Multiple ant colony algorithm method for selecting tag SNPs

[Display omitted] ► A multiple ant colony algorithm (MACA) is used to search the better combination of tag SNP for haplotyping. ► A minimum test set model is proposed for tag SNPs selection problem. ► Larger granularity can save run time, and smaller granularity can select a smaller set of tag SNP....

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Bibliographic Details
Published in:Journal of biomedical informatics 2012-10, Vol.45 (5), p.931-937
Main Authors: Liao, Bo, Li, Xiong, Zhu, Wen, Li, Renfa, Wang, Shulin
Format: Article
Language:English
Subjects:
Algorithms
Animals
Ant colony algorithm
Ants
Computer Simulation
Databases, Genetic
Genomics - methods
Haplotypes
HapMap Project
Humans
Models, Biological
Models, Genetic
Models, Statistical
Polymorphism, Single Nucleotide
Single nucleotide polymorphisms
Tag SNPs selection problem
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Summary:[Display omitted] ► A multiple ant colony algorithm (MACA) is used to search the better combination of tag SNP for haplotyping. ► A minimum test set model is proposed for tag SNPs selection problem. ► Larger granularity can save run time, and smaller granularity can select a smaller set of tag SNP. The search for the association between complex disease and single nucleotide polymorphisms (SNPs) or haplotypes has recently received great attention. Finding a set of tag SNPs for haplotyping in a great number of samples is an important step to reduce cost for association study. Therefore, it is essential to select tag SNPs with more efficient algorithms. In this paper, we model problem of selection tag SNPs by MINIMUM TEST SET and use multiple ant colony algorithm (MACA) to search a smaller set of tag SNPs for haplotyping. The various experimental results on various datasets show that the running time of our method is less than GTagger and MLR. And MACA can find the most representative SNPs for haplotyping, so that MACA is more stable and the number of tag SNPs is also smaller than other evolutionary methods (like GTagger and NSGA-II). Our software is available upon request to the corresponding author.
ISSN:1532-0464
1532-0480
DOI:10.1016/j.jbi.2012.03.003