title: Log-odds sequence logos.
abstract: BACKGROUND
  DNA and protein patterns are usefully represented by sequence logos. However, the methods for logo generation in common use lack a proper statistical basis, and are non-optimal for recognizing functionally relevant alignment columns.
  
  
  RESULTS
  We redefine the information at a logo position as a per-observation multiple alignment log-odds score. Such scores are positive or negative, depending on whether a column's observations are better explained as arising from relatedness or chance. Within this framework, we propose distinct normalized maximum likelihood and Bayesian measures of column information. We illustrate these measures on High Mobility Group B (HMGB) box proteins and a dataset of enzyme alignments. Particularly in the context of protein alignments, our measures improve the discrimination of biologically relevant positions.
  
  
  METHODS
  Our new measures are implemented in an open-source Web-based logo generation program, which is available at http://www.ncbi.nlm.nih.gov/CBBresearch/Yu/logoddslogo/index.html. A stand-alone version of the program is also available from this site.
  
  
  BACKGROUND
  altschul@ncbi.nlm.nih.gov
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, Center for Human Genetics Research and Department of Biomedical Informatics, Vanderbilt University, Nashville, TN 37232, USA.
authors.forename: Yi-Kuo
authors.initials: YK
authors.lastname: Yu
authors.affiliation: National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, Center for Human Genetics Research and Department of Biomedical Informatics, Vanderbilt University, Nashville, TN 37232, USA National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, Center for Human Genetics Research and Department of Biomedical Informatics, Vanderbilt University, Nashville, TN 37232, USA.
authors.forename: John A
authors.initials: JA
authors.lastname: Capra
authors.affiliation: National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, Center for Human Genetics Research and Department of Biomedical Informatics, Vanderbilt University, Nashville, TN 37232, USA.
authors.forename: Aleksandar
authors.initials: A
authors.lastname: Stojmirović
authors.affiliation: National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, Center for Human Genetics Research and Department of Biomedical Informatics, Vanderbilt University, Nashville, TN 37232, USA.
authors.forename: David
authors.initials: D
authors.lastname: Landsman
authors.affiliation: National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, Center for Human Genetics Research and Department of Biomedical Informatics, Vanderbilt University, Nashville, TN 37232, USA.
authors.forename: Stephen F
authors.initials: SF
authors.lastname: Altschul
mesh_terms: D000595:Amino Acid Sequence; D001499:Bayes Theorem; D006801:Humans; D058977:Molecular Sequence Annotation; D008969:Molecular Sequence Data; D056510:Position-Specific Scoring Matrices; D016415:Sequence Alignment / Q000379:methods*; D017422:Sequence Analysis, DNA / Q000379:methods*; D020539:Sequence Analysis, Protein / Q000379:methods*; D017386:Sequence Homology, Amino Acid; D012984:Software