Optimal DNA Pooling-Based Two-Stage Designs in Case-Control Association Studies
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作者:
Zhao, Yihong
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Columbia Univ, Mailman Sch Publ Hlth, Dept Biostat, New York, NY 10032 USAColumbia Univ, Mailman Sch Publ Hlth, Dept Biostat, New York, NY 10032 USA
Zhao, Yihong
[1
]
Wang, Shuang
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Columbia Univ, Mailman Sch Publ Hlth, Dept Biostat, New York, NY 10032 USAColumbia Univ, Mailman Sch Publ Hlth, Dept Biostat, New York, NY 10032 USA
Wang, Shuang
[1
]
机构:
[1] Columbia Univ, Mailman Sch Publ Hlth, Dept Biostat, New York, NY 10032 USA
Study cost remains the major limiting factor for genomewide association studies due to the necessity of genotyping a large number of SNPs for a large number of subjects. Both DNA pooling strategies and two-stage designs have been proposed to reduce genotyping costs. In this study, we propose a cost-effective, two-stage approach with a DNA pooling strategy. During stage I, all markers are evaluated on a subset of individuals using DNA pooling. The most promising set of markers is then evaluated with individual genotyping for all individuals during stage II. The goal is to determine the optimal parameters (pi(p)(sample), the proportion of samples used during stage I with DNA pooling; and pi(p)(marker), the proportion of markers evaluated during stage II with individual genotyping) that minimize the cost of a two-stage DNA pooling design while maintaining a desired overall significance level and achieving a level of power similar to that of a one-stage individual genotyping design. We considered the effects of three factors on optimal two-stage DNA pooling designs. Our results suggest that, under most scenarios considered, the optimal two-stage DNA pooling design may be much more cost-effective than the optimal two-stage individual genotyping design, which use individual genotyping during both stages. Copyright (C) 2008 S. Karger AG, Basel
机构:
Columbia Univ, Mailman Sch Publ Hlth, Dept Biostat, New York, NY 10032 USAColumbia Univ, Mailman Sch Publ Hlth, Dept Biostat, New York, NY 10032 USA
Zhao, Yihong
Wang, Shuang
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Columbia Univ, Mailman Sch Publ Hlth, Dept Biostat, New York, NY 10032 USAColumbia Univ, Mailman Sch Publ Hlth, Dept Biostat, New York, NY 10032 USA
机构:
Michigan State Univ, Dept Stat & Probabil, E Lansing, MI 48824 USAMichigan State Univ, Dept Stat & Probabil, E Lansing, MI 48824 USA
Zuo, Y.
Zou, G.
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机构:
Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100080, Peoples R China
Univ Rochester, Dept Biostat & Computat Biol, Rochester, NY 14642 USAMichigan State Univ, Dept Stat & Probabil, E Lansing, MI 48824 USA
Zou, G.
Wang, J.
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Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100080, Peoples R China
Kyoto Univ, Grad Sch Informat, Dept Appl Math & Phys, Kyoto 6068501, JapanMichigan State Univ, Dept Stat & Probabil, E Lansing, MI 48824 USA
Wang, J.
Zhao, H.
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Yale Univ, Sch Med, Dept Epidemiol & Publ Hlth, New Haven, CT 06520 USAMichigan State Univ, Dept Stat & Probabil, E Lansing, MI 48824 USA
Zhao, H.
Liang, H.
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Univ Rochester, Dept Biostat & Computat Biol, Rochester, NY 14642 USAMichigan State Univ, Dept Stat & Probabil, E Lansing, MI 48824 USA