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 <>, 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 (>= 3.34.5)
Imports: graphics, stats, utils, methods, locfit, Rcpp
Suggests: AnnotationDbi,, readr, splines
LinkingTo: Rcpp
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