# CoGAPS Version: 3.3.50 [](https://bioconductor.org/packages/CoGAPS) [](https://bioconductor.org/packages/CoGAPS) Coordinated Gene Activity in Pattern Sets (CoGAPS) implements a Bayesian MCMC matrix factorization algorithm, GAPS, and links it to gene set statistic methods to infer biological process activity. It can be used to perform sparse matrix factorization on any data, and when this data represents biomolecules, to do gene set analysis. # Installing CoGAPS *CoGAPS* is a bioconductor R package and so the release version can be installed as follows: ``` source("https://bioconductor.org/biocLite.R") biocLite("CoGAPS") ``` The most up-to-date version of *CoGAPS* can be installed directly from the *FertigLab* Github Repository: ``` ## Method 1 using biocLite biocLite("FertigLab/CoGAPS", dependencies = TRUE, build_vignettes = TRUE) ## Method 2 using devtools package devtools::install_github("FertigLab/CoGAPS") ``` There is also an option to install the development version of *CoGAPS*, while this version has the latest experimental features, it is not guaranteed to be stable. ``` ## Method 1 using biocLite biocLite("FertigLab/CoGAPS", ref="develop", dependencies = TRUE, build_vignettes = TRUE) ## Method 2 using devtools package devtools::install_github("FertigLab/CoGAPS", ref="develop") ``` # Using CoGAPS Follow the vignette here: http://htmlpreview.github.io/?https://github.com/FertigLab/CoGAPS/blob/develop/vignettes/CoGAPS.html