Title :
An Integer Programming Formulation of the Parsimonious Loss of Heterozygosity Problem
Author :
Catanzaro, Daniele ; Labbe, Mathieu ; Halldorsson, Bjarni V.
Author_Institution :
Comput. Sci. Dept., Univ. Libre de Bruxelles (ULB), Brussels, Belgium
Abstract :
A loss of heterozygosity (LOH) event occurs when, by the laws of Mendelian inheritance, an individual should be heterozygote at a given site but, due to a deletion polymorphism, is not. Deletions play an important role in human disease and their detection could provide fundamental insights for the development of new diagnostics and treatments. In this paper, we investigate the parsimonious loss of heterozygosity problem (PLOHP), i.e., the problem of partitioning suspected polymorphisms from a set of individuals into a minimum number of deletion areas. Specifically, we generalize Halldórsson et al.´s work by providing a more general formulation of the PLOHP and by showing how one can incorporate different recombination rates and prior knowledge about the locations of deletions. Moreover, we show that the PLOHP can be formulated as a specific version of the clique partition problem in a particular class of graphs called undirected catch-point interval graphs and we prove its general NP-hardness. Finally, we provide a state-of-the-art integer programming (IP) formulation and strengthening valid inequalities to exactly solve real instances of the PLOHP containing up to 9,000 individuals and 3,000 SNPs. Our results give perspectives on the mathematics of the PLOHP and suggest new directions on the development of future efficient exact solution approaches.
Keywords :
computational complexity; diseases; genetics; genomics; graph theory; integer programming; medical computing; polymorphism; Mendelian inheritance laws; PLOHP can; PLOHP mathematics; SNP; clique partition problem; deletion area minimum number; deletion locations; deletion polymorphism; diagnostic development; exact solution approach; general NP-hardness; heterozygote; human disease; integer programming formulation; loss of heterozygosity event; parsimonious loss of heterozygosity problem; prior knowledge; real instances; recombination rates; suspected polymorphism partitioning; treatment development; undirected catch-point interval graphs; valid inequality strengthening; Bioinformatics; Computational biology; DNA; Genomics; Human factors; Linear programming; Clique partitioning; combinatorial optimization; computational biology; genome-wide association studies; loss of heterozygosity; mixed integer programming; polymatroid rank functions; single nucleotide polymorphism; submodular functions; undirected catch-point interval graph;
Journal_Title :
Computational Biology and Bioinformatics, IEEE/ACM Transactions on
DOI :
10.1109/TCBB.2012.138