Package: edgeR
Version: 3.20.1
Date: 2017-10-31
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
Imports: graphics, stats, utils, methods, locfit, Rcpp
Suggests: MASS, statmod, splines, KernSmooth
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
Packaged: 2017-10-31 23:19:06 UTC; biocbuild
Built: R 3.4.1; x86_64-pc-linux-gnu; 2017-11-06 22:56:42 UTC; unix
