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Empirical Analysis of Digital Gene Expression Data in R
Empirical Analysis of Digital Gene Expression Data in R
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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.
Summary
Empirical Analysis of Digital Gene Expression Data in R
Last Updated
Feb 7, 2026 at 15:36
License
GPL (>=2)
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