Additional file 1: of Application of geographic population structure (GPS) algorithm for biogeographical analyses of populations with complex ancestries: a case study of South Asians from 1000 genomes project
Table S1. GPS predicted coordinates of individuals from five SAS populations. Figure S1. (a) Table showing proportion of Cross-Validation error (CVE) in ADMIXTURE carried out for the global dataset with different values of ancestral components (K) employed in the admixture analysis. The CVE was used to determine the optimum number of ancestral components (K) supported by the data. At K = 13 the CVE was minimized. (b) Plot depicting the change of CVE with increasing number of ancestral components (K). The optimum number of ancestral components with lowest CVE was thirteen (K = 13). Figure S2. (a) Table showing proportion of Cross-Validation error (CVE) in ADMIXTURE carried out for the South Asian only dataset with different values of ancestral components (K) employed in the admixture analysis. The CVE was used to determine the optimum number of ancestral components (K) supported by the data. At K = 8 the CVE was minimized. (b) Plot depicting the change of CVE with increasing number of ancestral components (K). The optimum number of ancestral components with lowest CVE was 8 (K = 8). (PDF 493 kb
