An Improved Phenotype-Driven Tool for Rare Mendelian Variant Prioritization: Benchmarking Exomiser on Real Patient Whole-Exome Data.
bioinformatics
human phenotype ontology
inherited retinal disease
phenotypic similarity
rare disease
variant prioritization
whole-exome sequencing
whole-genome sequencing
Journal
Genes
ISSN: 2073-4425
Titre abrégé: Genes (Basel)
Pays: Switzerland
ID NLM: 101551097
Informations de publication
Date de publication:
23 04 2020
23 04 2020
Historique:
received:
11
03
2020
revised:
08
04
2020
accepted:
16
04
2020
entrez:
29
4
2020
pubmed:
29
4
2020
medline:
27
3
2021
Statut:
epublish
Résumé
Next-generation sequencing has revolutionized rare disease diagnostics, but many patients remain without a molecular diagnosis, particularly because many candidate variants usually survive despite strict filtering. Exomiser was launched in 2014 as a Java tool that performs an integrative analysis of patients' sequencing data and their phenotypes encoded with Human Phenotype Ontology (HPO) terms. It prioritizes variants by leveraging information on variant frequency, predicted pathogenicity, and gene-phenotype associations derived from human diseases, model organisms, and protein-protein interactions. Early published releases of Exomiser were able to prioritize disease-causative variants as top candidates in up to 97% of simulated whole-exomes. The size of the tested real patient datasets published so far are very limited. Here, we present the latest Exomiser version 12.0.1 with many new features. We assessed the performance using a set of 134 whole-exomes from patients with a range of rare retinal diseases and known molecular diagnosis. Using default settings, Exomiser ranked the correct diagnosed variants as the top candidate in 74% of the dataset and top 5 in 94%; not using the patients' HPO profiles (i.e., variant-only analysis) decreased the performance to 3% and 27%, respectively. In conclusion, Exomiser is an effective support tool for rare Mendelian phenotype-driven variant prioritization.
Identifiants
pubmed: 32340307
pii: genes11040460
doi: 10.3390/genes11040460
pmc: PMC7230372
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : Department of Health
Pays : United Kingdom
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