PT - JOURNAL ARTICLE AU - Anurag Verma AU - Yuki Bradford AU - Scott Dudek AU - Shefali S. Verma AU - Sarah A. Pendergrass AU - Marylyn D. Ritchie TI - A simulation study investigating power estimates in Phenome-Wide Association Studies AID - 10.1101/115550 DP - 2017 Jan 01 TA - bioRxiv PG - 115550 4099 - http://biorxiv.org/content/early/2017/03/12/115550.short 4100 - http://biorxiv.org/content/early/2017/03/12/115550.full AB - Background Phenome-Wide Association Studies (PheWAS) are a high throughput approach to evaluate comprehensive associations between genetic variants and a wide range of phenotypic measures. One of the main challenges with PheWAS is the varying sample size ranges of cases and controls across the many phenotypes of interest, that could affect statistical power to detect associations. The motivation of this study is to investigate the parameters, including sample size, that affect estimation of statistical power in PheWAS.Results We performed a PheWAS simulation study, where we investigated variation in statistical power based on different parameters like overall sample size, number of cases, case-control ratio, minor allele frequency, and disease penetrance. The simulation was performed on both dichotomous and continuous phenotypic measures. Our simulation on dichotomous traits suggests that the number of cases have more impact than the case to control ratio; also we find that a sample size of 200 cases or more seems to maintain statistical power to identify associations for common variants. For continuous measures, a sample size of 1000 or more individuals performed best in the power calculations. We primarily focused on common variants (MAF>0.01) in this study; However, in future studies, we will be extending this effort to perform similar simulations on rare variants.Conclusions This study provides a series of PheWAS simulation analysis that can be used to estimate statistical power under a number of potential scenarios. These results can be used to provide guidelines for appropriate study design for future PheWAS analyses.