A parsimonious tree-grow method for haplotype inference.
BACKGROUND
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.


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


BACKGROUND
chen@elec.osaka-sandai.ac.jp


BACKGROUND
Supporting materials is available from http://zhangroup.aporc.org/bioinfo/ptg/bti572supplementary.pdf
Beijing Materials Institute, Beijing 101149, China.
Zhenping
Z
Li
Wenfeng
W
Zhou
Xiang-Sun
XS
Zhang
Luonan
L
Chen
D000465:Algorithms; D001483:Base Sequence; D002874:Chromosome Mapping / Q000379:methods*; D006239:Haplotypes / Q000235:genetics*; D008957:Models, Genetic; D008969:Molecular Sequence Data; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*; D016415:Sequence Alignment / Q000379:methods*; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software