CoGAPS-package: CoGAPS: Coordinated Gene Activity in Pattern Sets
In CoGAPS: Coordinated Gene Activity in Pattern Sets
Description
Author(s)
References
Description
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.
Package: CoGAPS
Type: Package
Version: 2.99.0
Date: 2018-01-24
License: LGPL
Author(s)
Maintainer: Elana J. Fertig ejfertig@jhmi.edu,
Michael F. Ochs ochsm@tcnj.edu
References
Fertig EJ, Ding J, Favorov AV, Parmigiani G, Ochs MF.
CoGAPS: an R/C++ package to identify patterns and biological
process activity in transcriptomic data.
Bioinformatics. 2010 Nov 1;26(21):2792-3
CoGAPS documentation built on Nov. 8, 2020, 5:02 p.m.
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Description Author(s) References
Description
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.
| Package: | CoGAPS |
| Type: | Package |
| Version: | 2.99.0 |
| Date: | 2018-01-24 |
| License: | LGPL |
Author(s)
Maintainer: Elana J. Fertig ejfertig@jhmi.edu, Michael F. Ochs ochsm@tcnj.edu
References
Fertig EJ, Ding J, Favorov AV, Parmigiani G, Ochs MF. CoGAPS: an R/C++ package to identify patterns and biological process activity in transcriptomic data. Bioinformatics. 2010 Nov 1;26(21):2792-3
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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