Statistics of local multiple alignments
Open Access
- 1 June 2005
- journal article
- research article
- Published by Oxford University Press (OUP) in Bioinformatics
- Vol. 21 (Suppl 1) , i344-i350
- https://doi.org/10.1093/bioinformatics/bti1042
Abstract
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@cs.washington.eduKeywords
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