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Haplotype inference with pseudo-Boolean optimization

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Abstract

The fast development of sequencing techniques in the recent past has required an urgent development of efficient and accurate haplotype inference tools. Besides being a crucial issue in genetics, haplotype inference is also a challenging computational problem. Among others, pure parsimony is a viable modeling approach to solve the problem of haplotype inference and also an interesting NP-hard problem in itself. Recently, the introduction of SAT-based methods, including pseudo-Boolean optimization (PBO) methods, has produced very efficient solvers. This paper provides a detailed description of RPoly, a PBO approach for the haplotype inference by pure parsimony (HIPP) problem. Moreover, an extensive evaluation of existent HIPP solvers, on a comprehensive set of instances, confirms that RPoly is currently the most efficient and robust HIPP approach.

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Authors and Affiliations

  1. Instituto Superior Técnico (IST), Technical University of Lisbon and INESC-ID Lisboa, Lisbon, Portugal

    Ana Graça, Inês Lynce & Arlindo L. Oliveira

  2. Complex and Adaptive Systems Lab, School of Computer Science and Informatics, University College Dublin, Dublin, Ireland

    João Marques-Silva

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  1. Ana Graça
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  2. João Marques-Silva
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  3. Inês Lynce
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  4. Arlindo L. Oliveira
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Correspondence to Ana Graça.

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Graça, A., Marques-Silva, J., Lynce, I. et al. Haplotype inference with pseudo-Boolean optimization. Ann Oper Res 184, 137–162 (2011). https://doi.org/10.1007/s10479-009-0675-4

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