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Ae Kyung Park 1 Article
A Review of Power and Sample Size Estimation in Genomewide Association Studies.
Ae Kyung Park, Ho Kim
J Prev Med Public Health. 2007;40(2):114-121.
DOI: https://doi.org/10.3961/jpmph.2007.40.2.114
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AbstractAbstract PDF
Power and sample size estimation is one of the crucially important steps in planning a genetic association study to achieve the ultimate goal, identifying candidate genes for disease susceptibility, by designing the study in such a way as to maximize the success possibility and minimize the cost. Here we review the optimal two-stage genotyping designs for genomewide association studies recently investigated by Wang et al(2006). We review two mathematical frameworks most commonly used to compute power in genetic association studies prior to the main study: Monte-Carlo and non-central chi-square estimates. Statistical powers are computed by these two approaches for case-control genotypic tests under one-stage direct association study design. Then we discuss how the linkagedisequilibrium strength affects power and sample size, and how to use empirically-derived distributions of important parameters for power calculations. We provide useful information on publicly available softwares developed to compute power and sample size for various study designs.
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Citations

Citations to this article as recorded by  
  • Sample Size and Statistical Power Calculation in Genetic Association Studies
    Eun Pyo Hong, Ji Wan Park
    Genomics & Informatics.2012; 10(2): 117.     CrossRef
  • The Effect of Increasing Control-to-case Ratio on Statistical Power in a Simulated Case-control SNP Association Study
    Moon-Su Kang, Sun-Hee Choi, In-Song Koh
    Genomics & Informatics.2009; 7(3): 148.     CrossRef

JPMPH : Journal of Preventive Medicine and Public Health