A Class Representative Model for Pure Parsimony Haplotyping under Uncertain Data

A Class Representative Model for Pure Parsimony Haplotyping under Uncertain Data

The Pure Parsimony Haplotyping (PPH) problem is a NP-hard combinatorial optimization problem that consists of finding the minimum number of haplotypes necessary to explain a given set of genotypes. PPH has attracted more and more attention in recent years due to its importance in analysis of many fine-scale genetic data. Its application fields range from mapping complex disease genes to inferri...

A Class Representative Model for Pure Parsimony Haplotyping

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...

A Column Generation Approach for Pure Parsimony Haplotyping

The knowledge of nucleotides chains that compose the double DNA chain of an individual has a relevant role in detecting diseases and studying populations. However, determining experimentally the single nucleotides chains that, paired, form a certain portion of the DNA is expensive and time-consuming. Mathematical programming approaches have been proposed instead, e.g. formulating the Haplotype ...

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...

On Parsimony Haplotyping