A Class Representative Model for Pure Parsimony Haplotyping

被引:10
作者
Catanzaro, Daniele [1 ]
Godi, Alessandra [2 ]
Labbe, Martine [1 ]
机构
[1] Univ Libre Bruxelles, Dept Comp Sci, B-1050 Brussels, Belgium
[2] CNR, Ist Anal Sistemi & Informat, I-00185 Rome, Italy
关键词
haplotype inference; computational biology; integer programming; EXPECTATION-MAXIMIZATION ALGORITHM; INFERENCE; SEQUENCE; RECONSTRUCTION; FORMULATION;
D O I
10.1287/ijoc.1090.0333
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Haplotyping estimation from aligned single nucleotide polymorphism fragments has attracted increasing attention in recent years because of its importance in the analysis of. ne-scale genetic data. Its application fields range from mapping of complex disease genes to inferring population histories, passing through designing drugs, functional genomics, and pharmacogenetics. The literature proposes several criteria for haplotyping populations, each of them characterized by biological motivations. One of the most important haplotyping criteria is parsimony, which consists of finding the minimum number of haplotypes necessary to explain a given set of genotypes. Parsimonious haplotype estimation is an NP-hard problem for which the literature has proposed several integer programming (IP) models. Here, we describe a new polynomial-sized IP model based on the concept of class representatives, already used for the coloring problem. We propose valid inequalities to strengthen our model and show, through computational experiments, that our model outperforms the best IP models currently known in literature.
引用
收藏
页码:195 / 209
页数:15
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