CoGAPS

DOI: 10.18129/B9.bioc.CoGAPS    

This is the development version of CoGAPS; for the stable release version, see CoGAPS.

Coordinated Gene Activity in Pattern Sets

Bioconductor version: Development (3.8)

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: 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>

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

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("http://bioc.ism.ac.jp/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
HTML R Script GWCoGAPS and PatternMarkers
PDF   Reference Manual
Text   NEWS

Details

biocViews Bayesian, Clustering, DifferentialExpression, DimensionReduction, GeneExpression, GeneSetEnrichment, Microarray, MultipleComparison, RNASeq, Software, TimeCourse, Transcription
Version 3.1.0
In Bioconductor since BioC 2.7 (R-2.12) (7.5 years)
License GPL (==2)
Depends R (>= 3.4.0), Rcpp (>= 0.11.0)
Imports RColorBrewer (>= 1.0.5), gplots (>= 2.8.0), graphics, grDevices, methods, cluster, shiny, stats, utils, doParallel, foreach, ggplot2, reshape2
LinkingTo Rcpp, BH
Suggests testthat, lintr, knitr, rmarkdown, BiocStyle
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me
Build Report  

Package Archives

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

Source Package CoGAPS_3.1.0.tar.gz
Windows Binary CoGAPS_3.1.0.zip (32- & 64-bit)
Mac OS X 10.11 (El Capitan) CoGAPS_3.1.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/CoGAPS
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/CoGAPS
Package Short Url http://bioconductor.org/packages/CoGAPS/
Package Downloads Report Download Stats

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