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Bioinformatics Advance Access published online on January 10, 2006
Bioinformatics, doi:10.1093/bioinformatics/btk035
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© The Author (2006). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
Received November 4, 2005
Revised December 16, 2005
Accepted December 30, 2005

Article

A greedier approach for finding tag SNPs

Chia-Jung Chang 1, Yao-Ting Huang 1, and Kun-Mao Chao 2 *

1 Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan 106
2 Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan 106; Graduate Institute of Networking and Multimedia, National Taiwan University, Taipei, Taiwan 106

* To whom correspondence should be addressed.
Kun-Mao Chao, E-mail: kmchao{at}csie.ntu.edu.tw


  Abstract

Motivation: Recent studies have shown that a small subset of SNPs (called tag SNPs) is sufficient to capture the haplotype patterns in a high linkage disequilibrium region. To find the minimum set of tag SNPs, exact algorithms for finding the optimal solution could take exponential time. On the other hand, approximation algorithms are more efficient but may fail to find the optimal solution.

Results: We propose a hybrid method that combines the ideas of the branch-and-bound method and the greedy algorithm. This method explores larger solution space to obtain a better solution than a traditional greedy algorithm. It also allows the user to adjust the efficiency of the program and quality of solutions. This algorithm has been implemented and tested on a variety of simulated and biological data. The experimental results indicate that our program can find better solutions than previous methods. This approach is quite general since it can be used to adapt other greedy algorithms to solving their corresponding problems.

Availability: The program is available upon request.

Associate Editor: Martin Bishop
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