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Related Experiment Videos

Increased coverage obtained by combination of methods for protein sequence database searching.

Caleb Webber1, Geoffrey J Barton

  • 1EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, England, UK.

Bioinformatics (Oxford, England)
|July 23, 2003
PubMed
Summary

Combining sequence alignment methods improves biological sequence relationship detection. The intersection of SSEARCH and GSRCH62 methods yielded the best performance, significantly increasing true positive findings.

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Area of Science:

  • Bioinformatics
  • Computational Biology

Background:

  • Pairwise sequence alignment is crucial for identifying biological sequence relationships.
  • Genome annotation often relies on the agreement of multiple alignment methods.

Purpose of the Study:

  • To assess the benefits of combining different sequence alignment search methods.
  • To compare the performance of dynamic programming and heuristic algorithms.

Main Methods:

  • Compared seven pairwise alignment methods: three local dynamic programming (PRSS, SSEARCH, SCANPS), two global dynamic programming (GSRCH, AMPS), and two heuristic (BLAST, FASTA).
  • Evaluated methods individually and in pairwise combinations (intersection and union) at equal p-value cutoffs.

Main Results:

  • SCANPS and SSEARCH showed superior coverage individually.

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  • Combining BLAST (p-value) and FASTA significantly improved coverage.
  • The intersection of SSEARCH and GSRCH62 provided the best overall performance, with a 12.4% increase in true positives at five false positives.

    • Conclusions:

    • Combining sequence alignment methods can enhance detection of biological sequence relationships.
    • The intersection of specific dynamic programming methods (SSEARCH and GSRCH62) offers significant advantages over individual methods.