Details of sample collection and genotype quality control are given in the Supplementary Note. The CLOZUK schizophrenia GWAS was performed using logistic regression with imputation probabilities (‘dosages’) adjusted for 11 principal-component analysis (PCA) covariates. These covariates were chosen as those nominally significant (P < 0.05) in a logistic regression for association with the phenotype56. To avoid overburdening the GWAS power by adding too many covariates to the regression model57, only the first 20 principal components were considered and tested for inclusion, as higher numbers only become useful for the analysis of populations that bear strong signatures of complex admixture58. The final set of covariates included the first five principal components (as recommended for most GWAS approaches59) and principal components 6, 9, 11, 12, 13 and 19. Quantile–quantile and Manhattan plots are shown in Supplementary Figs. 7 and 8.
