Haplotype inference with pseudo-Boolean optimization

被引:10
|
作者
Graca, Ana [1 ,2 ]
Marques-Silva, Joao [3 ]
Lynce, Ines [1 ,2 ]
Oliveira, Arlindo L. [1 ,2 ]
机构
[1] Univ Tecn Lisboa, IST, Lisbon, Portugal
[2] INESC ID Lisboa, Lisbon, Portugal
[3] Univ Coll Dublin, Sch Comp Sci & Informat, Complex & Adapt Syst Lab, Dublin 2, Ireland
关键词
Haplotype inference; Pure parsimony; Pseudo-Boolean optimization; GENOTYPE DATA; PURE PARSIMONY; RECONSTRUCTION; ALGORITHMS; DIVERSITY; MODEL;
D O I
10.1007/s10479-009-0675-4
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
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.
引用
收藏
页码:137 / 162
页数:26
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