title: R/EBcoexpress: an empirical Bayesian framework for discovering differential co-expression.
abstract: 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.
  
  
  METHODS
  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
authors.affiliation: Statistics and Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706, USA. DrJADawson@hotmail.com
authors.forename: John A
authors.initials: JA
authors.lastname: Dawson
authors.forename: Shuyun
authors.initials: S
authors.lastname: Ye
authors.forename: Christina
authors.initials: C
authors.lastname: Kendziorski
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D019295:Computational Biology / Q000379:methods; D015870:Gene Expression; D011381:Programming Languages; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software