Iuliana Ionita-Laza and colleagues report a statistical framework for exome sequencing studies used to identify the genetic basis of Mendelian disorders (Am. J. Hum. Genet., published online 30 November 2011; doi:10.1016/j.ajhg.2011.11.003). They develop a joint-rank algorithm implemented in publicly available software, which combines a filter-based approach for gene ranking, as is commonly used in current exome sequencing studies, with a new weighted-sum statistic that calculates an approximate P value for each gene. Their approach allows analyses of both related and unrelated individuals within a sample. They test their method in simulations as well as on an exome sequencing dataset that included 310 unaffected individuals from an autism sequencing project. In their simulations, the joint-rank method outperformed both the filter-based and weighted-sum statistics applied individually, and the relative performance improved with increasing genetic heterogeneity. The authors also note that the performance of each method was enhanced by increasing the numbers of sequenced controls. The joint-rank application is further demonstrated on three recent exome sequencing studies for Miller, Freeman-Sheldon and Kabuki Syndromes.