A Review of Power and Sample Size Estimation in Genomewide Association Studies.

Park, Ae Kyung; Kim, Ho

doi:2007.40.2.114

J Prev Med Public Health > Volume 40(2); 2007 > Article

English Abstract

Journal of Preventive Medicine and Public Health 2007;40(2): 114-121. doi: https://doi.org/10.3961/jpmph.2007.40.2.114

A Review of Power and Sample Size Estimation in Genomewide Association Studies.

Ae Kyung Park, Ho Kim

Graduate School of Public Health, Seoul National University, Korea. hokim@snu.ac.kr

ABSTRACT

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.

Key words: Research design; Sample size; Genomics; Genetic screening