All genome-wide SNP genotyping was performed using the InfiniumII HumanHap550 BeadChip at the Center for Applied Genomics at The Children’s Hospital of Philadelphia (CHOP). We called CNVs with the PennCNV algorithm15, which combines multiple values, including Log R Ratio, B Allele Frequency, SNP spacing and population frequency of the B allele into a hidden Markov model. The term ‘CNV’ represents individual CNV calls, whereas ‘CNVR’ refers to population-level variation. Quality control thresholds included a high success rate of attempted SNPs, low standard deviation of normalized intensity, genetically inferred European ancestry, low genomic wave artefacts, count of CNV calls per subject, and genotypic duplicate removal (Supplementary Table 4). CNV frequency between cases and controls was evaluated at each SNP using Fisher’s exact test. We report statistical local minimums in reference to a region of nominal significance including SNPs residing within 1Mb of each other (Supplementary Fig. 6). Resulting significant CNVRs were excluded if they were (1) residing on telomere or centromere proximal cytobands; (2) arising from a ‘peninsula’ of common CNV (Supplementary Fig. 7); (3) genomic regions with extremes in GC
