Recognizing the importance of more stringent filtering strategies to improve variant classification prompted us to use the DVD to define the molecular landscape of deafness-associated genes. When normalized to genomic size, some genes show remarkably high variation rates, such as ACTG1, although for the majority of genes the variation rate is below 10% (Figures 4B and S2B). This trend changes dramatically when only clinically relevant regions (coding and splice regions) are considered, implying that most variation is intronic. The coding/splice-site variation rate is highest for GJB2 (∼69%) and ranges from 8.5% to 53% for all other genes (Figures 4B and S2B, Table S5). Other studies, notably by Petrovski et al.,34 Lek et al.,12 and Samocha et al.,35 have used population-scale databases of variant numbers and allele frequencies to infer gene constraint or tolerance to genetic variation. Their assumption is that genes carrying more variants than expected have low constraint, while those with lesser variants have higher constraint and are intolerant to genetic variation. Our data showed that GJB2 does not fit into this model. Although it has the highest variation rate, it also carries the highest fraction of pathogenic variants (Figure 4C). This observation contrasts with its z-score of −1.07 (ExAC), which implies tolerance to variation and decreased constraint (Table S5). Similar findings are seen for SLC26A4, where every other variant is disease causing although its Z score is −3.23. These findings highlight the need to integrate real variant clinical interpretation data for each gene-phenotype association as large-scale population data can be misleading.