Quality control (QC) of GWAS data aims to remove low quality data and technical artifacts in order to reduce the risk of false positive associations. In diverse ancestry cohorts, the main issue is that many common QC criteria assume the sample comes from a homogeneous population. Applying standard QC procedures without adjustment for population structure leads to the erroneous removal of too many variants and samples from minority subgroups and admixed samples, reducing statistical power.
