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

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.

AuthorJustin Guinney with contributions from Robert Castelo
Date of publicationNone
MaintainerJustin Guinney <justin.guinney@sagebase.org>
LicenseGPL (>= 2)
Version1.22.3
http://www.sagebase.org

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Files in this package

GSVA/DESCRIPTION
GSVA/NAMESPACE
GSVA/NEWS
GSVA/R
GSVA/R/gsva.R
GSVA/build
GSVA/build/vignette.rds
GSVA/cleanup
GSVA/inst
GSVA/inst/CITATION
GSVA/inst/doc
GSVA/inst/doc/GSVA.R
GSVA/inst/doc/GSVA.Rnw
GSVA/inst/doc/GSVA.pdf
GSVA/inst/extdata
GSVA/inst/extdata/cache4vignette_leukemia_es.RData
GSVA/man
GSVA/man/computeGeneSetsOverlap.Rd GSVA/man/filterGeneSets.Rd GSVA/man/gsva.Rd
GSVA/src
GSVA/src/kernel_estimation.c
GSVA/src/ks_test.c
GSVA/src/register_cmethods.c
GSVA/vignettes
GSVA/vignettes/GSVA.Rnw
GSVA/vignettes/GSVA.bib
GSVA/vignettes/methods.png

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

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