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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 SummarizedExperiment objects), while providing an easy mechanism to support other data structures. 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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_2.8.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.1/ExiMiR_2.8.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.1/ExiMiR_2.8.0.zip", "mac.binary.ver": "bin/macosx/contrib/3.1/ExiMiR_2.8.0.tgz", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.1/ExiMiR_2.8.0.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": "1.12.0", "Depends": [ "IRanges", "GenomicRanges", "Rsamtools" ], "Imports": [ "stats4", "methods", "GenomeInfoDb" ], "Suggests": [ "Biostrings" ], "License": "GPL (>= 2)", "Archs": "i386, x64", "MD5sum": "9e83f9ea655d4a9020e28b4e12e74795", "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_1.12.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.1/exomeCopy_1.12.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.1/exomeCopy_1.12.0.zip", "mac.binary.ver": "bin/macosx/contrib/3.1/exomeCopy_1.12.0.tgz", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.1/exomeCopy_1.12.0.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": [ "Rariant", "SomaticCancerAlterations" ] }, "exomePeak": { "Package": "exomePeak", "Version": "1.6.0", "Depends": [ "Rsamtools", "GenomicFeatures (>= 1.14.5)", "rtracklayer" ], "License": "GPL-2", "MD5sum": "7ffd7b622057568357e7bbdbdee18443", "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": "Jia Meng ", "Maintainer": "Jia Meng ", "source.ver": "src/contrib/exomePeak_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.1/exomePeak_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.1/exomePeak_1.6.0.zip", "mac.binary.ver": "bin/macosx/contrib/3.1/exomePeak_1.6.0.tgz", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.1/exomePeak_1.6.0.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" ] }, "explorase": { "Package": "explorase", "Version": "1.30.0", "Depends": [ "R (>= 2.6.2)" ], "Imports": [ "limma", "rggobi", "RGtk2" ], "Suggests": [ "cairoDevice" ], "License": "GPL-2", "MD5sum": "775956341362f9b8571b81add20f07d4", "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_1.30.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.1/explorase_1.30.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.1/explorase_1.30.0.zip", "vignettes": [ "vignettes/explorase/inst/doc/explorase.pdf" ], "vignetteTitles": [ "Introduction to exploRase" ], "hasREADME": false, "hasNEWS": false, "hasINSTALL": false, "hasLICENSE": false, "Rfiles": [ "vignettes/explorase/inst/doc/explorase.R" ] }, "ExpressionView": { "Package": "ExpressionView", "Version": "1.18.0", "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": "57e7253059e4d444d7070664b23f3335", "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. 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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_1.10.2.tar.gz", "win.binary.ver": "bin/windows/contrib/3.1/gCMAP_1.10.2.zip", "win64.binary.ver": "bin/windows64/contrib/3.1/gCMAP_1.10.2.zip", "mac.binary.ver": "bin/macosx/contrib/3.1/gCMAP_1.10.2.tgz", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.1/gCMAP_1.10.2.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": "1.6.0", "Depends": [ "brew", "gCMAP (>= 1.3.0)", "R (>= 2.15.0)", "yaml", "Rook" ], "Imports": [ "Biobase", "annotate", "AnnotationDbi", "BiocGenerics", "brew", "graphics", "grDevices", "GSEABase", "hwriter", "IRanges", "methods", "parallel", "stats", "utils" ], "Suggests": [ "org.Hs.eg.db", "org.Mm.eg.db", "ArrayExpress", "affy", "hgfocus.db", "ArrayExpress", "hgu133a.db", "mgug4104a.db", "RUnit" ], "Enhances": [ "bigmemory", "bigmemoryExtras" ], "License": "Artistic-2.0", "MD5sum": "1d4e63e90012bbdca94394c426cd367f", "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_1.6.0.tar.gz", "win.binary.ver": "bin/windows/contrib/3.1/gCMAPWeb_1.6.0.zip", "win64.binary.ver": "bin/windows64/contrib/3.1/gCMAPWeb_1.6.0.zip", "mac.binary.ver": "bin/macosx/contrib/3.1/gCMAPWeb_1.6.0.tgz", "mac.binary.mavericks.ver": "bin/macosx/mavericks/contrib/3.1/gCMAPWeb_1.6.0.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" ] }, "gcrma": { "Package": "gcrma", "Version": "2.38.0", "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": "edcb1241b8a538a0ec4aa97128136e14", "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. 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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. 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