Name Mode Size
..
CoGAPS.R 100755 7 kb
DistributedCogaps.R 100755 10 kb
HelperFunctions.R 100755 13 kb
Package.R 100755 1 kb
RcppExports.R 100755 1 kb
SubsetData.R 100755 4 kb
class-CogapsParams.R 100755 12 kb
class-CogapsResult.R 100755 12 kb
methods-CogapsParams.R 100755 4 kb
methods-CogapsResult.R 100755 16 kb
README.md
# CoGAPS Version: 3.2.40 [![Bioc](https://bioconductor.org/images/logo_bioconductor.gif)](https://bioconductor.org/packages/CoGAPS) [![downloads](https://bioconductor.org/shields/downloads/release/CoGAPS.svg)](http://bioconductor.org/packages/stats/bioc/CoGAPS/) [![Build Status](https://travis-ci.org/FertigLab/CoGAPS.svg?branch=master)](https://travis-ci.org/FertigLab/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: ``` install.packages("BiocManager") BiocManager::install("CoGAPS") ``` The most up-to-date version of *CoGAPS* can be installed directly from the *FertigLab* Github Repository: ``` ## Method 1 using BiocManager BiocManager::install("FertigLab/CoGAPS") ## Method 2 using devtools package devtools::install_github("FertigLab/CoGAPS") ``` # Using CoGAPS Follow the vignette here: http://htmlpreview.github.io/?https://github.com/FertigLab/CoGAPS/blob/develop/vignettes/CoGAPS.html