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Bioinformatics Vol. 19 no. 14 2003
Pages 1773-1780
© 2003 Oxford University Press

Haplotype inference by maximum parsimony

Lusheng Wang 1,* and Ying Xu 2

1 Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong, People's Republic of China and 2 Department of Computer Science, Peking University, Beijing 100871, People's Republic of China

Received on December 26, 2002 ; revised on March 10, 2003 ; accepted on March 31, 2003

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{at}cs.cityu.edu.hk).

Contact: http://lwang{at}cs.citu.edu.hk

* To whom correspondence should be addressed.


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