It is important to note the distinction between leveraging functional annotations to collapse a set of rare variants based on their location versus predictions that the variants themselves have a functional effect (Box 2).35 In fact, two recent papers23, 36 suggest that leveraging functional annotations and computational methods for predicting the consequences of specific rare variants can be used to great advantage in the identification of disease-predisposing variants, at least for rare monogenic conditions. Functional annotations for rare CNVs and other forms of structural variation can also be leveraged in collapsed or group-wise analyses. However, many of these forms of variation are thought to exert or manifest their effects throughout the genome and not necessarily as a group of variants in a singular region of the genome. Thus, pathway-based (Box 2) and other higher-order approaches to collapsing or summarizing rare CNV effects have been proposed, especially in the context of neuropsychiatric disease.3, 37
