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A Hidden Markov Technique for Haplotype Reconstruction

  • Pasi Rastas
  • Mikko Koivisto
  • Heikki Mannila
  • Esko Ukkonen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3692)

Abstract

We give a new algorithm for the genotype phasing problem. Our solution is based on a hidden Markov model for haplotypes. The model has a uniform structure, unlike most solutions proposed so far that model recombinations using haplotype blocks. In our model, the haplotypes can be seen as a result of iterated recombinations applied on a few founder haplotypes. We find maximum likelihood model of this type by using the EM algorithm. We show how to solve the subtleties of the EM algorithm that arise when genotypes are generated using a haplotype model. We compare our method to the well-known currently available algorithms (phase, hap, gerbil) using some standard and new datasets. Our algorithm is relatively fast and gives results that are always best or second best among the methods compared.

Keywords

Hide Markov Model Haplotype Block Emission Probability Hide Data Haplotype Inference 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Pasi Rastas
    • 1
  • Mikko Koivisto
    • 1
  • Heikki Mannila
    • 1
  • Esko Ukkonen
    • 1
  1. 1.Department of Computer Science & HIIT Basic Research UnitUniversity of HelsinkiFinland

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