Interpretable Clinical Genomics with a Likelihood Ratio Paradigm.

ABSTRACT: 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 explo

SUBMITTER: Robinson PN 

PROVIDER: S-EPMC7477017 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature