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Hum Mutat. 2018 Feb;39(2):197-201. doi: 10.1002/humu.23374. Epub 2017 Dec 14.

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

Author information

1
Children's Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, Ontario, Canada.
2
McGill University and Genome Quebec Innovation Centre, Montreal, Quebec, Canada.
3
The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut.
4
Institute for Systems Genomics, University of Connecticut, Farmington, Connecticut.
5
Department of Genetics, Children's Hospital of Eastern Ontario, Ottawa, Ontario, Canada.

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's 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.

KEYWORDS:

Human Phenotype Ontology (HPO); clinical exome sequencing; exome filtering; phenotype driven analysis

PMID:
29193559
DOI:
10.1002/humu.23374
[Indexed for MEDLINE]

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