Polynomial and APX-hard cases of the individual haplotyping problem

  • Authors:

  • Vineet Bafna;Sorin Istrail;Giuseppe Lancia;Romeo Rizzi

  • Affiliations:

  • Department of Computer Science and Engineering, University of California at San Diego, 9500 Gilman Drive, La Jolla, CA;Informatics Research, Celera Genomics, 45 West Gude, Rockville, MD;Dipartimento di Matematica e Informatica, Università di Udine, via delle Scienze 206, 33100 Udine, Italy;Dipartimento di Matematica, Università di Trento, via Sommarive 14, 38050 Povo, Italy

  • Venue:
  • Theoretical Computer Science - Pattern discovery in the post genome
  • Year:
  • 2005

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Abstract

SNP haplotyping problems have been the subject of extensive research in the last few years, and are one of the hottest areas of Computational Biology today. In this paper we report on our work of the last two years, whose preliminary results were presented at the European Symposium on Algorithms (Proceedings of the Annual European Symposium on Algorithms (ESA), Vol. 2161. Lecture Notes in Computer Science, Springer, 2001, pp. 182-193.) and Workshop on Algorithms in Bioinformatics (Proceedings of the Annual Workshop on Algorithms in Bioinformatics (WABI), Vol. 2452. Lecture Notes in Computer Science, Springer, 2002, pp. 29-43.). We address the problem of reconstructing two haplotypes for an individual from fragment assembly data. This problem will be called the Single individual Haplotyping Problem. On the positive side, we prove that the problem can be solved effectively for gapless data, and give practical, dynamic programming algorithms for its solution. On the negative side, we show that it is unlikely that polynomial algorithms exist, even to approximate the solution arbitrarily well, when the data contain gaps. We remark that both the gapless and gapped data arise in different real-life applications.