A general framework for local pairwise alignment statistics with gaps

  • Authors:

  • Pasi Rastas

  • Affiliations:

  • Department of Computer Science & HIIT Basic Research Unit, University of Helsinki, Finland

  • Venue:
  • WABI'09 Proceedings of the 9th international conference on Algorithms in bioinformatics
  • Year:
  • 2009

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Abstract

We present a novel dynamic programming framework that allows one to compute tight upper bounds for the p-values of gapped local alignments in pseudo-polynomial time. Our algorithms are fast and simple and unlike most earlier solutions, require no curve fitting by sampling. Moreover, our new methods do not suffer from the so-called edge effects, a by-product of the common practice used to compute p-values. These new methods also provide a way to get into very small p-values, that are needed when comparing sequences against large databases. Based on our experiments, accurate estimates of small p-values are difficult to get by curve fitting.