Solving haplotyping inference parsimony problem using a new basic polynomial formulation

Solving haplotyping inference parsimony problem using a new basic polynomial formulation

Similarity and diversity among individuals of the same species are expressed in small DNA variations called Single Nucleotide Polymorphism. The knowledge of SNP phase gives rise to the haplotyping problem that in the parsimonious version states to infer the minimum number of haplotypes from a given set of genotype data. ILP technique represents a good resolution strategy for this interesting co...

On Parsimony Haplotyping

The pure parsimony haplotyping problem: overview and computational advances

Haplotyping estimation from aligned Single Nucleotide Polymorphism (SNP) fragments has attracted more and more attention in the recent years due to its importance in analysis of many fine-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 literatu...

Complete Parsimony Haplotype Inference Problem and Algorithms

Haplotype inference by pure parsimony (HIPP) is a wellknown paradigm for haplotype inference. In order to assess the biological significance of this paradigm, we generalize the problem of HIPP to the problem of finding all optimal solutions, which we call complete HIPP. We study intrinsic haplotype features, such as backbone haplotypes and fat genotypes as well as equal columns and decomposabil...

Extended Islands of Tractability for Parsimony Haplotyping

Parsimony haplotyping is the problem of finding a smallest size set of haplotypes that can explain a given set of genotypes. The problem is NP-hard, and many heuristic and approximation algorithms as well as polynomial-time solvable special cases have been discovered. We propose improved fixed-parameter tractability results with respect to the parameter “size of the target haplotype set” k by p...