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

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Current Bioconductor build status

  • release Bioconductor Availability Bioconductor Dependencies Bioconductor Commits Bioconductor Release Build
  • development Bioconductor Availability Bioconductor Dependencies Bioconductor Commits 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 such as 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 https://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 Bioconductor and then type the following line from the R shell:

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

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

install.packages("remotes")
library(remotes)
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 feature requests or bug reports and issues regarding this development version of GSVA please use the GitHub issues tab at the top-left of this page.

Contributing

Contributions to the software codebase of GSVA are welcome as long as contributors abide to the terms of the Bioconductor Contributor Code of Conduct. If you want to contribute to the development of GSVA please open an issue to start discussing your suggestion or, in case of a bugfix or a straightforward feature, directly a pull request.

Funding

This software project was supported in part by the Essential Open Source Software for Science (EOSS) program at Chan Zuckerberg Initiative, and the Spanish Ministry of Science, Innovation and Universities.