We used the resulting list from the PGC to calculate schizophrenia risk profile scores in the independent Swedish samples using the --score function in PLINK. We did this 10 times using different subsets of the PGC SNPs selected by increasing P value thresholds. From the set of filtered SNPs from the PGC, we evaluated 10 different association P thresholds (PT): 0.0001, 0.001, 0.01, 0.05, 0.1, 0.2, 0.3, 0.4, 0.5, and 1.0 (i.e., include all SNPs). For each of these 10 sets of SNPs derived from the PGC, the schizophrenia risk profile score (the number of schizophrenia risk alleles weighted by the logistic regression beta) was calculated for each case and control in Sw1-6. Logistic regression was then used to test whether Swedish cases had significantly different burden of schizophrenia risk alleles in comparison to controls (including ancestry principal components as covariates). To estimate the proportion of variance of case-control status in the Swedish samples accounted for by the risk profile score from the PGC, we used the difference in the Nagelkerke pseudo R2 contrasting a logistic regression model containing the risk profile score plus ancestry covariates with a logistic regression model containing the covariates alone.
