To install this package, start R and enter:

source("http://bioconductor.org/biocLite.R")
biocLite("CoGAPS")

In most cases, you don't need to download the package archive at all.

CoGAPS

Coordinated Gene Activity in Pattern Sets

Bioconductor version: Release (3.0)

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.

Author: Elana J. Fertig, Michael F. Ochs

Maintainer: Elana J. Fertig <ejfertig at jhmi.edu>, Michael F. Ochs <ochsm at tcnj.edu>

Citation (from within R, enter citation("CoGAPS")):

Installation

To install this package, start R and enter:

source("http://bioconductor.org/biocLite.R")
biocLite("CoGAPS")

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("CoGAPS")

 

PDF R Script GAPS/CoGAPS Users Manual
PDF   Reference Manual
Text   NEWS

Details

biocViews GeneExpression, Microarray, Software
Version 2.0.0
In Bioconductor since BioC 2.7 (R-2.12)
License GPL (==2)
Depends R (>= 3.0.1), Rcpp (>= 0.11.2), RColorBrewer (>= 1.0.5), gplots (>= 2.8.0)
Imports graphics, grDevices, methods, stats, utils
Suggests
System Requirements
URL
Depends On Me
Imports Me
Suggests Me

Package Archives

Follow Installation instructions to use this package in your R session.

Package Source CoGAPS_2.0.0.tar.gz
Windows Binary CoGAPS_2.0.0.zip (32- & 64-bit)
Mac OS X 10.6 (Snow Leopard) CoGAPS_2.0.0.tgz
Mac OS X 10.9 (Mavericks) CoGAPS_2.0.0.tgz
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