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Gene Set Enrichment Analysis (GSEA) of RNA-Seq Data: integrating differential expression and splicing

Bioconductor version: Release (3.19)

The package generally provides methods for gene set enrichment analysis of high-throughput RNA-Seq data by integrating differential expression and splicing. It uses negative binomial distribution to model read count data, which accounts for sequencing biases and biological variation. Based on permutation tests, statistical significance can also be achieved regarding each gene's differential expression and splicing, respectively.

Author: Xi Wang <Xi.Wang at>

Maintainer: Xi Wang <Xi.Wang at>

Citation (from within R, enter citation("SeqGSEA")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

Gene set enrichment analysis of RNA-Seq data with the SeqGSEA package PDF R Script
Reference Manual PDF


biocViews DifferentialExpression, DifferentialSplicing, GeneExpression, GeneSetEnrichment, ImmunoOncology, RNASeq, Sequencing, Software
Version 1.44.0
In Bioconductor since BioC 2.12 (R-3.0) (11.5 years)
License GPL (>= 3)
Depends Biobase, doParallel, DESeq2
Imports methods, biomaRt
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Follow Installation instructions to use this package in your R session.

Source Package SeqGSEA_1.44.0.tar.gz
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macOS Binary (x86_64) SeqGSEA_1.44.0.tgz
macOS Binary (arm64) SeqGSEA_1.44.0.tgz
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