Evaluation of exome filtering techniques for the analysis of clinically relevant genes.

Abstract

A significant challenge facing clinical translation of exome sequencing is meaningful and efficient variant interpretation. Each exome contains ∼500 rare coding variants; laboratories must systematically and efficiently identify which variant(s) contribute to the patient\u27s phenotype. In silico filtering is an approach that reduces analysis time while decreasing the chances of incidental findings. We retrospectively assessed 55 solved exomes using available datasets as in silico filters: Online Mendelian Inheritance in Man (OMIM), Orphanet, Human Phenotype Ontology (HPO), and Radboudumc University Medical Center curated panels. We found that personalized panels produced using HPO terms for each patient had the highest success rate (100%), while producing considerably less variants to assess. HPO panels also captured multiple diagnoses in the same individual. We conclude that custom HPO-derived panels are an efficient and effective way to identify clinically relevant exome variants. Hum Mutat 2018 Feb; 39(2):197-201

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