To identify genomic loci shared across multiple neuropsychiatric disorders, we performed primary meta-analysis using the subset-based fixed-effects method ASSET (Bhattacharjee et al., 2012). Standard meta-analysis pools the effect of a given SNP across K studies, weighting the effects by the size of the study. By exhaustive investigation of all subset-based effects, the maximum SNP effect was identified as: Zmax−meta=maxS∈S|Z(S)|, where the absolute value of the subset-specific effect [Z(S)] over class S of all possible subsets of K studies is highest. The numbers of shared subjects across eight disorder studies were identified using the PGC checksum algorithm, and Zmeta was standardized so that covariance between the statistics can be accounted for as previously described (Bhattacharjee et al., 2012; Lin and Sullivan, 2009). Tail probabilities for the distribution of the maximum, adjusting for multiple testing of all combination of subsets, were then estimated with the discrete local maxima method, which uses the correlation structure of test statistics across subsets. Based on the derived p-value, standard deviation of the SNP effect was adjusted to reflect the multiple-testing correction. Even when correcting for all
