Interpretable Clinical Genomics with a Likelihood Ratio Paradigm.
Human Phenotype Ontology
exome sequencing
genome sequencing
liklihood ratio
phenotype-driven genomic diagnostics
Journal
American journal of human genetics
ISSN: 1537-6605
Titre abrégé: Am J Hum Genet
Pays: United States
ID NLM: 0370475
Informations de publication
Date de publication:
03 09 2020
03 09 2020
Historique:
received:
25
01
2020
accepted:
26
06
2020
pubmed:
7
8
2020
medline:
21
10
2020
entrez:
7
8
2020
Statut:
ppublish
Résumé
Human Phenotype Ontology (HPO)-based analysis has become standard for genomic diagnostics of rare diseases. Current algorithms use a variety of semantic and statistical approaches to prioritize the typically long lists of genes with candidate pathogenic variants. These algorithms do not provide robust estimates of the strength of the predictions beyond the placement in a ranked list, nor do they provide measures of how much any individual phenotypic observation has contributed to the prioritization result. However, given that the overall success rate of genomic diagnostics is only around 25%-50% or less in many cohorts, a good ranking cannot be taken to imply that the gene or disease at rank one is necessarily a good candidate. Here, we present an approach to genomic diagnostics that exploits the likelihood ratio (LR) framework to provide an estimate of (1) the posttest probability of candidate diagnoses, (2) the LR for each observed HPO phenotype, and (3) the predicted pathogenicity of observed genotypes. LIkelihood Ratio Interpretation of Clinical AbnormaLities (LIRICAL) placed the correct diagnosis within the first three ranks in 92.9% of 384 case reports comprising 262 Mendelian diseases, and the correct diagnosis had a mean posttest probability of 67.3%. Simulations show that LIRICAL is robust to many typically encountered forms of genomic and phenomic noise. In summary, LIRICAL provides accurate, clinically interpretable results for phenotype-driven genomic diagnostics.
Identifiants
pubmed: 32755546
pii: S0002-9297(20)30230-5
doi: 10.1016/j.ajhg.2020.06.021
pmc: PMC7477017
pii:
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
403-417Subventions
Organisme : NIH HHS
ID : R24 OD011883
Pays : United States
Organisme : NHGRI NIH HHS
ID : U24 HG009650
Pays : United States
Organisme : NHGRI NIH HHS
ID : U24 HG011449
Pays : United States
Organisme : NHGRI NIH HHS
ID : U41 HG009650
Pays : United States
Informations de copyright
Copyright © 2020 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
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