DOI: 10.18129/B9.bioc.CoGAPS    

This package is for version 3.7 of Bioconductor; for the stable, up-to-date release version, see CoGAPS.

Coordinated Gene Activity in Pattern Sets

Bioconductor version: 3.7

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>, Thomas D. Sherman <tomsherman159 at>

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


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PDF R Script GAPS/CoGAPS Users Manual
HTML R Script GWCoGAPS and PatternMarkers
PDF   Reference Manual
Text   NEWS


biocViews Bayesian, Clustering, DifferentialExpression, DimensionReduction, GeneExpression, GeneSetEnrichment, Microarray, MultipleComparison, RNASeq, Software, TimeCourse, Transcription
Version 3.0.2
In Bioconductor since BioC 2.7 (R-2.12) (8 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
Depends On Me
Imports Me
Suggests Me
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