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Phylogeny- and Parsimony-Based Haplotype Inference with Constraints

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Combinatorial Pattern Matching (CPM 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6129))

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Abstract

Haplotyping, also known as haplotype phase prediction, is the problem of predicting likely haplotypes based on genotype data. One fast computational haplotyping method is based on an evolutionary model where a perfect phylogenetic tree is sought that explains the observed data. In their cpm 2009 paper, Fellows et al. studied an extension of this approach that incorporates prior knowledge in the form of a set of candidate haplotypes from which the right haplotypes must be chosen. While this approach may help to increase the accuracy of haplotyping methods, it was conjectured that the resulting formal problem constrained perfect phylogeny haplotyping might be NP-complete. In the present paper we present a polynomial-time algorithm for it. Our algorithmic ideas also yield new fixed-parameter algorithms for related haplotyping problems based on the maximum parsimony assumption.

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Authors and Affiliations

  1. Institut für Theoretische Informatik, Universität zu Lübeck, 23538, Lübeck, Germany

    Michael Elberfeld & Till Tantau

Authors
  1. Michael Elberfeld
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  2. Till Tantau
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Editors and Affiliations

  1. Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA, and Bar-Ilan University, 52900, Ramat-Gan, Israel

    Amihood Amir

  2. IBM T.J. Watson Research Center, Yorktown Heights, NY, USA

    Laxmi Parida

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Elberfeld, M., Tantau, T. (2010). Phylogeny- and Parsimony-Based Haplotype Inference with Constraints. In: Amir, A., Parida, L. (eds) Combinatorial Pattern Matching. CPM 2010. Lecture Notes in Computer Science, vol 6129. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13509-5_17

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  • DOI: https://doi.org/10.1007/978-3-642-13509-5_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13508-8

  • Online ISBN: 978-3-642-13509-5

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