Self-organizing map approaches for the haplotype assembly problem

Authors:
Ling-Yun Wu;Zhenping Li;Rui-Sheng Wang;Xiang-Sun Zhang;Luonan Chen
Affiliations:
Academy of Mathematics and Systems Science, CAS, Beijing 100080, China;School of Information, Beijing Wuzi University, Beijing 101149, China;Department of Mathematics, Renmin University of China, Beijing 100872, China;Academy of Mathematics and Systems Science, CAS, Beijing 100080, China;Department of Electrical Engineering and Electronics, Osaka Sangyo University, Osaka 574-8530, Japan
Venue:
Mathematics and Computers in Simulation
Year:
2009

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Abstract

Haplotype assembly is to reconstruct a pair of haplotypes from SNP values observed in a set of individual DNA fragments. In this paper, we focus on studying minimum error correction (MEC) model for the haplotype assembly problem and explore self-organizing map (SOM) methods for this problem. Specifically, haplotype assembly by MEC is formulated into an integer linear programming model. Since the MEC problem is NP-hard and thus cannot be solved exactly within acceptable running time for large-scale instances, we investigate the ability of classical SOMs to solve the haplotype assembly problem with MEC model. Then, aiming to overcome the limits of classical SOMs, a novel SOM approach is proposed for the problem. Extensive computational experiments on both synthesized and real datasets show that the new SOM-based algorithm can efficiently reconstruct haplotype pairs in a very high accuracy under realistic parameter settings. Comparison with previous methods also confirms the superior performance of the new SOM approach.