The statistical approach we used to classify recurrent CNVs and the results we obtained are useful tools for researchers and the clinical community in interpreting whether a CNV has pathologic effects. However, while such statistical analysis is possible for recurrent CNVs, where the frequency is high, this strategy is more difficult for the remaining ~75% of CNVs, which are not mediated by segmental duplications and are individually very rare. Therefore, other approaches need to be explored to address this class of CNVs. One possibility for these highly heterogenous CNVs is to analyze all genomic intervals of a defined size (e.g., 500 kb or 1 Mb) or to use a “sliding-window” analysis to examine overlapping genomic intervals along the length of each chromosome. By comparing structural variation observed in cases to controls, disease-causing regions can be differentiated from those associated with normal variation by using the control data to define regions of the genome where dosage changes can be tolerated without overt phenotypic effects. Since non-recurrent CNVs are very rare events, the collection of data from hundreds of thousands of cases
