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Bioinformatics Advance Access originally published online on July 7, 2005
Bioinformatics 2005 21(17):3475-3481; doi:10.1093/bioinformatics/bti572
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© The Author 2005. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions{at}oupjournals.org

A parsimonious tree-grow method for haplotype inference

Zhenping Li 1,2, Wenfeng Zhou 1, Xiang-Sun Zhang 2 and Luonan Chen 3,*

1Beijing Materials Institute Beijing 101149, China
2Chinese Academy of Sciences Beijing 100080, China
3Osaka Sangyo University Osaka 574-8530, Japan

*To whom correspondence should be addressed.

Motivation: Haplotype information has become increasingly important in analyzing fine-scale molecular genetics data, such as disease genes mapping and drug design. Parsimony haplotyping is one of haplotyping problems belonging to NP-hard class.

Results: In this paper, we aim to develop a novel algorithm for the haplotype inference problem with the parsimony criterion, based on a parsimonious tree-grow method (PTG). PTG is a heuristic algorithm that can find the minimum number of distinct haplotypes based on the criterion of keeping all genotypes resolved during tree-grow process. In addition, a block-partitioning method is also proposed to improve the computational efficiency. We show that the proposed approach is not only effective with a high accuracy, but also very efficient with the computational complexity in the order of O(m2n) time for n single nucleotide polymorphism sites in m individual genotypes.

Availability: The software is available upon request from the authors, or from http://zhangroup.aporc.org/bioinfo/ptg/

Contact: chen{at}elec.osaka-sandai.ac.jp

Supplementary information: Supporting materials is available from http://zhangroup.aporc.org/bioinfo/ptg/bti572supplementary.pdf

Received on May 24, 2005; revised on June 30, 2005; accepted on July 4, 2005

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