An Approximation Algorithm for Haplotype Inference by Maximum Parsimony

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چکیده

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Haplotype inference by maximum parsimony

MOTIVATION Haplotypes have been attracting increasing attention because of their importance in analysis of many fine-scale molecular-genetics data. Since direct sequencing of haplotype via experimental methods is both time-consuming and expensive, haplotype inference methods that infer haplotypes based on genotype samples become attractive alternatives. RESULTS (1) We design and implement an ...

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An Approximation Algorithm for Haplotype Inference by Maximum Parsimony (Class note)

This paper studies haplotype inference by maximum parsimony using population data. We define the optimal haplotype inference (OHI) problem as given a set of genotypes and a set of related haplotypes, find a minimum subset of haplotypes that can resolve all the genotypes. We prove that OHI is NP-hard and can be formulated as an integer quadratic programming (IQP) problem. To solve the IQP proble...

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Genetic Master-Slave Algorithm for Haplotype Inference by Parsimony

Haplotype Inference is a challenging problem in bioinformatics that consists in inferring the basic genetic constitution of diploid organisms on the basis of their genotypes. This piece of information makes it possible to perform association studies for the genetic variants involved in multifactorial diseases and the individual responses to therapeutic agents. A notable approach to the problem ...

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Haplotype Inference by Pure Parsimony via Genetic Algorithm

Haplotypes are specially important in the study of complex diseases since they contain more information about gene alleles than genotype data. However, getting haplotype data via experiments methods is techniquely difficult and expensive. Thus, haplotype inference through computational methods is practical and attractive. There are several models for inferrings haplotype from population genotyp...

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Toward an algebraic understanding of haplotype inference by pure parsimony.

Haplotype inference by pure parsimony (HIPP) is known to be NP-Hard. Despite this, many algorithms successfully solve HIPP instances on simulated and real data. In this paper, we explore the connection between algebraic rank and the HIPP problem, to help identify easy and hard instances of the problem. The rank of the input matrix is known to be a lower bound on the size an optimal HIPP solutio...

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ژورنال

عنوان ژورنال: Journal of Computational Biology

سال: 2005

ISSN: 1066-5277,1557-8666

DOI: 10.1089/cmb.2005.12.1261