designed to uncover the intrinsic cell progression path from single-cell RNA-seq data. It incorporates data pre-processing, preliminary PCA gene selection, preliminary cell ordering, feature selection, refined cell ordering, and post-analysis interpretation and visualization.", "biocViews": [ "CellBiology", "DNASeq", "GUI", "RNASeq", "Software" ], "Author": "Mai Chan Lau, Hao Chen, Jinmiao Chen", "Maintainer": "Hao Chen ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/uSORT_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/uSORT_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/uSORT_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/uSORT_1.0.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/uSORT/inst/doc/uSORT_quick_start.R" ], "htmlDocs": [ "vignettes/uSORT/inst/doc/uSORT_quick_start.html" ], "htmlTitles": [ "Quick Start" ] }, "VanillaICE": { "Package": "VanillaICE", "Version": "1.36.0", "Depends": [ "R (>= 3.0.0)", "BiocGenerics (>= 0.13.6)", "GenomicRanges (>= 1.19.47)", "SummarizedExperiment (>= 0.2.0)" ], "Imports": [ "Biobase", "S4Vectors (>= 0.9.25)", "IRanges (>= 1.14.0)", "oligoClasses (>= 1.31.1)", "foreach", "matrixStats", "data.table", "grid", "lattice", "methods", "GenomeInfoDb", "crlmm", "tools", "stats", "utils", "BSgenome.Hsapiens.UCSC.hg18" ], "Suggests": [ "RUnit", "SNPchip", "human610quadv1bCrlmm", "ArrayTV" ], "Enhances": [ "doMC", "doMPI", "doSNOW", "doParallel", "doRedis" ], "License": "LGPL-2", "Archs": "i386, x64", "MD5sum": "963384f405316bf4d66f5ef8504e71bc", "NeedsCompilation": "yes", "Title": "A Hidden Markov Model for high throughput genotyping arrays", "Description": "Hidden Markov Models for characterizing chromosomal alterations in high throughput SNP arrays.", "biocViews": [ "CopyNumberVariation", "Software" ], "Author": "Robert Scharpf , Kevin Scharpf, and Ingo Ruczinski ", "Maintainer": "Robert Scharpf ", "source.ver": "src/contrib/VanillaICE_1.36.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/VanillaICE_1.36.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/VanillaICE_1.36.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/VanillaICE_1.36.0.tgz", "vignettes": [ "vignettes/VanillaICE/inst/doc/crlmmDownstream.pdf", "vignettes/VanillaICE/inst/doc/VanillaICE.pdf" ], "vignetteTitles": [ "crlmmDownstream", "VanillaICE Vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/VanillaICE/inst/doc/crlmmDownstream.R", "vignettes/VanillaICE/inst/doc/VanillaICE.R" ], "dependsOnMe": [ "MinimumDistance" ], "suggestsMe": [ "CNPBayes", "oligoClasses" ] }, "variancePartition": { "Package": "variancePartition", "Version": "1.4.2", "Depends": [ "ggplot2", "foreach", "Biobase", "methods" ], "Imports": [ "MASS", "pbkrtest (>= 0.4-4)", "iterators", "splines", "colorRamps", "gplots", "reshape2", "lme4 (>= 1.1-10)", "doParallel", "limma", "grDevices", "graphics", "utils", "stats" ], "Suggests": [ "edgeR", "dendextend", "tximport", "tximportData", "ballgown", "DESeq2", "readr", "knitr", "BiocStyle" ], "License": "GPL (>= 2)", "MD5sum": "80da83c388260720cb4fd43064802669", "NeedsCompilation": "no", "Title": "Quantify and interpret divers of variation in multilevel gene expression experiments", "Description": "Quantify and interpret multiple sources of biological and technical variation in gene expression experiments. Uses linear mixed model to quantify variation in gene expression attributable to individual, tissue, time point, or technical variables.", "biocViews": [ "GeneExpression", "RNASeq", "Regression", "Software" ], "Author": "Gabriel E. Hoffman", "Maintainer": "Gabriel E. Hoffman ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/variancePartition_1.4.2.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/variancePartition_1.4.2.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/variancePartition_1.4.2.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/variancePartition_1.4.2.tgz", "vignettes": [ "vignettes/variancePartition/inst/doc/additional_visualization.pdf", "vignettes/variancePartition/inst/doc/variancePartition.pdf" ], "vignetteTitles": [ "2) Additional visualizations", "1) Tutorial on using variancePartition" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/variancePartition/inst/doc/additional_visualization.R", "vignettes/variancePartition/inst/doc/variancePartition.R" ] }, "VariantAnnotation": { "Package": "VariantAnnotation", "Version": "1.20.3", "Depends": [ "R (>= 2.8.0)", "methods", "BiocGenerics (>= 0.15.3)", "GenomeInfoDb (>= 1.7.1)", "GenomicRanges (>= 1.19.47)", "SummarizedExperiment (>= 0.3.1)", "Rsamtools (>= 1.23.10)" ], "Imports": [ "utils", "DBI", "zlibbioc", "Biobase", "S4Vectors (>= 0.9.47)", "IRanges (>= 2.3.25)", "XVector (>= 0.5.6)", "Biostrings (>= 2.33.5)", "AnnotationDbi (>= 1.27.9)", "BSgenome (>= 1.37.6)", "rtracklayer (>= 1.25.16)", "GenomicFeatures (>= 1.19.17)" ], "LinkingTo": [ "S4Vectors", "IRanges", "XVector", "Biostrings", "Rsamtools" ], "Suggests": [ "RUnit", "AnnotationHub", "BSgenome.Hsapiens.UCSC.hg19", "TxDb.Hsapiens.UCSC.hg19.knownGene", "SNPlocs.Hsapiens.dbSNP.20110815", "SNPlocs.Hsapiens.dbSNP.20101109", "SIFT.Hsapiens.dbSNP132", "SIFT.Hsapiens.dbSNP137", "PolyPhen.Hsapiens.dbSNP131", "snpStats", "ggplot2", "BiocStyle" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "a16f2e9d24eb4c19607c2e5fcd1d5ea3", "NeedsCompilation": "yes", "Title": "Annotation of Genetic Variants", "Description": "Annotate variants, compute amino acid coding changes, predict coding outcomes.", "biocViews": [ "Annotation", "DataImport", "Genetics", "SNP", "Sequencing", "Software", "VariantAnnotation" ], "Author": "Valerie Obenchain [aut, cre], Martin Morgan [aut], Michael Lawrence [aut], Stephanie Gogarten [ctb]", "Maintainer": "Valerie Obenchain ", "Video": "https://www.youtube.com/watch?v=Ro0lHQ_J--I&list=UUqaMSQd_h-2EDGsU6WDiX0Q", "source.ver": "src/contrib/VariantAnnotation_1.20.3.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/VariantAnnotation_1.20.3.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/VariantAnnotation_1.20.3.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/VariantAnnotation_1.20.3.tgz", "vignettes": [ "vignettes/VariantAnnotation/inst/doc/filterVcf.pdf", "vignettes/VariantAnnotation/inst/doc/VariantAnnotation.pdf" ], "vignetteTitles": [ "filterVcf Overview", "Introduction to VariantAnnotation" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/VariantAnnotation/inst/doc/filterVcf.R", "vignettes/VariantAnnotation/inst/doc/VariantAnnotation.R" ], "dependsOnMe": [ "ampliQueso", "cgdv17", "CNVrd2", "deepSNV", "DOQTL", "ensemblVEP", "genotypeeval", "GoogleGenomics", "HelloRanges", "HTSeqGenie", "myvariant", "PolyPhen.Hsapiens.dbSNP131", "PureCN", "R453Plus1Toolbox", "RareVariantVis", "Rariant", "SIFT.Hsapiens.dbSNP132", "SIFT.Hsapiens.dbSNP137", "SomaticSignatures", "VariantFiltering", "VariantTools" ], "importsMe": [ "AllelicImbalance", "BadRegionFinder", "BBCAnalyzer", "biovizBase", "COSMIC.67", "customProDB", "FunciSNP", "genbankr", "GenomicFiles", "ggbio", "GGtools", "gmapR", "gQTLstats", "gwascat", "MADSEQ", "MafDb.ESP6500SI.V2.SSA137", "maftools", "methyAnalysis", "motifbreakR", "MutationalPatterns", "PGA", "SeqArray", "SeqVarTools", "signeR", "SNPhood", "systemPipeR", "TVTB", "YAPSA" ], "suggestsMe": [ "AnnotationHub", "AshkenazimSonChr21", "CrispRVariants", "GenomicRanges", "GeuvadisTranscriptExpr", "GMRP", "GWASTools", "podkat", "trackViewer", "trio", "vtpnet" ] }, "VariantFiltering": { "Package": "VariantFiltering", "Version": "1.10.1", "Depends": [ "R (>= 3.0.0)", "methods", "BiocGenerics (>= 0.13.8)", "VariantAnnotation (>= 1.13.29)" ], "Imports": [ "utils", "DBI", "RSQLite (>= 1.0.0)", "Biobase", "S4Vectors (>= 0.9.25)", "IRanges (>= 2.3.23)", "RBGL", "graph", "AnnotationDbi", "BiocParallel", "Biostrings (>= 2.33.11)", "GenomeInfoDb (>= 1.3.6)", "GenomicRanges (>= 1.19.13)", "SummarizedExperiment", "GenomicFeatures", "Rsamtools (>= 1.17.8)", "BSgenome", "Gviz", "shiny" ], "LinkingTo": [ "S4Vectors", "IRanges", "XVector", "Biostrings" ], "Suggests": [ "RUnit", "BiocStyle", "org.Hs.eg.db", "BSgenome.Hsapiens.1000genomes.hs37d5", "TxDb.Hsapiens.UCSC.hg19.knownGene", "SNPlocs.Hsapiens.dbSNP144.GRCh37", "MafDb.1Kgenomes.phase3.hs37d5", "MafDb.ExAC.r0.3.1.snvs.hs37d5", "phastCons100way.UCSC.hg19", "PolyPhen.Hsapiens.dbSNP131", "SIFT.Hsapiens.dbSNP137" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "cdb51d3f8446ba99742d8ba68c19b6fd", "NeedsCompilation": "yes", "Title": "Filtering of coding and non-coding genetic variants", "Description": "Filter genetic variants using different criteria such as inheritance model, amino acid change consequence, minor allele frequencies across human populations, splice site strength, conservation, etc.", "biocViews": [ "Annotation", "Genetics", "HighThroughputSequencing", "Homo_sapiens", "SNP", "Sequencing", "Software" ], "Author": "Robert Castelo [aut, cre], Dei Martinez Elurbe [ctb], Pau Puigdevall [ctb]", "Maintainer": "Robert Castelo ", "URL": "https://github.com/rcastelo/VariantFiltering", "BugReports": "https://github.com/rcastelo/VariantFiltering/issues", "source.ver": "src/contrib/VariantFiltering_1.10.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/VariantFiltering_1.10.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/VariantFiltering_1.10.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/VariantFiltering_1.10.1.tgz", "vignettes": [ "vignettes/VariantFiltering/inst/doc/usingVariantFiltering.pdf" ], "vignetteTitles": [ "VariantFiltering: filter coding and non-coding genetic variants" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/VariantFiltering/inst/doc/usingVariantFiltering.R" ], "dependsOnMe": [ "fitCons.UCSC.hg19", "MafDb.1Kgenomes.phase1.hs37d5", "MafDb.1Kgenomes.phase3.hs37d5", "MafDb.ESP6500SI.V2.SSA137", "MafDb.ESP6500SI.V2.SSA137.GRCh38", "MafDb.ESP6500SI.V2.SSA137.hs37d5", "MafDb.ExAC.r0.3.1.nonTCGA.snvs.hs37d5", "MafDb.ExAC.r0.3.1.snvs.hs37d5", "phastCons100way.UCSC.hg19", "phastCons100way.UCSC.hg38", "phastCons7way.UCSC.hg38" ] }, "VariantTools": { "Package": "VariantTools", "Version": "1.16.0", "Depends": [ "S4Vectors (>= 0.9.25)", "IRanges (>= 1.99.2)", "GenomicRanges (>= 1.17.7)", "VariantAnnotation (>= 1.11.16)", "methods" ], "Imports": [ "Rsamtools (>= 1.17.6)", "BiocGenerics", "Biostrings", "parallel", "gmapR (>= 1.13.4)", "GenomicFeatures (>= 1.17.13)", "Matrix", "rtracklayer (>= 1.25.3)", "BiocParallel", "GenomeInfoDb", "BSgenome", "Biobase" ], "Suggests": [ "RUnit", "LungCancerLines (>= 0.0.6)", "RBGL", "graph" ], "License": "Artistic-2.0", "MD5sum": "fa6f1cbb3d7af0a9a9fec7107b3cbf6a", "NeedsCompilation": "no", "Title": "Tools for Working with Genetic Variants", "Description": "Tools for detecting, filtering, calling, comparing and plotting variants.", "biocViews": [ "GeneticVariability", "Genetics", "Sequencing", "Software" ], "Author": "Michael Lawrence, Jeremiah Degenhardt, Robert Gentleman", "Maintainer": "Michael Lawrence ", "source.ver": "src/contrib/VariantTools_1.16.0.tar.gz", "vignettes": [ "vignettes/VariantTools/inst/doc/VariantTools.pdf" ], "vignetteTitles": [ "Introduction to VariantTools" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/VariantTools/inst/doc/VariantTools.R" ], "importsMe": [ "HTSeqGenie" ] }, "vbmp": { "Package": "vbmp", "Version": "1.42.0", "Depends": [ "R (>= 2.10)" ], "Suggests": [ "Biobase (>= 2.5.5)", "statmod" ], "License": "GPL (>= 2)", "MD5sum": "fc00938ba24342b5e6bcbb7a05c03748", "NeedsCompilation": "no", "Title": "Variational Bayesian Multinomial Probit Regression", "Description": "Variational Bayesian Multinomial Probit Regression with Gaussian Process Priors. It estimates class membership posterior probability employing variational and sparse approximation to the full posterior. This software also incorporates feature weighting by means of Automatic Relevance Determination.", "biocViews": [ "Classification", "Software" ], "Author": "Nicola Lama , Mark Girolami ", "Maintainer": "Nicola Lama ", "URL": "http://bioinformatics.oxfordjournals.org/cgi/content/short/btm535v1", "source.ver": "src/contrib/vbmp_1.42.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/vbmp_1.42.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/vbmp_1.42.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/vbmp_1.42.0.tgz", "vignettes": [ "vignettes/vbmp/inst/doc/vbmp.pdf" ], "vignetteTitles": [ "vbmp Tutorial" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/vbmp/inst/doc/vbmp.R" ] }, "Vega": { "Package": "Vega", "Version": "1.22.0", "Depends": [ "R (>= 2.10)" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "cb494858a2166efc7256f3324c80df16", "NeedsCompilation": "yes", "Title": "An R package for copy number data segmentation", "Description": "Vega (Variational Estimator for Genomic Aberrations) is an algorithm that adapts a very popular variational model (Mumford and Shah) used in image segmentation so that chromosomal aberrant regions can be efficiently detected.", "biocViews": [ "CopyNumberVariation", "Software", "aCGH" ], "Author": "Sandro Morganella", "Maintainer": "Sandro Morganella ", "source.ver": "src/contrib/Vega_1.22.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/Vega_1.22.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/Vega_1.22.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/Vega_1.22.0.tgz", "vignettes": [ "vignettes/Vega/inst/doc/Vega.pdf" ], "vignetteTitles": [ "Vega" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/Vega/inst/doc/Vega.R" ] }, "VegaMC": { "Package": "VegaMC", "Version": "3.12.0", "Depends": [ "R (>= 2.10.0)", "biomaRt", "Biobase" ], "Imports": [ "methods", "genoset" ], "License": "GPL-2", "Archs": "i386, x64", "MD5sum": "021153f00b2207c8f1f934cb9d64c60a", "NeedsCompilation": "yes", "Title": "VegaMC: A Package Implementing a Variational Piecewise Smooth Model for Identification of Driver Chromosomal Imbalances in Cancer", "Description": "This package enables the detection of driver chromosomal imbalances including loss of heterozygosity (LOH) from array comparative genomic hybridization (aCGH) data. VegaMC performs a joint segmentation of a dataset and uses a statistical framework to distinguish between driver and passenger mutation. VegaMC has been implemented so that it can be immediately integrated with the output produced by PennCNV tool. In addition, VegaMC produces in output two web pages that allows a rapid navigation between both the detected regions and the altered genes. In the web page that summarizes the altered genes, the link to the respective Ensembl gene web page is reported.", "biocViews": [ "CopyNumberVariation", "Software", "aCGH" ], "Author": "S. Morganella and M. Ceccarelli", "Maintainer": "Sandro Morganella ", "source.ver": "src/contrib/VegaMC_3.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/VegaMC_3.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/VegaMC_3.12.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/VegaMC_3.12.0.tgz", "vignettes": [ "vignettes/VegaMC/inst/doc/VegaMC.pdf" ], "vignetteTitles": [ "VegaMC" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/VegaMC/inst/doc/VegaMC.R" ] }, "viper": { "Package": "viper", "Version": "1.8.0", "Depends": [ "R (>= 2.14.0)", "Biobase", "methods" ], "Imports": [ "mixtools", "stats", "parallel", "e1071", "KernSmooth" ], "Suggests": [ "bcellViper" ], "License": "file LICENSE", "MD5sum": "741f25830d38ad0cef57ec59a0b564d8", "NeedsCompilation": "no", "Title": "Virtual Inference of Protein-activity by Enriched Regulon analysis", "Description": "Inference of protein activity from gene expression data, including the VIPER and msVIPER algorithms", "biocViews": [ "FunctionalPrediction", "GeneExpression", "GeneRegulation", "NetworkEnrichment", "Software", "SystemsBiology" ], "Author": "Mariano J Alvarez ", "Maintainer": "Mariano J Alvarez ", "source.ver": "src/contrib/viper_1.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/viper_1.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/viper_1.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/viper_1.8.0.tgz", "vignettes": [ "vignettes/viper/inst/doc/viper.pdf" ], "vignetteTitles": [ "Using VIPER" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/viper/inst/doc/viper.R" ], "importsMe": [ "diggit", "diggitdata" ], "dependsOnMe": [ "aracne.networks" ] }, "vsn": { "Package": "vsn", "Version": "3.42.3", "Depends": [ "R (>= 3.0.0)", "Biobase" ], "Imports": [ "methods", "affy", "limma", "lattice", "ggplot2" ], "Suggests": [ "affydata", "hgu95av2cdf", "BiocStyle", "knitr" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "db262be78cb4020f9485790a0e70f9b1", "NeedsCompilation": "yes", "Title": "Variance stabilization and calibration for microarray data", "Description": "The package implements a method for normalising microarray intensities, and works for single- and multiple-color arrays. It can also be used for data from other technologies, as long as they have similar format. The method uses a robust variant of the maximum-likelihood estimator for an additive-multiplicative error model and affine calibration. The model incorporates data calibration step (a.k.a. normalization), a model for the dependence of the variance on the mean intensity and a variance stabilizing data transformation. Differences between transformed intensities are analogous to \"normalized log-ratios\". However, in contrast to the latter, their variance is independent of the mean, and they are usually more sensitive and specific in detecting differential transcription.", "biocViews": [ "Microarray", "OneChannel", "Preprocessing", "Software", "TwoChannel" ], "Author": "Wolfgang Huber, with contributions from Anja von Heydebreck. Many comments and suggestions by users are acknowledged, among them Dennis Kostka, David Kreil, Hans-Ulrich Klein, Robert Gentleman, Deepayan Sarkar and Gordon Smyth", "Maintainer": "Wolfgang Huber ", "URL": "http://www.r-project.org, http://www.ebi.ac.uk/huber", "VignetteBuilder": "knitr", "source.ver": "src/contrib/vsn_3.42.3.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/vsn_3.42.3.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/vsn_3.42.3.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/vsn_3.42.3.tgz", "vignettes": [ "vignettes/vsn/inst/doc/A-vsn.pdf", "vignettes/vsn/inst/doc/C-likelihoodcomputations.pdf", "vignettes/vsn/inst/doc/D-convergence.pdf" ], "vignetteTitles": [ "Introduction to vsn (Sweave version)", "Likelihood Calculations for vsn", "Verifying and assessing the performance with simulated data" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/vsn/inst/doc/A-vsn.R", "vignettes/vsn/inst/doc/C-likelihoodcomputations.R", "vignettes/vsn/inst/doc/vsn.R" ], "htmlDocs": [ "vignettes/vsn/inst/doc/vsn.html" ], "htmlTitles": [ "Introduction to vsn (HTML version)" ], "dependsOnMe": [ "affyPara", "cellHTS2", "MmPalateMiRNA", "webbioc" ], "importsMe": [ "arrayQualityMetrics", "imageHTS", "LVSmiRNA", "metaseqR", "MSnbase", "pvca", "Ringo", "tilingArray" ], "suggestsMe": [ "adSplit", "beadarray", "BiocCaseStudies", "DESeq", "DESeq2", "estrogen", "flowVS", "ggbio", "GlobalAncova", "globaltest", "limma", "lumi", "PAA", "twilight" ] }, "vtpnet": { "Package": "vtpnet", "Version": "0.14.0", "Depends": [ "R (>= 3.0.0)", "graph", "GenomicRanges", "gwascat", "doParallel", "foreach" ], "Suggests": [ "MotifDb", "VariantAnnotation", "Rgraphviz" ], "License": "Artistic-2.0", "MD5sum": "3a6ec1473cde8baaeea2950142551641", "NeedsCompilation": "no", "Title": "variant-transcription factor-phenotype networks", "Description": "variant-transcription factor-phenotype networks, inspired by Maurano et al., Science (2012), PMID 22955828", "biocViews": [ "Network", "Software" ], "Author": "VJ Carey ", "Maintainer": "VJ Carey ", "source.ver": "src/contrib/vtpnet_0.14.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/vtpnet_0.14.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/vtpnet_0.14.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/vtpnet_0.14.0.tgz", "vignettes": [ "vignettes/vtpnet/inst/doc/vtpnet.pdf" ], "vignetteTitles": [ "vtpnet: variant-transcription factor-network tools" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/vtpnet/inst/doc/vtpnet.R" ] }, "wateRmelon": { "Package": "wateRmelon", "Version": "1.18.0", "Depends": [ "R (>= 2.10)", "Biobase", "limma", "methods", "matrixStats", "methylumi", "lumi", "ROC", "IlluminaHumanMethylation450kanno.ilmn12.hg19", "illuminaio" ], "Imports": [ "Biobase" ], "Suggests": [ "RPMM" ], "Enhances": [ "minfi" ], "License": "GPL-3", "MD5sum": "8619ffd4d72713e28328ecb46b2a1143", "NeedsCompilation": "no", "Title": "Illumina 450 methylation array normalization and metrics", "Description": "15 flavours of betas and three performance metrics, with methods for objects produced by methylumi and minfi packages.", "biocViews": [ "DNAMethylation", "Microarray", "Preprocessing", "QualityControl", "Software", "TwoChannel" ], "Author": "Leonard C Schalkwyk, Ruth Pidsley, Chloe CY Wong, with functions contributed by Nizar Touleimat, Matthieu Defrance, Andrew Teschendorff, Jovana Maksimovic, Tyler Gorrie-Stone, Louis El Khoury", "Maintainer": "Leo ", "source.ver": "src/contrib/wateRmelon_1.18.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/wateRmelon_1.18.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/wateRmelon_1.18.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/wateRmelon_1.18.0.tgz", "vignettes": [ "vignettes/wateRmelon/inst/doc/wateRmelon.pdf" ], "vignetteTitles": [ "The \\Rpackage{wateRmelon} Package" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/wateRmelon/inst/doc/wateRmelon.R" ], "dependsOnMe": [ "bigmelon", "skewr" ], "importsMe": [ "ChAMP", "ENmix" ], "suggestsMe": [ "RnBeads" ] }, "wavClusteR": { "Package": "wavClusteR", "Version": "2.8.0", "Depends": [ "R (>= 3.2)", "GenomicRanges (>= 1.23.16)", "Rsamtools" ], "Imports": [ "methods", "BiocGenerics", "S4Vectors (>= 0.9.25)", "IRanges (>= 2.5.27)", "Biostrings", "foreach", "GenomicFeatures", "ggplot2", "Hmisc", "mclust", "rtracklayer", "seqinr", "stringr", "wmtsa" ], "Suggests": [ "BiocStyle", "knitr", "rmarkdown", "BSgenome.Hsapiens.UCSC.hg19" ], "Enhances": [ "doMC" ], "License": "GPL-2", "MD5sum": "80658f26308c401555423b67170bf2c3", "NeedsCompilation": "no", "Title": "Sensitive and highly resolved identification of RNA-protein interaction sites in PAR-CLIP data", "Description": "The package provides an integrated pipeline for the analysis of PAR-CLIP data. PAR-CLIP-induced transitions are first discriminated from sequencing errors, SNPs and additional non-experimental sources by a non- parametric mixture model. The protein binding sites (clusters) are then resolved at high resolution and cluster statistics are estimated using a rigorous Bayesian framework. Post-processing of the results, data export for UCSC genome browser visualization and motif search analysis are provided. In addition, the package allows to integrate RNA-Seq data to estimate the False Discovery Rate of cluster detection. Key functions support parallel multicore computing. Note: while wavClusteR was designed for PAR-CLIP data analysis, it can be applied to the analysis of other NGS data obtained from experimental procedures that induce nucleotide substitutions (e.g. BisSeq).", "biocViews": [ "Bayesian", "RIPSeq", "RNASeq", "Sequencing", "Software", "Technology" ], "Author": "Federico Comoglio and Cem Sievers", "Maintainer": "Federico Comoglio ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/wavClusteR_2.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/wavClusteR_2.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/wavClusteR_2.8.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/wavClusteR_2.8.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/wavClusteR/inst/doc/wavCluster_vignette.R" ], "htmlDocs": [ "vignettes/wavClusteR/inst/doc/wavCluster_vignette.html" ], "htmlTitles": [ "wavClusteR: a workflow for PAR-CLIP data analysis" ] }, "waveTiling": { "Package": "waveTiling", "Version": "1.16.0", "Depends": [ "oligo", "oligoClasses", "Biobase", "Biostrings", "GenomeGraphs" ], "Imports": [ "methods", "affy", "preprocessCore", "GenomicRanges", "waveslim", "IRanges" ], "Suggests": [ "BSgenome", "BSgenome.Athaliana.TAIR.TAIR9", "waveTilingData", "pd.atdschip.tiling", "TxDb.Athaliana.BioMart.plantsmart22" ], "License": "GPL (>=2)", "Archs": "i386, x64", "MD5sum": "9815ee110bd39d2abe764ac20b42012b", "NeedsCompilation": "yes", "Title": "Wavelet-Based Models for Tiling Array Transcriptome Analysis", "Description": "This package is designed to conduct transcriptome analysis for tiling arrays based on fast wavelet-based functional models.", "biocViews": [ "DifferentialExpression", "GeneExpression", "Microarray", "Software", "TimeCourse" ], "Author": "Kristof De Beuf , Peter Pipelers and Lieven Clement ", "Maintainer": "Kristof De Beuf ", "URL": "https://r-forge.r-project.org/projects/wavetiling/", "source.ver": "src/contrib/waveTiling_1.16.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/waveTiling_1.16.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/waveTiling_1.16.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/waveTiling_1.16.0.tgz", "vignettes": [ "vignettes/waveTiling/inst/doc/waveTiling-vignette.pdf" ], "vignetteTitles": [ "The waveTiling package" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/waveTiling/inst/doc/waveTiling-vignette.R" ] }, "weaver": { "Package": "weaver", "Version": "1.40.0", "Depends": [ "R (>= 2.5.0)", "digest", "tools", "utils", "codetools" ], "Suggests": [ "codetools" ], "License": "GPL-2", "MD5sum": "bb4f562dadf71ff72028bcf2a581a0ad", "NeedsCompilation": "no", "Title": "Tools and extensions for processing Sweave documents", "Description": "This package provides enhancements on the Sweave() function in the base package. In particular a facility for caching code chunk results is included.", "biocViews": [ "Infrastructure", "Software" ], "Author": "Seth Falcon", "Maintainer": "Seth Falcon ", "source.ver": "src/contrib/weaver_1.40.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/weaver_1.40.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/weaver_1.40.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/weaver_1.40.0.tgz", "vignettes": [ "vignettes/weaver/inst/doc/weaver_howTo.pdf" ], "vignetteTitles": [ "Using weaver to process Sweave documents" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/weaver/inst/doc/weaver_howTo.R" ], "suggestsMe": [ "BiocCaseStudies" ] }, "webbioc": { "Package": "webbioc", "Version": "1.46.0", "Depends": [ "R (>= 1.8.0)", "Biobase", "affy", "multtest", "annaffy", "vsn", "gcrma", "qvalue" ], "Imports": [ "multtest", "qvalue", "stats", "utils", "BiocInstaller" ], "License": "GPL (>= 2)", "MD5sum": "1e78ac32eb42e17d9d5fdc76f1a6b206", "NeedsCompilation": "no", "Title": "Bioconductor Web Interface", "Description": "An integrated web interface for doing microarray analysis using several of the Bioconductor packages. It is intended to be deployed as a centralized bioinformatics resource for use by many users. (Currently only Affymetrix oligonucleotide analysis is supported.)", "biocViews": [ "DifferentialExpression", "Infrastructure", "Microarray", "OneChannel", "Software" ], "Author": "Colin A. Smith ", "Maintainer": "Colin A. Smith ", "URL": "http://www.bioconductor.org/", "SystemRequirements": "Unix, Perl (>= 5.6.0), Netpbm", "source.ver": "src/contrib/webbioc_1.46.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/webbioc_1.46.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/webbioc_1.46.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/webbioc_1.46.0.tgz", "vignettes": [ "vignettes/webbioc/inst/doc/demoscript.pdf", "vignettes/webbioc/inst/doc/webbioc.pdf" ], "vignetteTitles": [ "webbioc Demo Script", "webbioc Overview" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false }, "widgetTools": { "Package": "widgetTools", "Version": "1.52.0", "Depends": [ "R (>= 2.4.0)", "methods", "utils", "tcltk" ], "Suggests": [ "Biobase" ], "License": "LGPL", "MD5sum": "66112f14cda80ecf57cecb4fc9014ce2", "NeedsCompilation": "no", "Title": "Creates an interactive tcltk widget", "Description": "This packages contains tools to support the construction of tcltk widgets", "biocViews": [ "Infrastructure", "Software" ], "Author": "Jianhua Zhang", "Maintainer": "Jianhua Zhang ", "source.ver": "src/contrib/widgetTools_1.52.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/widgetTools_1.52.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/widgetTools_1.52.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/widgetTools_1.52.0.tgz", "vignettes": [ "vignettes/widgetTools/inst/doc/widgetTools.pdf" ], "vignetteTitles": [ "widgetTools Introduction" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/widgetTools/inst/doc/widgetTools.R" ], "dependsOnMe": [ "tkWidgets" ], "importsMe": [ "OLINgui" ], "suggestsMe": [ "affy" ] }, "XBSeq": { "Package": "XBSeq", "Version": "1.4.0", "Depends": [ "DESeq2", "R (>= 3.2.0)" ], "Imports": [ "pracma", "matrixStats", "locfit", "ggplot2", "methods", "Biobase", "dplyr", "Delaporte", "magrittr", "roar" ], "Suggests": [ "knitr", "DESeq", "rmarkdown", "BiocStyle", "testthat" ], "License": "GPL (>=3)", "MD5sum": "ce32ab4af47860b538f2f0221f9da0ec", "NeedsCompilation": "no", "Title": "Test for differential expression for RNA-seq data", "Description": "We developed a novel algorithm, XBSeq, where a statistical model was established based on the assumption that observed signals are the convolution of true expression signals and sequencing noises. The mapped reads in non-exonic regions are considered as sequencing noises, which follows a Poisson distribution. Given measureable observed and noise signals from RNA-seq data, true expression signals, assuming governed by the negative binomial distribution, can be delineated and thus the accurate detection of differential expressed genes.", "biocViews": [ "DifferentialExpression", "ExperimentalDesign", "RNASeq", "Sequencing", "Software" ], "Author": "Yuanhang Liu", "Maintainer": "Yuanhang Liu ", "URL": "https://github.com/Liuy12/XBSeq", "VignetteBuilder": "rmarkdown", "source.ver": "src/contrib/XBSeq_1.4.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/XBSeq_1.4.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/XBSeq_1.4.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/XBSeq_1.4.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false }, "xcms": { "Package": "xcms", "Version": "1.50.1", "Depends": [ "R (>= 2.14.0)", "methods", "mzR (>= 1.1.6)", "BiocGenerics", "ProtGenerics", "Biobase" ], "Imports": [ "lattice", "RColorBrewer", "plyr", "RANN", "multtest", "MassSpecWavelet (>= 1.5.2)", "BiocParallel", "S4Vectors" ], "Suggests": [ "BiocStyle", "knitr (>= 1.1.0)", "faahKO", "msdata", "ncdf4", "rgl", "RUnit" ], "Enhances": [ "Rgraphviz", "Rmpi", "XML" ], "License": "GPL (>= 2) + file LICENSE", "Archs": "i386, x64", "MD5sum": "141ee8a11a1f26a11e37eb6dce3474f8", "NeedsCompilation": "yes", "Title": "LC/MS and GC/MS Data Analysis", "Description": "Framework for processing and visualization of chromatographically separated and single-spectra mass spectral data. Imports from AIA/ANDI NetCDF, mzXML, mzData and mzML files. Preprocesses data for high-throughput, untargeted analyte profiling.", "biocViews": [ "MassSpectrometry", "Metabolomics", "Software" ], "Author": "Colin A. Smith , Ralf Tautenhahn , Steffen Neumann , Paul Benton , Christopher Conley , Johannes Rainer ", "Maintainer": "Steffen Neumann ", "URL": "http://metlin.scripps.edu/download/ and https://github.com/sneumann/xcms", "VignetteBuilder": "knitr", "BugReports": "https://github.com/sneumann/xcms/issues/new", "source.ver": "src/contrib/xcms_1.50.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/xcms_1.50.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/xcms_1.50.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/xcms_1.50.1.tgz", "vignettes": [ "vignettes/xcms/inst/doc/xcmsDirect.pdf", "vignettes/xcms/inst/doc/xcmsInstall.pdf", "vignettes/xcms/inst/doc/xcmsMSn.pdf", "vignettes/xcms/inst/doc/xcmsPreprocess.pdf" ], "vignetteTitles": [ "Grouping FTICR-MS data with xcms", "Installation Instructions for xcms", "Processing Tandem-MS and MS$^n$ data with xcms", "LC/MS Preprocessing and Analysis with xcms" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": true, "Rfiles": [ "vignettes/xcms/inst/doc/xcmsDirect.R", "vignettes/xcms/inst/doc/xcmsMSn.R", "vignettes/xcms/inst/doc/xcmsPreprocess.R" ], "dependsOnMe": [ "CAMERA", "faahKO", "flagme", "IPO", "LOBSTAHS", "Metab", "metaMS", "proFIA", "PtH2O2lipids" ], "importsMe": [ "CAMERA", "cosmiq", "MAIT", "Risa" ], "suggestsMe": [ "MassSpecWavelet", "msdata", "msPurity", "mtbls2", "RforProteomics", "RMassBank", "ropls" ] }, "XDE": { "Package": "XDE", "Version": "2.20.0", "Depends": [ "R (>= 2.10.0)", "Biobase (>= 2.5.5)", "methods", "graphics" ], "Imports": [ "Biobase", "BiocGenerics", "genefilter", "graphics", "grDevices", "gtools", "MergeMaid", "methods", "stats", "utils", "mvtnorm" ], "Suggests": [ "siggenes", "genefilter", "MASS", "RColorBrewer", "GeneMeta", "RUnit" ], "Enhances": [ "coda" ], "License": "LGPL-2", "Archs": "i386, x64", "MD5sum": "2b2d6edcc4e1c022c03ed3615a454c30", "NeedsCompilation": "yes", "Title": "XDE: a Bayesian hierarchical model for cross-study analysis of differential gene expression", "Description": "Multi-level model for cross-study detection of differential gene expression.", "biocViews": [ "DifferentialExpression", "Microarray", "Software" ], "Author": "R.B. Scharpf, G. Parmigiani, A.B. Nobel, and H. Tjelmeland", "Maintainer": "Robert Scharpf ", "source.ver": "src/contrib/XDE_2.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/XDE_2.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/XDE_2.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/XDE_2.20.0.tgz", "vignettes": [ "vignettes/XDE/inst/doc/XDE.pdf", "vignettes/XDE/inst/doc/XdeParameterClass.pdf" ], "vignetteTitles": [ "XDE Vignette", "XdeParameterClass Vignette" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/XDE/inst/doc/XDE.R", "vignettes/XDE/inst/doc/XdeParameterClass.R" ] }, "xmapbridge": { "Package": "xmapbridge", "Version": "1.32.0", "Depends": [ "R (>= 2.0)", "methods" ], "Suggests": [ "RUnit", "RColorBrewer" ], "License": "LGPL-3", "MD5sum": "aec80bb5dd9d3a1c096f8291f331a1b3", "NeedsCompilation": "no", "Title": "Export plotting files to the xmapBridge for visualisation in X:Map", "Description": "xmapBridge can plot graphs in the X:Map genome browser. This package exports plotting files in a suitable format.", "biocViews": [ "Annotation", "ReportWriting", "Software", "Visualization" ], "Author": "Tim Yates and Crispin J Miller ", "Maintainer": "Chris Wirth ", "URL": "http://xmap.picr.man.ac.uk, http://www.bioconductor.org", "source.ver": "src/contrib/xmapbridge_1.32.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/xmapbridge_1.32.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/xmapbridge_1.32.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/xmapbridge_1.32.0.tgz", "vignettes": [ "vignettes/xmapbridge/inst/doc/xmapbridge.pdf" ], "vignetteTitles": [ "xmapbridge primer" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/xmapbridge/inst/doc/xmapbridge.R" ] }, "xps": { "Package": "xps", "Version": "1.34.0", "Depends": [ "R (>= 2.6.0)", "methods", "utils" ], "Suggests": [ "tools" ], "License": "GPL (>= 2.0)", "MD5sum": "b365346f597fafe54c6cd375b0ef1e57", "NeedsCompilation": "yes", "Title": "Processing and Analysis of Affymetrix Oligonucleotide Arrays including Exon Arrays, Whole Genome Arrays and Plate Arrays", "Description": "The package handles pre-processing, normalization, filtering and analysis of Affymetrix GeneChip expression arrays, including exon arrays (Exon 1.0 ST: core, extended, full probesets), gene arrays (Gene 1.0 ST) and plate arrays on computers with 1 GB RAM only. It imports Affymetrix .CDF, .CLF, .PGF and .CEL as well as annotation files, and computes e.g. RMA, MAS5, FARMS, DFW, FIRMA, tRMA, MAS5-calls, DABG-calls, I/NI-calls. It is an R wrapper to XPS (eXpression Profiling System), which is based on ROOT, an object-oriented framework developed at CERN. Thus, the prior installation of ROOT is a prerequisite for the usage of this package, however, no knowledge of ROOT is required. ROOT is licensed under LGPL and can be downloaded from http://root.cern.ch.", "biocViews": [ "DataImport", "DifferentialExpression", "ExonArray", "GeneExpression", "Microarray", "OneChannel", "Preprocessing", "Software", "Transcription" ], "Author": "Christian Stratowa, Vienna, Austria", "Maintainer": "Christian Stratowa ", "SystemRequirements": "GNU make, root_v5.34.05 - See README file for installation instructions.", "source.ver": "src/contrib/xps_1.34.0.tar.gz", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/xps_1.34.0.tgz", "vignettes": [ "vignettes/xps/inst/doc/APTvsXPS.pdf", "vignettes/xps/inst/doc/xps.pdf", "vignettes/xps/inst/doc/xpsClasses.pdf", "vignettes/xps/inst/doc/xpsPreprocess.pdf" ], "vignetteTitles": [ "3. XPS Vignette: Comparison APT vs XPS", "1. XPS Vignette: Overview", "2. XPS Vignette: Classes", "4. XPS Vignette: Function express()" ], "hasREADME": true, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/xps/inst/doc/APTvsXPS.R", "vignettes/xps/inst/doc/xps.R", "vignettes/xps/inst/doc/xpsClasses.R", "vignettes/xps/inst/doc/xpsPreprocess.R" ] }, "XVector": { "Package": "XVector", "Version": "0.14.1", "Depends": [ "R (>= 2.8.0)", "methods", "BiocGenerics (>= 0.19.2)", "S4Vectors (>= 0.9.29)", "IRanges (>= 2.5.27)" ], "Imports": [ "methods", "zlibbioc", "BiocGenerics", "S4Vectors", "IRanges" ], "LinkingTo": [ "S4Vectors", "IRanges" ], "Suggests": [ "Biostrings", "drosophila2probe", "RUnit" ], "License": "Artistic-2.0", "Archs": "i386, x64", "MD5sum": "27445c0311b9eab3cf1cf032bc55f538", "NeedsCompilation": "yes", "Title": "Representation and manpulation of external sequences", "Description": "Memory efficient S4 classes for storing sequences \"externally\" (behind an R external pointer, or on disk).", "biocViews": [ "DataRepresentation", "Infrastructure", "Software" ], "Author": "Hervé Pagès and Patrick Aboyoun", "Maintainer": "Hervé Pagès ", "source.ver": "src/contrib/XVector_0.14.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/XVector_0.14.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/XVector_0.14.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/XVector_0.14.1.tgz", "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "dependsOnMe": [ "Biostrings", "motifRG", "triplex" ], "importsMe": [ "Biostrings", "BSgenome", "ChIPsim", "CNEr", "compEpiTools", "DECIPHER", "gcrma", "GenomicFeatures", "GenomicRanges", "Gviz", "IONiseR", "kebabs", "MatrixRider", "motifRG", "R453Plus1Toolbox", "Rsamtools", "rtracklayer", "TFBSTools", "tracktables", "VariantAnnotation" ], "suggestsMe": [ "IRanges" ] }, "yamss": { "Package": "yamss", "Version": "1.0.4", "Depends": [ "R (>= 3.3.0)", "methods", "BiocGenerics (>= 0.15.3)", "SummarizedExperiment" ], "Imports": [ "IRanges", "stats", "S4Vectors", "EBImage", "Matrix", "mzR", "data.table", "grDevices", "limma" ], "Suggests": [ "BiocStyle", "knitr", "rmarkdown", "digest", "mtbls2", "testthat" ], "License": "Artistic-2.0", "MD5sum": "7dc8eb8e5561590c551d57c0a78916f0", "NeedsCompilation": "no", "Title": "Tools for high-throughput metabolomics", "Description": "Tools to analyze and visualize high-throughput metabolomics data aquired using chromatography-mass spectrometry. These tools preprocess data in a way that enables reliable and powerful differential analysis.", "biocViews": [ "MassSpectrometry", "Metabolomics", "Software" ], "Author": "Leslie Myint [cre, aut], Kasper Daniel Hansen [aut]", "Maintainer": "Leslie Myint ", "URL": "https://github.com/hansenlab/yamss", "VignetteBuilder": "knitr", "BugReports": "https://github.com/hansenlab/yamss/issues", "source.ver": "src/contrib/yamss_1.0.4.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/yamss_1.0.4.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/yamss_1.0.4.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/yamss_1.0.4.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/yamss/inst/doc/yamss.R" ], "htmlDocs": [ "vignettes/yamss/inst/doc/yamss.html" ], "htmlTitles": [ "yamss User's Guide" ] }, "YAPSA": { "Package": "YAPSA", "Version": "1.0.0", "Depends": [ "R (>= 3.3.0)", "GenomicRanges", "ggplot2", "grid" ], "Imports": [ "lsei", "SomaticSignatures", "VariantAnnotation", "GenomeInfoDb", "reshape2", "gridExtra", "corrplot", "dendextend", "GetoptLong", "circlize", "gtrellis", "PMCMR", "ComplexHeatmap", "KEGGREST", "grDevices" ], "Suggests": [ "BSgenome.Hsapiens.UCSC.hg19", "testthat", "BiocStyle", "knitr", "rmarkdown" ], "License": "GPL-3", "MD5sum": "f34f5a5f9dd96ef12e690bd853123ed3", "NeedsCompilation": "no", "Title": "Yet Another Package for Signature Analysis", "Description": "This package provides functions and routines useful in the analysis of somatic signatures (cf. L. Alexandrov et al., Nature 2013). In particular, functions to perform a signature analysis with known signatures (LCD = linear combination decomposition) and a signature analysis on stratified mutational catalogue (SMC = stratify mutational catalogue) are provided.", "biocViews": [ "BiologicalQuestion", "Clustering", "DNASeq", "GenomicVariation", "Sequencing", "Software", "SomaticMutation", "StatisticalMethod", "Visualization" ], "Author": "Daniel Huebschmann, Zuguang Gu, Matthias Schlesner", "Maintainer": "Daniel Huebschmann ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/YAPSA_1.0.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/YAPSA_1.0.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/YAPSA_1.0.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/YAPSA_1.0.0.tgz", "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/YAPSA/inst/doc/YAPSA.R" ], "htmlDocs": [ "vignettes/YAPSA/inst/doc/YAPSA.html" ], "htmlTitles": [ "YAPSA" ] }, "yaqcaffy": { "Package": "yaqcaffy", "Version": "1.34.0", "Depends": [ "simpleaffy (>= 2.19.3)", "methods" ], "Imports": [ "stats4" ], "Suggests": [ "MAQCsubsetAFX", "affydata", "xtable", "tcltk2", "tcltk" ], "License": "Artistic-2.0", "MD5sum": "ed61494fa21c589c110a52aee997002e", "NeedsCompilation": "no", "Title": "Affymetrix expression data quality control and reproducibility analysis", "Description": "Quality control of Affymetrix GeneChip expression data and reproducibility analysis of human whole genome chips with the MAQC reference datasets.", "biocViews": [ "Microarray", "OneChannel", "QualityControl", "ReportWriting", "Software" ], "Author": "Laurent Gatto", "Maintainer": "Laurent Gatto ", "source.ver": "src/contrib/yaqcaffy_1.34.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/yaqcaffy_1.34.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/yaqcaffy_1.34.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/yaqcaffy_1.34.0.tgz", "vignettes": [ "vignettes/yaqcaffy/inst/doc/yaqcaffy.pdf" ], "vignetteTitles": [ "yaqcaffy: Affymetrix quality control and MAQC reproducibility" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/yaqcaffy/inst/doc/yaqcaffy.R" ], "suggestsMe": [ "qcmetrics" ] }, "yarn": { "Package": "yarn", "Version": "1.0.1", "Depends": [ "Biobase" ], "Imports": [ "biomaRt", "downloader", "edgeR", "gplots", "graphics", "limma", "matrixStats", "preprocessCore", "readr", "RColorBrewer", "stats", "quantro" ], "Suggests": [ "knitr", "rmarkdown", "testthat (>= 0.8)" ], "License": "Artistic-2.0", "MD5sum": "143e46d549a57666da8c17f47c5355a6", "NeedsCompilation": "no", "Title": "YARN: Robust Multi-Condition RNA-Seq Preprocessing and Normalization", "Description": "Expedite large RNA-Seq analyses using a combination of previously developed tools. YARN is meant to make it easier for the user in performing basic mis-annotation quality control, filtering, and condition-aware normalization. YARN leverages many Bioconductor tools and statistical techniques to account for the large heterogeneity and sparsity found in very large RNA-seq experiments.", "biocViews": [ "Annotation", "Clustering", "GeneExpression", "Normalization", "Preprocessing", "QualityControl", "Sequencing", "Software", "Visualization" ], "Author": "Joseph N Paulson [aut, cre], Cho-Yi Chen [aut], Camila Lopes-Ramos [aut], Marieke Kuijjer [aut], John Platig [aut], Abhijeet Sonawane [aut], Maud Fagny [aut], Kimberly Glass [aut], John Quackenbush [aut]", "Maintainer": "Joseph N Paulson ", "VignetteBuilder": "knitr", "source.ver": "src/contrib/yarn_1.0.1.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/yarn_1.0.1.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/yarn_1.0.1.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/yarn_1.0.1.tgz", "vignettes": [ "vignettes/yarn/inst/doc/yarn.pdf" ], "vignetteTitles": [ "YARN: Robust Multi-Tissue RNA-Seq Preprocessing and Normalization" ], "hasREADME": false, "hasNEWS": true, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/yarn/inst/doc/yarn.R" ] }, "zlibbioc": { "Package": "zlibbioc", "Version": "1.20.0", "License": "Artistic-2.0 + file LICENSE", "Archs": "i386, x64", "MD5sum": "f68b45fca70f39c7958fb43c0504c546", "NeedsCompilation": "yes", "Title": "An R packaged zlib-1.2.5", "Description": "This package uses the source code of zlib-1.2.5 to create libraries for systems that do not have these available via other means (most Linux and Mac users should have system-level access to zlib, and no direct need for this package). See the vignette for instructions on use.", "biocViews": [ "Infrastructure", "Software" ], "Author": "Martin Morgan", "Maintainer": "Bioconductor Package Maintainer ", "URL": "http://bioconductor.org/packages/release/bioc/html/Zlibbioc.html", "source.ver": "src/contrib/zlibbioc_1.20.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.3/zlibbioc_1.20.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.3/zlibbioc_1.20.0.zip", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.3/zlibbioc_1.20.0.tgz", "vignettes": [ "vignettes/zlibbioc/inst/doc/UsingZlibbioc.pdf" ], "vignetteTitles": [ "Using zlibbioc C libraries" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": true, "dependsOnMe": [ "BitSeq", "seqTools" ], "importsMe": [ "affy", "affyio", "affyPLM", "bamsignals", "ChemmineOB", "DiffBind", "LVSmiRNA", "MADSEQ", "makecdfenv", "ncdfFlow", "oligo", "polyester", "QuasR", "rhdf5", "Rhtslib", "Rsamtools", "rtracklayer", "seqbias", "ShortRead", "snpStats", "Starr", "TransView", "VariantAnnotation", "XVector" ] } }