To install this package, start R and enter:
## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("GSVA")
In most cases, you don't need to download the package archive at all.
GSVA
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Gene Set Variation Analysis for microarray and RNA-seq data
Bioconductor version: Release (3.5)
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 [aut, cre], Robert Castelo [aut]
Maintainer: Justin Guinney <justin.guinney at sagebase.org>
Citation (from within R,
enter citation("GSVA")):
Installation
To install this package, start R and enter:
## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("GSVA")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("GSVA")
| R Script | Gene Set Variation Analysis | |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | GeneSetEnrichment, Microarray, Pathways, Software |
| Version | 1.24.2 |
| In Bioconductor since | BioC 2.8 (R-2.13) (6.5 years) |
| License | GPL (>= 2) |
| Depends | R (>= 2.13.0) |
| Imports | methods, BiocGenerics, Biobase, GSEABase(>= 1.17.4) |
| LinkingTo | |
| Suggests | limma, RColorBrewer, genefilter, mclust, edgeR, snow, parallel, GSVAdata |
| SystemRequirements | |
| Enhances | |
| URL | http://www.sagebase.org |
| Depends On Me | SISPA |
| Imports Me | EGSEA, oppar |
| Suggests Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | GSVA_1.24.2.tar.gz |
| Windows Binary | GSVA_1.24.2.zip (32- & 64-bit) |
| Mac OS X 10.11 (El Capitan) | GSVA_1.24.2.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/GSVA |
| Package Short Url | http://bioconductor.org/packages/GSVA/ |
| Package Downloads Report | Download Stats |
Documentation »
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