Homozygosity Mapping (HM) is a well-known technique to identify long runs of genetic marker homozygosity that are likely to harbor genes responsible for recessive disease, but there has been no comparable method for dominant traits. We have developed an approach to map dominant disease genes based on heterozygosity frequencies of sequence variants in the immediate vicinity of a dominant trait. Based on theoretical analysis, computer simulation, and sequence data in patients with known pathogenic variants, the new Heterozygosity Analysis (HA) represents a powerful tool for finding dominant disease variants. In contrast to HM (based on recombination), our HA method relies on linkage disequilibrium, which dissipates rapidly with increasing distance from a trait variant, so that HA tends to identify dominant disease variants rather accurately.
As part of our statistical analysis, we developed a novel approach to test for homogeneity, assuming heterogeneity as the null hypothesis (equivalence testing), which appears the most plausible situation for many complex traits.