README.md
In CoGAPS/CoGAPS: Coordinated Gene Activity in Pattern Sets
CoGAPS
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.
Installing CoGAPS
Via Bioconductor:
install.packages("BiocManager")
BiocManager::install("FertigLab/CoGAPS")
The most up-to-date version of CoGAPS can be installed directly from the
FertigLab Github Repository:
devtools::install_github("FertigLab/CoGAPS")
Using CoGAPS
Follow the vignette here and available as static html here
CoGAPS/CoGAPS documentation built on April 12, 2024, 3:12 a.m.
R Package Documentation
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CoGAPS
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.
Installing CoGAPS
Via Bioconductor:
install.packages("BiocManager")
BiocManager::install("FertigLab/CoGAPS")
The most up-to-date version of CoGAPS can be installed directly from the FertigLab Github Repository:
devtools::install_github("FertigLab/CoGAPS")
Using CoGAPS
Follow the vignette here and available as static html here
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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