grimbough / CoGAPS

Bayesian MCMC matrix factorization algorithm

Home Page:https://www.bioconductor.org/packages/release/bioc/html/CoGAPS.html

Geek Repo:Geek Repo

Github PK Tool:Github PK Tool

CoGAPS Version: 3.5.13

Bioc downloads Build Status

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 (link) 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:

BiocManager::install("FertigLab/CoGAPS")

Using CoGAPS

Follow the vignette here

About

Bayesian MCMC matrix factorization algorithm

https://www.bioconductor.org/packages/release/bioc/html/CoGAPS.html

License:GNU General Public License v2.0


Languages

Language:C++ 99.4%Language:C 0.4%Language:R 0.2%Language:M4 0.0%