Identification of consensus patterns in unaligned dna and protein sequences: a large-deviation stati

Using log-likelihood statistics to compare sequence alignments, we have been able to determine alignments from multiple, unaligned, functionally related, DNA (Stormo and Hartzell. 1989. Proc. Natl. Acad. Sci. USA 86, 1183–1187; Hertz et al. 1990. Comput. Appl. Biosci. 6, 81–92) and protein sequences. In this paper, we reanalyze DNA sequences that bind the E. coli repressor LexA to demonstrate the ability of our scoring scheme to identify patterns when each sequence can contain zero or more binding sites. The scoring formula we have used previously does not allow for insertions and deletions in the alignments. In this paper, we use large-deviation statistics to extend the scoring formula to allow for insertions and deletions. The insertion-deletion penalty of this scoring scheme depends exclusively on the observed alignment rather than on previous observations or the user’s intuition. We also describe the close relationship between our formulas and hidden markov models. Finally, we present results of applying this new scoring formula to align a set of E. coli promoter DNA sequences.

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