CoGAPS

This package is for version 3.6 of Bioconductor; for the stable, up-to-date release version, see CoGAPS.

Coordinated Gene Activity in Pattern Sets

Bioconductor version: 3.6

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: Wai-shing Lee, Conor Kelton, Ondrej Maxian, Jacob Carey, Genevieve Stein-O'Brien, Michael Considine, John Stansfield, Shawn Sivy, Carlo Colantuoni, Alexander Favorov, Mike Ochs, Elana Fertig

Maintainer: Elana J. Fertig <ejfertig at jhmi.edu>

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

Installation

To install this package, start R (version "3.4") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("CoGAPS")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

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

browseVignettes("CoGAPS")

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

Need some help? Ask on the Bioconductor Support site!

Details

biocViews	Bayesian, Clustering, DifferentialExpression, DimensionReduction, GeneExpression, GeneSetEnrichment, Microarray, MultipleComparison, RNASeq, Software, TimeCourse, Transcription
Version	2.12.0
In Bioconductor since	BioC 2.7 (R-2.12) (13.5 years)
License	GPL (==2)
Depends	R (>= 3.0.1), Rcpp (>= 0.11.2)
Imports	RColorBrewer (>= 1.0.5), gplots (>= 2.8.0), graphics, grDevices, methods, cluster, shiny, stats, utils, doParallel, foreach, ggplot2, reshape2
System Requirements
URL

Suggests	testthat, iterators, parallel, lintr
Linking To	Rcpp, BH, RcppArmadillo
Enhances
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report	Build Report

Package Archives

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

Source Package	CoGAPS_2.12.0.tar.gz
Windows Binary	CoGAPS_2.12.0.zip (32- & 64-bit)
Mac OS X 10.11 (El Capitan)	CoGAPS_2.12.0.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	https://bioconductor.org/packages/CoGAPS/
Package Downloads Report	Download Stats
Old Source Packages for BioC 3.6	Source Archive