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Bioinformatics. 2014 Jan 1;30(1):127-8. doi: 10.1093/bioinformatics/btt592. Epub 2013 Oct 15.

gCMAP: user-friendly connectivity mapping with R.

Author information

1
Department of Bioinformatics and Computational Biology, Genentech Inc., South San Francisco, CA 94080, USA.

Abstract

Connections between disease phenotypes and drug effects can be made by identifying commonalities in the associated patterns of differential gene expression. Searchable databases that record the impacts of chemical or genetic perturbations on the transcriptome--here referred to as 'connectivity maps'--permit discovery of such commonalities. We describe two R packages, gCMAP and gCMAPWeb, which provide a complete framework to construct and query connectivity maps assembled from user-defined collections of differential gene expression data. Microarray or RNAseq data are processed in a standardized way, and results can be interrogated using various well-established gene set enrichment methods. The packages also feature an easy-to-deploy web application that facilitates reproducible research through automatic generation of graphical and tabular reports.

AVAILABILITY AND IMPLEMENTATION:

The gCMAP and gCMAPWeb R packages are freely available for UNIX, Windows and Mac OS X operating systems at Bioconductor (http://www.bioconductor.org).

PMID:
24132929
DOI:
10.1093/bioinformatics/btt592
[Indexed for MEDLINE]

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