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Bioinformatics 2005 21(Suppl 1):i344-i350; doi:10.1093/bioinformatics/bti1042
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© The Author 2005. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions{at}oupjournals.org

Statistics of local multiple alignments

Amol Prakash * and Martin Tompa

Department of Computer Science and Engineering Box 352350 University of Washington Seattle, WA 98195-2350, USA

*To whom correspondence should be addressed.

Summary: BLAST statistics have been shown to be extremely useful for searching for significant similarity hits, for amino acid and nucleotide sequences. Although these statistics are well understood for pairwise comparisons, there has been little success developing statistical scores for multiple alignments. In particular, there is no score for multiple alignment that is well founded and treated as a standard. We extend the BLAST theory to multiple alignments. Following some simple assumptions, we present and justify a significance score for multiple segments of a local multiple alignment. We demonstrate its usefulness in distinguishing high and moderate quality multiple alignments from low quality ones, with supporting experiments on orthologous vertebrate promoter sequences.

Contact: amol{at}cs.washington.edu

Received on January 15, 2005; accepted on March 27, 2005

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