DOI: 10.18129/B9.bioc.GSVA  

This package is for version 3.16 of Bioconductor; for the stable, up-to-date release version, see GSVA.

Gene Set Variation Analysis for microarray and RNA-seq data

Bioconductor version: 3.16

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]

Maintainer: Robert Castelo <robert.castelo at>

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biocViews FunctionalGenomics, GeneSetEnrichment, Microarray, Pathways, RNASeq, Software
Version 1.46.0
In Bioconductor since BioC 2.8 (R-2.13) (12 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, sparseMatrixStats, DelayedArray, DelayedMatrixStats, HDF5Array, BiocSingular
Suggests BiocGenerics, RUnit, BiocStyle, knitr, rmarkdown, limma, RColorBrewer,, genefilter, edgeR, GSVAdata, shiny, shinydashboard, ggplot2, data.table, plotly, future, promises, shinybusy, shinyjs
Depends On Me SISPA
Imports Me consensusOV, EGSEA, escape, octad, oppar, signifinder, singleCellTK, TBSignatureProfiler, TNBC.CMS
Suggests Me decoupleR, MCbiclust, sparrow
Links To Me
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