We used JAG (Joint Association of Genetic variants, http://ctglab.nl/software) to conduct gene-set analyses. This method has previously been applied to the International Schizophrenia Consortium data by Lips et al. 94 JAG tests for the association of specified gene-sets with schizophrenia as applied to individual-level genotype data which tends to be more powerful than using summary statistics. JAG constructs a test-statistic for each gene-set. JAG includes both self-contained and competitive tests. These two approaches evaluate different null hypotheses. Statistical significance (Pself and Pcomp) are determined using permutation. First, the self-contained test evaluates the null hypothesis that a defined set of genes is not associated with schizophrenia while accounting for the some of the properties of the SNPs being studied (e.g., LD structure). Second, the competitive test evaluates whether a specific set of genes has evidence for stronger associations with schizophrenia than randomly selected sets of control genes (with the latter matched to the former using the same effective number of SNPs per gene-set). Thus, a competitive test is of the null hypothesis is that these genes are not more strongly associated
