Literature DB >> 22595207

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

John A Dawson1, Shuyun Ye, Christina Kendziorski.   

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

Mesh:

Year:  2012        PMID: 22595207      PMCID: PMC3492001          DOI: 10.1093/bioinformatics/bts268

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  10 in total

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  10 in total
  22 in total

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10.  Cluster and propensity based approximation of a network.

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