To install this package, start R and enter:
## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("GSVA")
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GSVA
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This package is for version 2.8 of Bioconductor; for the stable, up-to-date release version, see GSVA.
Gene Set Variation Analysis
Bioconductor version: 2.8
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. Users on all platforms must install the GNU Scientific Library; see the README file, available in the source distribution of this file, for details.
Author: Justin Guinney <justin.guinney at sagebase.org> (with contributions from Robert Castelo <robert.castelo at upf.edu> and Sonja Haenzelmann Maintainer: Justin Guinney <justin.guinney at sagebase.org> Citation (from within R,
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Installation instructions to use this
package in your R session.citation("GSVA")):Installation
## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("GSVA")
Documentation
browseVignettes("GSVA")
PDF
GSVA.pdf
PDF
Reference Manual
Details
biocViews
Bioinformatics, Microarray, Pathways, Software
Version
1.0.1
In Bioconductor since
BioC 2.8 (R-2.13) (5 years)
License
GPL (>= 2)
Depends
R (>= 2.13.0), methods
Imports
methods, Biobase, GSEABase
LinkingTo
Suggests
limma, qpgraph, graph, Rgraphviz, RColorBrewer, genefilter, GSVAdata
SystemRequirements
GNU Scientific Library >= 1.12
Enhances
snow, multicore
URL
http://www.sagebase.org
Depends On Me
Imports Me
Suggests Me
Build Report
Package Archives
Package Source
GSVA_1.0.1.tar.gz
Windows Binary
GSVA_1.0.1.zip (32- & 64-bit)
Mac OS X 10.6 (Snow Leopard)
Mac OS X 10.9 (Mavericks)
Subversion source
(username/password: readonly)
Git source
https://github.com/Bioconductor-mirror/GSVA/tree/release-2.8
Package Short Url
http://bioconductor.org/packages/GSVA/
Package Downloads Report
Download Stats
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