title: Efficient large-scale sequence comparison by locality-sensitive hashing.
abstract: BACKGROUND
  Comparison of multimegabase genomic DNA sequences is a popular technique for finding and annotating conserved genome features. Performing such comparisons entails finding many short local alignments between sequences up to tens of megabases in length. To process such long sequences efficiently, existing algorithms find alignments by expanding around short runs of matching bases with no substitutions or other differences. Unfortunately, exact matches that are short enough to occur often in significant alignments also occur frequently by chance in the background sequence. Thus, these algorithms must trade off between efficiency and sensitivity to features without long exact matches.
  
  
  RESULTS
  We introduce a new algorithm, LSH-ALL-PAIRS, to find ungapped local alignments in genomic sequence with up to a specified fraction of substitutions. The length and substitution rate of these alignments can be chosen so that they appear frequently in significant similarities yet still remain rare in the background sequence. The algorithm finds ungapped alignments efficiently using a randomized search technique, locality-sensitive hashing. We have found LSH-ALL-PAIRS to be both efficient and sensitive for finding local similarities with as little as 63% identity in mammalian genomic sequences up to tens of megabases in length
authors.affiliation: Department of Computer Science and Engineering, University of Washington, Seattle, WA 98195-2350, USA. jbuhler@cs.washington.edu
authors.forename: J
authors.initials: J
authors.lastname: Buhler
mesh_terms: D000465:Algorithms; D000818:Animals; D002892:Chromosomes, Human, Pair 22 / Q000235:genetics; D019295:Computational Biology; D004247:DNA / Q000235:genetics; D016208:Databases, Factual; D005914:Globins / Q000235:genetics; D006801:Humans; D019901:Locus Control Region; D051379:Mice; D016693:Receptors, Antigen, T-Cell, alpha-beta / Q000235:genetics; D016415:Sequence Alignment / Q000706:statistics & numerical data*; D012984:Software
chemical_list: D016693:Receptors, Antigen, T-Cell, alpha-beta; D005914:Globins; D004247:DNA