This is the development version of CoGAPS; for the stable release version, see CoGAPS.
Coordinated Gene Activity in Pattern SetsBioconductor version: Development (3.22)
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: Jeanette Johnson, Ashley Tsang, Jacob Mitchell, Thomas Sherman, Wai-shing Lee, Conor Kelton, Ondrej Maxian, Jacob Carey, Genevieve Stein-O'Brien, Michael Considine, Maggie Wodicka, John Stansfield, Shawn Sivy, Carlo Colantuoni, Alexander Favorov, Mike Ochs, Elana Fertig
Maintainer: Elana J. Fertig <ejfertig at jhmi.edu>, Thomas D. Sherman <tomsherman159 at gmail.com>, Jeanette Johnson <jjohn450 at jhmi.edu>, Dmitrijs Lvovs <dlvovs1 at jh.edu>
Citation (from within R, entercitation("CoGAPS")): Installation
To install this package, start R (version "4.5") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
# The following initializes usage of Bioc devel
BiocManager::install(version='devel')
BiocManager::install("CoGAPS")
For older versions of R, please refer to the appropriate Bioconductor release.
DocumentationTo view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("CoGAPS")Follow Installation instructions to use this package in your R session.
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