In order to examine overall consistency of association between datasets, we employed a leave-one-out procedure for internal cross-validation. At each step, we meta-analyzed eight of the nine CC GWAS samples as the “training” set (seven of the eight samples were used for FS), the results of which were then tested in the respective remaining target sample (“testing” set). The top associated SNPs in the training set (Ptraining<1×10−5, pruned to r2<0.4 within a 500-kb window) were used to test the replicability (Ptesting<0.05) and consistency of the direction of their effects with the top associated SNPs identified in each testing set. One thousand random permutations of phenotype allocation to an individual’s genome-wide genotypes were performed in each training-testing set pair, totaling 9,000 and 8,000 permutations in CC and FS, respectively. Across all sets, we compared the aggregate numbers of replicated SNPs and SNPs with the same direction of effect against the numbers expected by chance.
