Gene Set Variation Analysis for microarray and RNA-seq data

Bioconductor version: Release (2.11)

Gene Set Variation Analysis (GSVA) is a non-parametric, unsupervised method for estimating variation of gene set enrichment through the samples of a expression data set. GSVA performs a change in coordinate systems, transforming the data from a gene by sample matrix to a gene-set by sample matrix, thereby allowing the evaluation of pathway enrichment for each sample. This new matrix of GSVA enrichment scores facilitates applying standard analytical methods like functional enrichment, survival analysis, clustering, CNV-pathway analysis or cross-tissue pathway analysis, in a pathway-centric manner.

Author: Justin Guinney <justin.guinney at> (with contributions from Robert Castelo <robert.castelo at> and Sonja Haenzelmann <sonjahaenzelmann at>)

Maintainer: Justin Guinney <justin.guinney at>

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biocViews GeneSetEnrichment, Microarray, Pathways, Software
Version 1.6.6
In Bioconductor since BioC 2.8 (R-2.13)
License GPL (>= 2)
Depends R (>= 2.13.0), methods, GSEABase(>= 1.17.4)
Imports methods, BiocGenerics, Biobase, GSEABase
Suggests limma, RColorBrewer, genefilter, mclust, edgeR, GSVAdata
System Requirements
Depends On Me
Imports Me
Suggests Me

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Package Source GSVA_1.6.6.tar.gz
Windows Binary (32- & 64-bit)
MacOS 10.5 (Leopard) GSVA_1.6.6.tgz
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