title: Scanning sequences after Gibbs sampling to find multiple occurrences of functional elements.
abstract: BACKGROUND
  Many DNA regulatory elements occur as multiple instances within a target promoter. Gibbs sampling programs for finding DNA regulatory elements de novo can be prohibitively slow in locating all instances of such an element in a sequence set.
  
  
  RESULTS
  We describe an improvement to the A-GLAM computer program, which predicts regulatory elements within DNA sequences with Gibbs sampling. The improvement adds an optional "scanning step" after Gibbs sampling. Gibbs sampling produces a position specific scoring matrix (PSSM). The new scanning step resembles an iterative PSI-BLAST search based on the PSSM. First, it assigns an "individual score" to each subsequence of appropriate length within the input sequences using the initial PSSM. Second, it computes an E-value from each individual score, to assess the agreement between the corresponding subsequence and the PSSM. Third, it permits subsequences with E-values falling below a threshold to contribute to the underlying PSSM, which is then updated using the Bayesian calculus. A-GLAM iterates its scanning step to convergence, at which point no new subsequences contribute to the PSSM. After convergence, A-GLAM reports predicted regulatory elements within each sequence in order of increasing E-values, so users have a statistical evaluation of the predicted elements in a convenient presentation. Thus, although the Gibbs sampling step in A-GLAM finds at most one regulatory element per input sequence, the scanning step can now rapidly locate further instances of the element in each sequence.
  
  
  CONCLUSIONS
  Datasets from experiments determining the binding sites of transcription factors were used to evaluate the improvement to A-GLAM. Typically, the datasets included several sequences containing multiple instances of a regulatory motif. The improvements to A-GLAM permitted it to predict the multiple instances.
authors.affiliation: Computational Biology Branch, National Center for Biotechnology Information National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, MSC 6075 Bethesda, MD 20894-6075, USA. tharakar@ncbi.nlm.nih.gov
authors.forename: Kannan
authors.initials: K
authors.lastname: Tharakaraman
authors.forename: Leonardo
authors.initials: L
authors.lastname: Mariño-Ramírez
authors.forename: Sergey L
authors.initials: SL
authors.lastname: Sheetlin
authors.forename: David
authors.initials: D
authors.lastname: Landsman
authors.forename: John L
authors.initials: JL
authors.lastname: Spouge
mesh_terms: D000818:Animals; D001483:Base Sequence; D004330:Drosophila / Q000235:genetics; D008390:Markov Chains; D008969:Molecular Sequence Data; D009010:Monte Carlo Method; D050436:Regulatory Elements, Transcriptional / Q000235:genetics*; D012440:Saccharomyces / Q000235:genetics; D016415:Sequence Alignment / Q000379:methods; D017422:Sequence Analysis, DNA / Q000379:methods*