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 b...

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Bibliographic Details
Published inBioinformatics Vol. 19; no. 14; pp. 1773 - 1780
Main Authors Wang, Lusheng, Xu, Ying
Format Journal Article
LanguageEnglish
Published England Oxford University Press 22.09.2003
Oxford Publishing Limited (England)
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Summary: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 algorithm for an important computational model of haplotype inference that has been suggested before in several places. The model finds a set of minimum number of haplotypes that explains the genotype samples. (2) Strong supports of this computational model are given based on the computational results on both real data and simulation data. (3) We also did some comparative study to show the strength and weakness of this computational model using our program. Availability: The software HAPAR is free for non-commercial uses. Available upon request (lwang@cs.cityu.edu.hk).
Bibliography:istex:381DA544DCE70B581D613E6CB9D4EAE21A9C1EE6
local:btg239
Contact: http://lwang@cs.citu.edu.hk
ark:/67375/HXZ-G5HJ4GXM-5
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ISSN:1367-4803
1460-2059
1367-4811
DOI:10.1093/bioinformatics/btg239