CoGAPS

Coordinated Gene Activity in Pattern Sets


Bioconductor version: Release (3.20)

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, enter citation("CoGAPS")):

Installation

To install this package, start R (version "4.4") 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")
CoGAPS HTML R Script
Reference Manual PDF
NEWS Text
LICENSE Text

Details

biocViews Bayesian, Clustering, DifferentialExpression, DimensionReduction, GeneExpression, GeneSetEnrichment, ImmunoOncology, Microarray, MultipleComparison, RNASeq, Software, TimeCourse, Transcription
Version 3.26.0
In Bioconductor since BioC 2.7 (R-2.12) (14 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, dplyr, fgsea, forcats, ggplot2
System Requirements
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See More
Suggests testthat, knitr, rmarkdown, BiocStyle, SeuratObject, BiocFileCache
Linking To Rcpp, BH
Enhances
Depends On Me
Imports Me
Suggests Me projectR, SpaceMarkers
Links To Me
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Package Archives

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

Source Package CoGAPS_3.26.0.tar.gz
Windows Binary (x86_64) CoGAPS_3.26.0.zip
macOS Binary (x86_64) CoGAPS_3.26.0.tgz
macOS Binary (arm64) CoGAPS_3.26.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/CoGAPS
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/CoGAPS
Bioc Package Browser https://code.bioconductor.org/browse/CoGAPS/
Package Short Url https://bioconductor.org/packages/CoGAPS/
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