title: Epigenetic priors for identifying active transcription factor binding sites.
abstract: BACKGROUND
  Accurate knowledge of the genome-wide binding of transcription factors in a particular cell type or under a particular condition is necessary for understanding transcriptional regulation. Using epigenetic data such as histone modification and DNase I, accessibility data has been shown to improve motif-based in silico methods for predicting such binding, but this approach has not yet been fully explored.
  
  
  RESULTS
  We describe a probabilistic method for combining one or more tracks of epigenetic data with a standard DNA sequence motif model to improve our ability to identify active transcription factor binding sites (TFBSs). We convert each data type into a position-specific probabilistic prior and combine these priors with a traditional probabilistic motif model to compute a log-posterior odds score. Our experiments, using histone modifications H3K4me1, H3K4me3, H3K9ac and H3K27ac, as well as DNase I sensitivity, show conclusively that the log-posterior odds score consistently outperforms a simple binary filter based on the same data. We also show that our approach performs competitively with a more complex method, CENTIPEDE, and suggest that the relative simplicity of the log-posterior odds scoring method makes it an appealing and very general method for identifying functional TFBSs on the basis of DNA and epigenetic evidence.
  
  
  METHODS
  FIMO, part of the MEME Suite software toolkit, now supports log-posterior odds scoring using position-specific priors for motif search. A web server and source code are available at http://meme.nbcr.net. Utilities for creating priors are at http://research.imb.uq.edu.au/t.bailey/SD/Cuellar2011.
  
  
  BACKGROUND
  t.bailey@uq.edu.au
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Institute for Molecular Bioscience, The University of Queensland, Brisbane QLD 4072, Australia.
authors.forename: Gabriel
authors.initials: G
authors.lastname: Cuellar-Partida
authors.forename: Fabian A
authors.initials: FA
authors.lastname: Buske
authors.forename: Robert C
authors.initials: RC
authors.lastname: McLeay
authors.forename: Tom
authors.initials: T
authors.lastname: Whitington
authors.forename: William Stafford
authors.initials: WS
authors.lastname: Noble
authors.forename: Timothy L
authors.initials: TL
authors.lastname: Bailey
mesh_terms: D000818:Animals; D004247:DNA / Q000737:chemistry / Q000378:metabolism; D057890:Epigenomics; D005786:Gene Expression Regulation; D042421:Histone Code; D006801:Humans; D015233:Models, Statistical; D059372:Nucleotide Motifs; D017422:Sequence Analysis, DNA; D012984:Software; D014157:Transcription Factors / Q000737:chemistry / Q000378:metabolism*
chemical_list: D014157:Transcription Factors; D004247:DNA
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