The simplest approach to testing rare variants for association with a trait is to test them individually using standard contingency table and regression methods of the sort implemented in widely used genetic data analysis packages such as PLINK.32 This strategy is highly problematic given, for example, the poor power that such statistical tests have to detect small rare variant frequency differences between diagnostic or phenotypic groups (figures 1A and 1B).14, 28, 29 In order to overcome power issues associated with testing rare variants individually, one could ‘collapse’ sets of rare variants into a single group and test their collective frequency differences between cases and controls.28, 30 In its simplest form this strategy could involve counting individuals possessing a rare variant at any position in the genomic region of interest, calculating the frequencies of these individuals, for example in case and control groups, and then testing the two groups for frequency differences. This strategy forms the basis for most of the statistical models described in this review and variations of it have been considered in many studies involving rare variants (Table
