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

Bioconductor version: Release (2.12)

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>

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


biocViews DifferentialExpression, GeneExpression, GeneSetEnrichment, HighThroughputSequencing, RNAseq, Software
Version 1.0.2
In Bioconductor since BioC 2.13 (R-2.18)
License GPL (>= 3)
Depends Biobase, DESeq, biomaRt, foreach
Imports methods, doParallel
System Requirements
Depends On Me
Imports Me
Suggests Me

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Package Source SeqGSEA_1.0.2.tar.gz
Windows Binary (32- & 64-bit)
Mac OS X 10.6 (Snow Leopard) SeqGSEA_1.0.2.tgz
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