Using Population Mixtures to Optimize the Utility of Genomic Databases: Linkage Disequilibrium and Association Study Design in India

Authors

  • T. J. Pemberton,

    1. Institute for Genetic Medicine, University of Southern California, 2250 Alcazar St., Los Angeles, California 90033 USA
    2. Department of Human Genetics and Center for Computational Medicine and Biology, University of Michigan, 100 Washtenaw Ave., Ann Arbor, Michigan 48109 USA
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    • These authors contributed equally to this work.

  • M. Jakobsson,

    1. Department of Human Genetics and Center for Computational Medicine and Biology, University of Michigan, 100 Washtenaw Ave., Ann Arbor, Michigan 48109 USA
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    • These authors contributed equally to this work.

  • D. F. Conrad,

    1. Department of Human Genetics, University of Chicago, 920 East 58th St., Chicago, Illinois 60637 USA
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  • G. Coop,

    1. Department of Human Genetics, University of Chicago, 920 East 58th St., Chicago, Illinois 60637 USA
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  • J. D. Wall,

    1. Department of Epidemiology and Biostatistics, University of California, San Francisco, California 94107 USA
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  • J. K. Pritchard,

    1. Department of Human Genetics, University of Chicago, 920 East 58th St., Chicago, Illinois 60637 USA
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  • P. I. Patel,

    1. Institute for Genetic Medicine, University of Southern California, 2250 Alcazar St., Los Angeles, California 90033 USA
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  • N. A. Rosenberg

    Corresponding author
    1. Department of Human Genetics and Center for Computational Medicine and Biology, University of Michigan, 100 Washtenaw Ave., Ann Arbor, Michigan 48109 USA
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*Corresponding author: Department of Human Genetics and Center for Computational Medicine and Biology, University of Michigan, 100 Washtenaw Ave., Ann Arbor, MI 48109. Tel: (734) 615 9556, Fax: (734) 615 6553, E-mail: rnoah@umich.edu

Summary

When performing association studies in populations that have not been the focus of large-scale investigations of haplotype variation, it is often helpful to rely on genomic databases in other populations for study design and analysis – such as in the selection of tag SNPs and in the imputation of missing genotypes. One way of improving the use of these databases is to rely on a mixture of database samples that is similar to the population of interest, rather than using the single most similar database sample. We demonstrate the effectiveness of the mixture approach in the application of African, European, and East Asian HapMap samples for tag SNP selection in populations from India, a genetically intermediate region underrepresented in genomic studies of haplotype variation.

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