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Empirical analysis of digital gene expression data in R

Bioconductor version: 3.1

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 <yuchen at>, Aaron Lun <alun at>, Davis McCarthy <dmccarthy at>, Xiaobei Zhou <xiaobei.zhou at>, Mark Robinson <mark.robinson at>, Gordon Smyth <smyth at>

Maintainer: Yunshun Chen <yuchen at>, Aaron Lun <alun at>, Mark Robinson <mark.robinson at>, Davis McCarthy <dmccarthy at>, Gordon Smyth <smyth at>

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PDF R Script edgeR Vignette
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biocViews AlternativeSplicing, BatchEffect, Bayesian, ChIPSeq, Clustering, Coverage, DifferentialExpression, DifferentialSplicing, GeneExpression, GeneSetEnrichment, Genetics, MultipleComparison, Normalization, QualityControl, RNASeq, Regression, SAGE, Sequencing, Software, TimeCourse, Transcription
Version 3.10.5
In Bioconductor since BioC 2.3 (R-2.8) (7 years)
License GPL (>=2)
Depends R (>= 2.15.0), limma
Imports methods
Suggests MASS, statmod, splines, locfit, KernSmooth
Depends On Me DBChIP, EDDA, manta, methylMnM, MLSeq, RnaSeqSampleSizeData, RUVSeq, TCC, tRanslatome
Imports Me ampliQueso, ArrayExpressHTS, compcodeR, csaw, DEGreport, DiffBind, diffHic, easyRNASeq, EDDA, EnrichmentBrowser, erccdashboard, HTSFilter, MEDIPS, metaseqR, msmsTests, PROPER, Repitools, ReportingTools, rnaSeqMap, RnaSeqSampleSize, STATegRa, systemPipeR, ToPASeq, tweeDEseq
Suggests Me baySeq, BitSeq, ClassifyR, clonotypeR, cqn, EDASeq, gage, GenomicAlignments, GenomicRanges, goseq, groHMM, GSAR, GSVA, leeBamViews, missMethyl, oneChannelGUI, pasilla, SSPA
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