CoGAPS: An R/C++ package to identify patterns and biological process activity in transcriptomic data

Elana J. Fertig, Jie Ding, Alexander V. Favorov, Giovanni Parmigiani, Michael F. Ochs

Research output: Contribution to journalArticlepeer-review

Abstract

Summary: Coordinated 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.

Original languageEnglish (US)
Article numberbtq503
Pages (from-to)2792-2793
Number of pages2
JournalBioinformatics
Volume26
Issue number21
DOIs
StatePublished - Nov 2010

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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