AUTHOR=Wang Yi , Li Yi , Hao Meng , Liu Xiaoyu , Zhang Menghan , Wang Jiucun , Xiong Momiao , Shugart Yin Yao , Jin Li TITLE=Robust Reference Powered Association Test of Genome-Wide Association Studies JOURNAL=Frontiers in Genetics VOLUME=10 YEAR=2019 URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2019.00319 DOI=10.3389/fgene.2019.00319 ISSN=1664-8021 ABSTRACT=

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.