title: Bayesian prediction of tissue-regulated splicing using RNA sequence and cellular context.
abstract: BACKGROUND
  Alternative splicing is a major contributor to cellular diversity in mammalian tissues and relates to many human diseases. An important goal in understanding this phenomenon is to infer a 'splicing code' that predicts how splicing is regulated in different cell types by features derived from RNA, DNA and epigenetic modifiers.
  
  
  METHODS
  We formulate the assembly of a splicing code as a problem of statistical inference and introduce a Bayesian method that uses an adaptively selected number of hidden variables to combine subgroups of features into a network, allows different tissues to share feature subgroups and uses a Gibbs sampler to hedge predictions and ascertain the statistical significance of identified features.
  
  
  RESULTS
  Using data for 3665 cassette exons, 1014 RNA features and 4 tissue types derived from 27 mouse tissues (http://genes.toronto.edu/wasp), we benchmarked several methods. Our method outperforms all others, and achieves relative improvements of 52% in splicing code quality and up to 22% in classification error, compared with the state of the art. Novel combinations of regulatory features and novel combinations of tissues that share feature subgroups were identified using our method.
  
  
  BACKGROUND
  frey@psi.toronto.edu
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Department of Electrical and Computer Engineering, University of Toronto, Toronto, Canada.
authors.forename: Hui Yuan
authors.initials: HY
authors.lastname: Xiong
authors.forename: Yoseph
authors.initials: Y
authors.lastname: Barash
authors.forename: Brendan J
authors.initials: BJ
authors.lastname: Frey
mesh_terms: D000465:Algorithms; D017398:Alternative Splicing / Q000235:genetics*; D000818:Animals; D001483:Base Sequence; D001499:Bayes Theorem; D005091:Exons; D015870:Gene Expression; D005786:Gene Expression Regulation; D006801:Humans; D051379:Mice; D008957:Models, Genetic; D012313:RNA / Q000235:genetics*; D059368:RNA Isoforms / Q000235:genetics*; D012326:RNA Splicing; D014158:Transcription, Genetic
chemical_list: D059368:RNA Isoforms; D012313:RNA