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dc.contributor.authorFertig, Elana J.
dc.contributor.authorDing, Jie
dc.contributor.authorFavorov, Alexander V.
dc.contributor.authorParmigiani, Giovanni
dc.contributor.authorOchs, Michael F.
dc.date.accessioned2018-04-28T15:17:12Z
dc.date.available2018-04-28T15:17:12Z
dc.date.issued2010
dc.identifier.citationFertig, E., Favorov, A., Ochs, M., Ding, J., & Parmigiani, G. (2010). CoGAPS: An R/C++ package to identify patterns and biological process activity in transcriptomic data. Bioinformatics, 26(21), 2792-2793.en_US
dc.identifier.urihttps://dx.doi.org/10.1093/bioinformatics/btq503
dc.descriptionFile not available for download due to copyright restrictionsen_US
dc.description.abstractCoordinated Gene Activity in Pattern Sets (CoGAPS) provides an integrated package for isolating gene expression driven by a biological process, enhancing inference of biological processes from transcriptomic data. CoGAPS improves on other enrichment measurement methods by combining a Markov chain Monte Carlo (MCMC) matrix factorization algorithm (GAPS) with a threshold-independent statistic inferring activity on gene sets. The software is provided as open source C++ code built on top of JAGS software with an R interface.en_US
dc.language.isoen_USen_US
dc.publisherOxford University Pressen_US
dc.titleCoGAPS: an R/C++ package to identify patterns and biological process activity in transcriptomic dataen_US
dc.typeArticleen_US
dc.typeTexten_US
prism.publicationNameBioinformatics
prism.volume26
prism.issueIdentifier21
prism.publicationDate2010
prism.startingPage2792
prism.endingPage2793
dc.identifier.handlehttps://dr.tcnj.edu/handle/2900/2316


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