A benchmark study on current GWAS models in admixed populations.

ABSTRACT:

Objective

The performances of popular genome-wide association study (GWAS) models have not been examined yet in a consistent manner under the scenario of genetic admixture, which introduces several challenging aspects: heterogeneity of minor allele frequency (MAF), wide spectrum of case-control ratio, varying effect sizes, etc.

Methods

We generated a cohort of synthetic individuals (N = 19 234) that simulates (i) a large sample size; (ii) two-way admixture (Native American and European ancestry) and (iii) a binary phenotype. We then benchmarked three popular GWAS tools [generalized linear mixed model associated test (GMMAT), scalable and accurate implementation of generalized mixed model (SAIGE) and Tractor] by computing inflation factors and power calculations under differe

SUBMITTER: Yang Z 

PROVIDER: S-EPMC10689347 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature