| Literature DB >> 31479590 |
Sebastian Köhler1,2,3, N Christine Øien4, Orion J Buske5, Tudor Groza6, Julius O B Jacobsen3,7, Craig McNamara6, Nicole Vasilevsky3,8, Leigh C Carmody3,9, J P Gourdine3,8, Michael Gargano3,9, Julie A McMurry3,10, Daniel Danis3,9, Christopher J Mungall3,11, Damian Smedley3,7, Melissa Haendel3,8,10, Peter N Robinson3,9,12.
Abstract
The Human Phenotype Ontology (HPO) is a standardized set of phenotypic terms that are organized in a hierarchical fashion. It is a widely used resource for capturing human disease phenotypes for computational analysis to support differential diagnostics. The HPO is frequently used to create a set of terms that accurately describe the observed clinical abnormalities of an individual being evaluated for suspected rare genetic disease. This profile is compared with computational disease profiles in the HPO database with the aim of identifying genetic diseases with comparable phenotypic profiles. The computational analysis can be coupled with the analysis of whole-exome or whole-genome sequencing data through applications such as Exomiser. This article explains how to choose an optimal set of HPO terms for these cases and enter them with software, such as PhenoTips and PatientArchive, and demonstrates how to use Phenomizer and Exomiser to generate a computational differential diagnosis.Entities:
Keywords: HPO; Human Phenotype Ontology; differential diagnosis; exome; phenotype
Mesh：
Year: 2019 PMID： 31479590 PMCID： PMC6814016 DOI： 10.1002/cphg.92
Source DB: PubMed Journal: Curr Protoc Hum Genet ISSN： 1934-8258