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This is the development version of GSVA; for the stable release version, see GSVA.

Gene Set Variation Analysis for Microarray and RNA-Seq Data

Bioconductor version: Development (3.20)

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: Robert Castelo [aut, cre], Justin Guinney [aut], Alexey Sergushichev [ctb], Pablo Sebastian Rodriguez [ctb], Axel Klenk [ctb]

Maintainer: Robert Castelo <robert.castelo at>

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


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

# The following initializes usage of Bioc devel


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 variation analysis HTML R Script
Reference Manual PDF


biocViews FunctionalGenomics, GeneSetEnrichment, Microarray, Pathways, RNASeq, Software
Version 1.53.4
In Bioconductor since BioC 2.8 (R-2.13) (13.5 years)
License GPL (>= 2)
Depends R (>= 3.5.0)
Imports methods, stats, utils, graphics, S4Vectors, IRanges, Biobase, SummarizedExperiment, GSEABase, Matrix (>= 1.5-0), parallel, BiocParallel, SingleCellExperiment, SpatialExperiment, sparseMatrixStats, DelayedArray, DelayedMatrixStats, HDF5Array, BiocSingular
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Suggests BiocGenerics, RUnit, BiocStyle, knitr, rmarkdown, limma, RColorBrewer,, genefilter, edgeR, GSVAdata, shiny, shinydashboard, ggplot2, data.table, plotly, future, promises, shinybusy, shinyjs
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Depends On Me
Imports Me consensusOV, EGSEA, escape, octad, oppar, scFeatures, singleCellTK, TBSignatureProfiler, autoGO, clustermole, DRviaSPCN, psSubpathway, scMappR, SIGN, sigQC, SMDIC
Suggests Me decoupleR, MCbiclust, ReporterScore
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Source Package GSVA_1.53.4.tar.gz
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macOS Binary (x86_64) GSVA_1.53.4.tgz
macOS Binary (arm64) GSVA_1.53.4.tgz
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