TY - JOUR AU - Wang, Yi AU - Li, Yi AU - Hao, Meng AU - Liu, Xiaoyu AU - Zhang, Menghan AU - Wang, Jiucun AU - Xiong, Momiao AU - Shugart, Yin Yao AU - Jin, Li PY - 2019 M3 - Original Research TI - Robust Reference Powered Association Test of Genome-Wide Association Studies JO - Frontiers in Genetics UR - https://www.frontiersin.org/articles/10.3389/fgene.2019.00319 VL - 10 SN - 1664-8021 N2 - Genome-wide association studies (GWASs) have identified abundant genetic susceptibility loci, GWAS of small sample size are far less from meeting the previous expectations due to low statistical power and false positive results. Effective statistical methods are required to further improve the analyses of massive GWAS data. Here we presented a new statistic (Robust Reference Powered Association Test1) to use large public database (gnomad) as reference to reduce concern of potential population stratification. To evaluate the performance of this statistic for various situations, we simulated multiple sets of sample size and frequencies to compute statistical power. Furthermore, we applied our method to several real datasets (psoriasis genome-wide association datasets and schizophrenia genome-wide association dataset) to evaluate the performance. Careful analyses indicated that our newly developed statistic outperformed several previously developed GWAS applications. Importantly, this statistic is more robust than naive merging method in the presence of small control-reference differentiation, therefore likely to detect more association signals. ER -