CoGAPS
This is the released version of CoGAPS; for the devel version, see CoGAPS.
All Bioconductor versions of CoGAPS
3.24 (devel), 3.23 (release), 3.22, 3.21, 3.20, 3.19, 3.18, 3.17, 3.16, 3.15, 3.14, 3.13, 3.12, 3.11, 3.10, 3.9, 3.8, 3.7, 3.6, 3.5, 3.4, 3.3, 3.2, 3.1, 3.0, 2.14, 2.13, 2.12, 2.11, 2.10, 2.9, 2.8, 2.7
Coordinated Gene Activity in Pattern Sets
Bioconductor version: 3.23 · Package version: 3.32.0
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"):
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. CoGAPS: Coordinated Gene Activity in Pattern Sets. doi:10.18129/B9.bioc.CoGAPS, R package version 3.32.0, https://bioconductor.org/packages/CoGAPS.
Generated from the package metadata; it may differ from the package's own citation.
Installation
To install this package, start R (version "4.6") 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.
Details
| Version | 3.32.0 |
| License | BSD_3_clause + file LICENSE |
| Last updated | 2026-04-28 |
| In Bioconductor since | BioC 2.7 (R-2.12) (15 years) |
| Downloads rank | 679 of 2,418 |
| Source branch | RELEASE_3_23 |
| Build report | Bioconductor build system, r-universe |
| biocViews | Bayesian, Clustering, DifferentialExpression, DimensionReduction, GeneExpression, GeneSetEnrichment, ImmunoOncology, Microarray, MultipleComparison, RNASeq, Software, TimeCourse, Transcription |
| Package Short Url | https://bioconductor.org/packages/CoGAPS/ |
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("CoGAPS")| CoGAPS - Coordinated Gene Association in Pattern Sets | HTML | R Script |
| Reference Manual | ||
| NEWS | Text |
Download
Follow the installation instructions to use this package in your R session.
| Source package | CoGAPS_3.32.0.tar.gz |
| Windows binary (x86_64) | CoGAPS_3.32.0.zip |
| macOS binary (arm64) | CoGAPS_3.32.0.tgz |
| macOS binary (x86_64) | CoGAPS_3.32.0.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/CoGAPS |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/CoGAPS |
| Package Downloads Report | Download Stats |
Dependencies
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
Suggests: testthat, knitr, rmarkdown, BiocStyle, SeuratObject, BiocFileCache, xml2
Reverse dependencies
Suggests Me (2): projectR, SpaceMarkers