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In the era of precision medicine, variant interpretation is arguably the most challenging aspect of molecular diagnosis. Despite continuous and rapid advances in the field, many genes still do not have well-established genotype–phenotype correlations. On a variant level, pathogenicity characterizations have mostly relied on qualitative descriptors within a Mendelian framework while less discrete effects have been difficult to quantitate.1 Attempts to aggregate variant information across large cohorts have given us useful metrics such as population allele frequencies; however, these can be difficult to make inferences from due to variation across ancestral groups2 or allele association with conditions of varying clinical presentation.
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Wang et al. (2018) studied this question.
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