The identification and characterization of the effects of collections of rare variants on common complex disease susceptibility and general phenotypic expression will play prominent roles in future genetic studies. Appropriate data analysis methods for associating rare variants to a phenotype are therefore needed. A number of rare variant association analysis methods have been proposed that build off the notion of collapsing variants into groups based on either functional annotations of the genomic regions they reside in or on their location in a defined genomic region or ‘window.’ The power and robustness of these models need to be assessed in a wide variety of contexts. In addition, future studies of rare variants will likely be pursued in the context of a broader understanding of the genetic and environmental factors contributing to a particular common complex disease, making it unlikely that an exclusive focus on the influence of rare variants would be appropriate. Furthermore, as DNA sequencing and other genomic technology costs decrease, the frequency and functional impact of different forms of variation beyond SNPs will also be better understood. In this
