CoGAPS

DOI: 10.18129/B9.bioc.CoGAPS    

Coordinated Gene Activity in Pattern Sets

Bioconductor version: Release (3.14)

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>, Melanie L. Loth <mloth1 at jhmi.edu>

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

Installation

To install this package, start R (version "4.1") 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")

 

HTML R Script CoGAPS
PDF   Reference Manual
Text   NEWS
Text   LICENSE

Details

biocViews Bayesian, Clustering, DifferentialExpression, DimensionReduction, GeneExpression, GeneSetEnrichment, ImmunoOncology, Microarray, MultipleComparison, RNASeq, Software, TimeCourse, Transcription
Version 3.14.0
In Bioconductor since BioC 2.7 (R-2.12) (11.5 years)
License BSD_3_clause + file LICENSE
Depends R (>= 3.5.0)
Imports BiocParallel, cluster, methods, gplots, graphics, grDevices, RColorBrewer, Rcpp, S4Vectors, SingleCellExperiment, stats, SummarizedExperiment, tools, utils, rhdf5
LinkingTo Rcpp, BH
Suggests testthat, knitr, rmarkdown, BiocStyle
SystemRequirements
Enhances
URL
Depends On Me
Imports Me projectR
Suggests Me
Links To Me
Build Report  

Package Archives

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

Source Package CoGAPS_3.14.0.tar.gz
Windows Binary CoGAPS_3.14.0.zip (32- & 64-bit)
macOS 10.13 (High Sierra) CoGAPS_3.14.0.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 3.14 Source Archive

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