Package: edgeR
Version: 4.9.0
Date: 2025-10-10
Title: Empirical Analysis of Digital Gene Expression Data in R
Description: Differential expression analysis of sequence count data.
        Implements a range of statistical methodology based on the
        negative binomial distributions, including empirical Bayes
        estimation, exact tests, generalized linear models,
        quasi-likelihood, and gene set enrichment. Can perform
        differential analyses of any type of omics data that produces
        read counts, including RNA-seq, ChIP-seq, ATAC-seq,
        Bisulfite-seq, SAGE, CAGE, metabolomics, or proteomics spectral
        counts. RNA-seq analyses can be conducted at the gene or
        isoform level, and tests can be conducted for differential exon
        or transcript usage.
Author: Yunshun Chen, Lizhong Chen, Aaron TL Lun, Davis J McCarthy,
        Pedro Baldoni, Matthew E Ritchie, Belinda Phipson, Yifang Hu,
        Xiaobei Zhou, Mark D Robinson, Gordon K Smyth
Maintainer: Yunshun Chen <yuchen@wehi.edu.au>, Gordon Smyth
 <smyth@wehi.edu.au>, Aaron Lun
 <infinite.monkeys.with.keyboards@gmail.com>, Mark Robinson
 <mark.robinson@imls.uzh.ch>
License: GPL (>=2)
Depends: R (>= 3.6.0), limma (>= 3.63.6)
Imports: methods, graphics, stats, utils, locfit
Suggests: arrow, jsonlite, knitr, Matrix, readr, rhdf5, SeuratObject,
        splines, AnnotationDbi, Biobase, BiocStyle, org.Hs.eg.db,
        SummarizedExperiment
VignetteBuilder: knitr
URL: https://bioinf.wehi.edu.au/edgeR/,
        https://bioconductor.org/packages/edgeR
biocViews: AlternativeSplicing, BatchEffect, Bayesian,
        BiomedicalInformatics, CellBiology, ChIPSeq, Clustering,
        Coverage, DifferentialExpression, DifferentialMethylation,
        DifferentialSplicing, DNAMethylation, Epigenetics,
        FunctionalGenomics, GeneExpression, GeneSetEnrichment,
        Genetics, Genetics, ImmunoOncology, MultipleComparison,
        Normalization, Pathways, Proteomics, QualityControl,
        Regression, RNASeq, SAGE, Sequencing, SingleCell,
        SystemsBiology, TimeCourse, Transcription, Transcriptomics
NeedsCompilation: yes
Repository: https://bioc.r-universe.dev
Date/Publication: 2025-10-29 14:01:19 UTC
RemoteUrl: https://github.com/bioc/edgeR
RemoteRef: HEAD
RemoteSha: e338260eb7dc9912759d81a0832820573b0bd8c9
Packaged: 2025-10-30 05:28:09 UTC; root
Built: R 4.6.0; x86_64-w64-mingw32; 2025-10-30 05:34:46 UTC; windows
Archs: x64
