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Bioinformatics Advance Access first published online on September 7, 2007
This version published online on September 12, 2007
Bioinformatics, doi:10.1093/bioinformatics/btm426
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Published by Oxford University Press 2007.
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TAGster: Efficient Selection of LD tag SNPs in Single or Multiple Populations

Zongli Xu 1, Norman L. Kaplan 2 and Jack A. Taylor 1,3,*

1Epidemiology Branch, 2Biostatistics Branch, and 3Laboratory of Molecular Carcinogenesis, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina 27709, USA

*To whom correspondence should be addressed. Jack A. Taylor E-mail: taylor{at}niehs.nih.gov


  Abstract

Summary: Genetic association studies increasingly rely on the use of linkage disequilibrium (LD) tag SNPs to reduce genotyping costs. We developed a software package TAGster to select, evaluate, and visualize LD tag SNPs both for single and multiple populations. We implement several strategies to improve the efficiency of current LD tag SNP selection algorithms: 1) we modify the tag SNP selection procedure of Carlson et al. (2004) to improve selection efficiency and further generalize it to multiple populations. 2) We propose a redundant SNP elimination step to speed up the exhaustive tag SNP search algorithm proposed by Qin et al. (2006). 3) We present an additional multiple population tag SNP selection algorithm based on the framework of Howie et al. (2006), but using our modified exhaustive search procedure. We evaluate these methods using resequenced candidate gene data from the Environmental Genome Project and show improvements in both computational and tagging efficiency.

Availability: The software Package TAGster is freely available at http://dir.niehs.nih.gov/direb/tagster/

Supplementary information: Additional information, including a tutorial, detailed algorithm and detailed evaluation results, is also available from TAGster web site (see above)

Contact: taylor{at}niehs.nih.gov

Associate Editor: Prof. Martin Bishop

Received on June 5, 2007; revised on July 23, 2007; accepted on August 15, 2007

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