# GSVA: gene set variation analysis for microarray and RNA-seq data
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**Current build status**
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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.
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](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](https://bioconductor.org/developers/how-to/useDevel) 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](https://github.com/r-lib/remotes "remotes") package.
## Questions, bug reports and issues
For questions and bug reports regarding the __release__ version of **GSVA**
please use the [Bioconductor support site](https://support.bioconductor.org "Bioconductor support site").
For feature requests or bug reports and issues regarding this __development__ version of **GSVA**
please use the GitHub issues [tab](https://github.com/rcastelo/GSVA/issues)) at the top-left of this page.
Contributions to the software codebase of GSVA are welcome as long as contributors abide to the
terms of the [Bioconductor Contributor Code of Conduct](https://bioconductor.org/about/code-of-conduct).
If you want to contribute to the development of GSVA please open an
[issue](https://github.com/rcastelo/GSVA/issues) to start discussing your suggestion or, in case of a
bugfix or a straightforward feature, directly a