Empirical estimation of genome-wide significance thresholds based on the 1000 Genomes Project data set

• Published in: Journal of human genetics 2016-10, Vol.61 (10), p.861-866
• Main Authors: Kanai, Masahiro, Tanaka, Toshihiro, Okada, Yukinori
• Format: Article
• Language: English
• Subjects: Computer Simulation; Datasets as Topic; Ethnic Groups - genetics; Genetics, Population - methods; Genome-Wide Association Study - methods; Genomics - methods; Humans; Linkage Disequilibrium; Meta-Analysis as Topic; Models, Genetic; Original
• ISSN: 1434-5161; 1435-232X
• DOI: 10.1038/jhg.2016.72

To assess the statistical significance of associations between variants and traits, genome-wide association studies (GWAS) should employ an appropriate threshold that accounts for the massive burden of multiple testing in the study. Although most studies in the current literature commonly set a genome-wide significance threshold at the level of P=5.0 × 10 , the adequacy of this value for respective populations has not been fully investigated. To empirically estimate thresholds for different ancestral populations, we conducted GWAS simulations using the 1000 Genomes Phase 3 data set for Africans (AFR), Europeans (EUR), Admixed Americans (AMR), East Asians (EAS) and South Asians (SAS). The estimated empirical genome-wide significance thresholds were P =3.24 × 10 (AFR), 9.26 × 10 (EUR), 1.83 × 10 (AMR), 1.61 × 10 (EAS) and 9.46 × 10 (SAS). We additionally conducted trans-ethnic meta-analyses across all populations (ALL) and all populations except for AFR (ΔAFR), which yielded P =3.25 × 10 (ALL) and 4.20 × 10 (ΔAFR). Our results indicate that the current threshold (P=5.0 × 10 ) is overly stringent for all ancestral populations except for Africans; however, we should employ a more stringent threshold when conducting a meta-analysis, regardless of the presence of African samples.