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Bioconductor - GSVA

GSVA

This is the released version of GSVA; for the devel version, see GSVA.

Gene Set Variation Analysis for Microarray and RNA-Seq Data

Bioconductor version: Release (3.21)

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 upf.edu>

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

To install this package, start R (version "4.5") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("GSVA")

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

Documentation

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

browseVignettes("GSVA")

Details biocViews FunctionalGenomics, GeneSetEnrichment, Microarray, Pathways, RNASeq, Software Version 2.2.0 In Bioconductor since BioC 2.8 (R-2.13) (14 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, cli System Requirements URL https://github.com/rcastelo/GSVA Bug Reports https://github.com/rcastelo/GSVA/issues See More Suggests BiocGenerics, RUnit, BiocStyle, knitr, rmarkdown, limma, RColorBrewer, org.Hs.eg.db, genefilter, edgeR, GSVAdata, sva, shiny, shinydashboard, ggplot2, data.table, plotly, future, promises, shinybusy, shinyjs Linking To cli Enhances Depends On Me SMDIC Imports Me consensusOV, EGSEA, escape, octad, oppar, pathMED, scFeatures, signifinder, singleCellTK, TBSignatureProfiler, autoGO, clustermole, DRviaSPCN, GSEMA, psSubpathway, scMappR, SIGN, sigQC, spatialGE, ssdGSA Suggests Me decoupleR, MCbiclust, mitology, sparrow, SPONGE, ReporterScore Links To Me Build Report Build Report Package Archives

Follow Installation instructions to use this package in your R session.

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