we rigorously eliminated potential sources of errors in the case CNV data with a combination of both manual and automated filters, including calls with low probe counts, high degrees of overlap with segmental duplications in the reference assembly, and likely reference-sample CNVs. Third, for the sliding window enrichment tests we eliminated all CNVs in cases that spanned fewer than 10 probes on the lowest resolution (HH317K) control SNP array. Fourth, we have validated 402/425 CNVs and determined the precision in cases to be high in general (0.945) and higher in cases relative to controls (0.892). Fifth, we specifically analyzed the 14 potentially pathogenic CNVs (Table 2) for control SNP microarray performance. 11/14 loci harbored small CNV calls within the region of interest from multiple control studies; as CNV calling algorithms tend to demonstrate increased sensitivity to larger alterations, we consider this to indicate sufficient control sensitivity within these loci to detect large CNVs. The remaining three loci are split between the minimal common region on 1q24.3, which demonstrates a single 72 kbp CNV in controls (again suggesting detectability of larger events), and two loci that harbor very small CNVs detectable only on the highest resolution 1.2M probe arrays. These two
