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Gene set variation analysis for microarray and RNA-seq data
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README.md

GSVA: gene set variation analysis for microarray and RNA-seq data

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Current build status

  • release Bioconductor Availability Bioconductor Release Build
  • development Bioconductor Availability Bioconductor Devel Build

The GSVA package allows one to perform a change in coordinate systems of molecular measurements, 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. For citing GSVA as a software package, please use the following reference:

Hänzelmann S., Castelo R. and Guinney J. GSVA: gene set variation analysis for microarray and RNA-Seq data. BMC Bioinformatics, 14:7, 2013.

Installation

This is the development version of the R/Bioconductor package GSVA. This version is unstable and should be used only to test new features. If you are looking for the release version of this package please go to its package release landing page at http://bioconductor.org/packages/GSVA and follow the instructions there to install it.

If you were really looking for this development version, then to install it you need first to install the development version of R that you can find at http://cran.r-project.org and then type the following instructions from the R shell:

install.packages("BiocManager")
BiocManager::install("GSVA", version = "devel")

Alternatively, you can install it from GitHub using the devtools package.

install.packages("devtools")
library(devtools)
install_github("rcastelo/GSVA")

Questions, bug reports and issues

For questions and bug reports regarding the release version of GSVA please use the Bioconductor support site. For bug reports and issues regarding this development version of GSVA please use the GitHub issues link at the top-right of this page (https://github.com/rcastelo/GSVA/issues).

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