coded in sequence VCF files (Tan et al. 2015). It would be difficult if not impossible to ensure that we accurately coded effect alleles for indels and multi-allelic sites for all the variants. We also removed low-frequency SNPs (MAF < 10%) and low-quality imputed variants (Minimac RSQ<0.9). For each p value threshold, we then rank-ordered all candidate SNPs by reported p value for association with schizophrenia in the PGC. We considered the most significant SNP and removed all variants in linkage disequilibrium r2 > 0.1 within 1 megabase of this variant from our rank-ordered list. We then moved on to the next most significant variant and again removed variants in linkage disequilibrium, repeating this process until no more variants remained in the rank-ordered list. This approach is similar to that used in the PGC’s own analysis (Schizophrenia Working Group of the Psychiatric Genomics Consortium, 2014). To derive statistically valid p values for the correlations between the polygenic risk scores and each endophenotype in the context of our twin design, we estimated in OpenMx (Boker et al. 2011) correlations and their 95% confidence intervals (Neale & Miller, 1997) using a standard twin family model (Martin & Eaves, 1977) with a shared
