There are established QC metrics that are used to remove problematic variants prior to running GWAS analyses, including markers in violation of HWE, low minor allele frequency (MAF), and poor imputation quality. These QC procedures need to be carefully considered when applied to diverse samples as there can be significant differences on these metrics by ancestry. Therefore standard QC procedures were applied to each genetically assigned super-population separately. Post GWAS filtering was performed using ancestry specific HWE (p >10−6) and sample size based MAFs. As a result, there was greater marker retention by applying QC to empirically assigned ancestry groups and then meta-analyzed across groups. When analyzing all samples together, 2.7×106 markers were removed due to excessive violation of HWE (p<10−6), representing 16% of markers passing minimum INFO and MAF thresholds. As shown in Table 2, for individual groups, few markers (0.1%) were filtered due to HWE except for census Asian (0.8%) which had a higher frequency of markers failing HWE than other census categories. By performing meta-analysis across assigned ancestry groups, as compared to census categories or all samples together, we were able to retain 220,689 – 1,930,671 SNPs, which would have otherwise been removed from analysis (Table 2).
