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Bioinformatics. 2010 Nov 1;26(21):2792-3. doi: 10.1093/bioinformatics/btq503. Epub 2010 Sep 1.

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

Author information

1
Department of Oncology and Division of Oncology, Biostatistics and Bioinformatics, Sidney Kimmel Comprehensive Cancer Center, School of Medicine, Johns Hopkins University, Baltimore, MD 21205, USA. ejfertig@jhmi.edu

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.

AVAILABILITY:

The R package CoGAPS and the C++ package GAPS-JAGS are provided open source under the GNU Lesser Public License (GLPL) with a users manual containing installation and operating instructions. CoGAPS is available through Bioconductor and depends on the rjags package available through CRAN to interface CoGAPS with GAPS-JAGS. URL: http://www.cancerbiostats.onc.jhmi.edu/cogaps.cfm .

PMID:
20810601
PMCID:
PMC3025742
DOI:
10.1093/bioinformatics/btq503
[Indexed for MEDLINE]
Free PMC Article

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