Package: signeR
Type: Package
Title: Empirical Bayesian approach to mutational signature discovery
Version: 2.6.0
Author: Rafael Rosales, Rodrigo Drummond, Renan Valieris,
        Alexandre Defelicibus, Israel Tojal da Silva
Maintainer: Renan Valieris <renan.valieris@accamargo.org.br>
Description: The signeR package provides an empirical Bayesian approach
        to mutational signature discovery. It is designed to analyze
        single nucleotide variation (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.
License: GPL-3
Imports: BiocGenerics, Biostrings, class, grDevices, GenomeInfoDb,
        GenomicRanges, IRanges, nloptr, methods, stats, utils,
        PMCMRplus, parallel, pvclust, ppclust, clue, survival, maxstat,
        survivalAnalysis, future, VGAM, MASS, kknn, glmnet, e1071,
        randomForest, ada, future.apply, ggplot2, pROC, pheatmap,
        RColorBrewer, listenv, reshape2, scales, survminer, dplyr,
        ggpubr, cowplot, tibble, readr, shiny, shinydashboard,
        shinycssloaders, shinyWidgets, bsplus, DT, magrittr, tidyr,
        BiocFileCache, proxy, rtracklayer, BSgenome
Depends: R (>= 3.0.2), VariantAnnotation, NMF
LinkingTo: Rcpp, RcppArmadillo (>= 0.7.100)
SystemRequirements: C++11
URL: https://github.com/TojalLab/signeR
LazyData: true
NeedsCompilation: yes
ByteCompile: TRUE
biocViews: GenomicVariation, SomaticMutation, StatisticalMethod,
        Visualization
Suggests: knitr, BSgenome.Hsapiens.UCSC.hg19,
        BSgenome.Hsapiens.UCSC.hg38, rmarkdown
VignetteBuilder: knitr
RoxygenNote: 7.2.3
Encoding: UTF-8
git_url: https://git.bioconductor.org/packages/signeR
git_branch: RELEASE_3_19
git_last_commit: cc9b68f
git_last_commit_date: 2024-04-30
Repository: Bioconductor 3.19
Date/Publication: 2024-05-01
Packaged: 2024-05-02 02:00:38 UTC; biocbuild
Built: R 4.4.0; x86_64-w64-mingw32; 2024-05-02 13:32:21 UTC; windows
Archs: x64
