Package: edgeR
Version: 3.16.5
Date: 2016-12-12
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.
Author: Yunshun Chen <>, Aaron Lun <>, Davis McCarthy <>, Xiaobei Zhou <>, Mark Robinson <>, Gordon Smyth <>
Maintainer: Yunshun Chen <>, Aaron Lun <>, Mark Robinson <>, Davis McCarthy <>, Gordon Smyth <>
License: GPL (>=2)
Depends: R (>= 2.15.0), limma
Imports: graphics, stats, utils, methods, locfit
Suggests: MASS, statmod, splines, KernSmooth
biocViews: GeneExpression, Transcription, AlternativeSplicing,
        Coverage, DifferentialExpression, DifferentialSplicing,
        GeneSetEnrichment, Genetics, Bayesian, Clustering, Regression,
        TimeCourse, SAGE, Sequencing, ChIPSeq, RNASeq, BatchEffect,
        MultipleComparison, Normalization, QualityControl
NeedsCompilation: yes