There are a number of statistical analysis strategies that can be used to test the hypothesis that specific collections of rare variants are associated with a particular trait or disease. Some of these methods have been developed in contexts beyond human association studies, such as assessing genetic differentiation between human geoethnic groups or pathogen sequences. In addition, some methods are more or less agnostic to variant frequencies. In order to facilitate their descriptions, we have grouped various methods together in three broad and somewhat arbitrary categories: tests based on the use of group summary information on variant frequencies compared between, for example, case and control groups; tests based on the similarity or diversity of unique DNA sequences possessed by different individuals; and regression models that consider collapsed sets of variants and other factors as predictors of a phenotype. We consider each of these three categories separately below, although Table 2 provides brief summaries of representative methods from each category. Each of the methods discussed can leverage functional annotations to define collapsed variant sets or can be used in a moving window setting (Box 2).
