Package: edgeR
Version: 3.22.5
Date: 2018-09-26
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, Bisulfite-seq, SAGE and CAGE.
Author: Yunshun Chen <yuchen@wehi.edu.au>, Aaron Lun <alun@wehi.edu.au>, Davis McCarthy <dmccarthy@wehi.edu.au>, Xiaobei Zhou <xiaobei.zhou@uzh.ch>, Mark Robinson <mark.robinson@imls.uzh.ch>, Gordon Smyth <smyth@wehi.edu.au>
Maintainer: Yunshun Chen <yuchen@wehi.edu.au>, Aaron Lun <alun@wehi.edu.au>, Mark Robinson <mark.robinson@imls.uzh.ch>, Davis McCarthy <dmccarthy@wehi.edu.au>, Gordon Smyth <smyth@wehi.edu.au>
License: GPL (>=2)
Depends: R (>= 2.15.0), limma (>= 3.34.5)
Imports: graphics, stats, utils, methods, locfit, Rcpp
Suggests: AnnotationDbi, org.Hs.eg.db, readr, splines
LinkingTo: Rcpp
URL: http://bioinf.wehi.edu.au/edgeR
biocViews: GeneExpression, Transcription, AlternativeSplicing,
        Coverage, DifferentialExpression, DifferentialSplicing,
        DifferentialMethylation, GeneSetEnrichment, Pathways, Genetics,
        DNAMethylation, Bayesian, Clustering, ChIPSeq, Regression,
        TimeCourse, Sequencing, RNASeq, BatchEffect, SAGE,
        Normalization, QualityControl, MultipleComparison
NeedsCompilation: yes
SystemRequirements: C++11
git_url: https://git.bioconductor.org/packages/edgeR
git_branch: RELEASE_3_7
git_last_commit: 44461aa
git_last_commit_date: 2018-09-26
Date/Publication: 2018-10-02
Packaged: 2018-10-02 22:59:04 UTC; biocbuild
Built: R 3.5.1; x86_64-apple-darwin14.5.0; 2018-10-12 23:10:50 UTC; unix
