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In 2003, Gusfield introduced the Haplotype Inference by Pure Parsimony (HIPP) problem and presented an integer program (IP) that quickly solved many simulated instances of the problem [1]. Although it solved well on small instances, Gusfield's IP can be of exponential size in the worst case. Several authors [2], [3] have presented polynomial-sized IPs for the problem. In this paper, we further the work on IP approaches to HIPP. We extend the existing polynomial-sized IPs by introducing several classes of valid cuts for the IP. We also present a new polynomial-sized IP formulation that is a hybrid between two existing IP formulations and inherits many of the strengths of both. Many problems that are too complex for the exponential-sized formulations can still be solved in our new formulation in a reasonable amount of time. We provide a detailed empirical comparison of these IP formulations on both simulated and real genotype sequences. Our formulation can also be extended in a variety of ways to allow errors in the input or model the structure of the population under consideration.
Computations on discrete structures, integer programming, biology and genetics, haplotype inference.
Ian M. Harrower, Daniel G. Brown, "Integer Programming Approaches to Haplotype Inference by Pure Parsimony", IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 3, no. , pp. 141-154, April-June 2006, doi:10.1109/TCBB.2006.24
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