As expected, principal components analysis (PCA) using the entire 200K SNP sets were effective in correcting the false positive associations for each of the three surrogate phenotypes was examined in mixed population sets (Fig. 3a, b, c and Supplementary Table S5). The 128 In4 and 96 In4 AIM sets were nearly as effective in correcting the false positive associations. Smaller In4 sets also corrected most of the false positive results, however these sets failed on some of the analyses e.g. the false association for rs4871195 in the LCT model remained significant for 64 In4 and smaller sets. For the admixed AFA population group, similar results were observed (Fig. 3d and Supplementary Table S5). Here, the smallest set (24 In4) showed incomplete correction. Together, these analyses show that relatively small numbers of AIMs can correct for false positive results in these Mendelian models.
