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GSVA : Gene Set Variation Analysis for microarray and RNA-seq data

Package: GSVA
Version: 1.20.0
Title: Gene Set Variation Analysis for microarray and RNA-seq data
Author: Justin Guinney with contributions from Robert Castelo
Maintainer: Justin Guinney <justin.guinney@sagebase.org>
Depends: R (>= 2.13.0)
Imports: methods, BiocGenerics, Biobase, GSEABase (>= 1.17.4)
Suggests: limma, RColorBrewer, genefilter, mclust, edgeR, snow,
parallel, GSVAdata
Description: 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.
License: GPL (>= 2)
LazyLoad: yes
biocViews: Microarray, Pathways, GeneSetEnrichment
URL: http://www.sagebase.org
Encoding: latin1
NeedsCompilation: yes
Packaged: 2016-05-04 04:11:27 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: GeneSetEnrichment, Microarray, Pathways
● 0 images, 3 functions, 0 datasets
Reverse Depends: 2