The Evolution of Constitutional Sequence Variant Interpretation

Clinics in Laboratory Medicine(2020)

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摘要
A combination of different types of evidence incorporating population data, functional studies, clinical data, and predictive tools is necessary for thorough, thoughtful variant classification. Variant classification criteria may be optimized in a quantitative, gene-specific manner using validated predictors of pathogenicity for genes or conditions with sufficient information. Large-scale data (genome sequencing of healthy and affected cohorts, high-throughput functional studies, and in silico metapredictors) increase the robustness of evidence used for variant classification and lend themselves to incorporation in quantitative frameworks. Collaborative efforts by laboratories and disease-specific expert groups reduce variant classification discrepancies and improve the quality of variant interpretation information available to patients and researchers.
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关键词
Variant classification,Genetic testing,Population data,Functional studies,In silico,de novo,Quantitative,ACMG-AMP
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