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R/EBcoexpress: an empirical Bayesian framework for discovering differential co-expression. | LitMetric

R/EBcoexpress: an empirical Bayesian framework for discovering differential co-expression.

Bioinformatics

Statistics and Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706, USA.

Published: July 2012

AI Article Synopsis

Article Abstract

Unlabelled: R/EBcoexpress implements the approach of Dawson and Kendziorski using R, a freely available, open source statistical programming language. The approach identifies differential co-expression (DC) by examining the correlations among gene pairs using an empirical Bayesian approach, producing a false discovery rate controlled list of DC pairs. This interrogation of DC gene pairs complements but is distinct from differential expression analyses, under the general goal of understanding differential regulation across biological conditions.

Availability And Implementation: R/EBcoexpress is freely available and hosted on Bioconductor; a source file and vignette may be found at http://www.bioconductor.org/packages/release/bioc/html/EBcoexpress.html

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3492001PMC
http://dx.doi.org/10.1093/bioinformatics/bts268DOI Listing

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