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The Human Phenotype Ontology in 2017.

Sebastian Köhler | Nicole A Vasilevsky | Mark Engelstad | Erin Foster | Julie McMurry | Ségolène Aymé | Gareth Baynam | Susan M Bello | Cornelius F Boerkoel | Kym M Boycott | Michael Brudno | Orion J Buske | Patrick F Chinnery | Valentina Cipriani | Laureen E Connell | Hugh J S Dawkins | Laura E DeMare | Andrew D Devereau | Bert B A de Vries | Helen V Firth | Kathleen Freson | Daniel Greene | Ada Hamosh | Ingo Helbig | Courtney Hum | Johanna A Jähn | Roger James | Roland Krause | Stanley J F Laulederkind | Hanns Lochmüller | Gholson J Lyon | Soichi Ogishima | Annie Olry | Willem H Ouwehand | Nikolas Pontikos | Ana Rath | Franz Schaefer | Richard H Scott | Michael Segal | Panagiotis I Sergouniotis | Richard Sever | Cynthia L Smith | Volker Straub | Rachel Thompson | Catherine Turner | Ernest Turro | Marijcke W M Veltman | Tom Vulliamy | Jing Yu | Julie von Ziegenweidt | Andreas Zankl | Stephan Züchner | Tomasz Zemojtel | Julius O B Jacobsen | Tudor Groza | Damian Smedley | Christopher J Mungall | Melissa Haendel | Peter N Robinson
Nucleic acids research | 2017

Deep phenotyping has been defined as the precise and comprehensive analysis of phenotypic abnormalities in which the individual components of the phenotype are observed and described. The three components of the Human Phenotype Ontology (HPO; www.human-phenotype-ontology.org) project are the phenotype vocabulary, disease-phenotype annotations and the algorithms that operate on these. These components are being used for computational deep phenotyping and precision medicine as well as integration of clinical data into translational research. The HPO is being increasingly adopted as a standard for phenotypic abnormalities by diverse groups such as international rare disease organizations, registries, clinical labs, biomedical resources, and clinical software tools and will thereby contribute toward nascent efforts at global data exchange for identifying disease etiologies. This update article reviews the progress of the HPO project since the debut Nucleic Acids Research database article in 2014, including specific areas of expansion such as common (complex) disease, new algorithms for phenotype driven genomic discovery and diagnostics, integration of cross-species mapping efforts with the Mammalian Phenotype Ontology, an improved quality control pipeline, and the addition of patient-friendly terminology.

Pubmed ID: 27899602 RIS Download

Research resources used in this publication

None found

Antibodies used in this publication

None found

Associated grants

  • Agency: NHGRI NIH HHS, United States
    Id: U01 HG009453
  • Agency: British Heart Foundation, United Kingdom
    Id: RG/09/012/28096
  • Agency: Medical Research Council, United Kingdom
    Id: MC_UP_1501/2
  • Agency: Medical Research Council, United Kingdom
    Id: G1002274
  • Agency: NHGRI NIH HHS, United States
    Id: U41 HG000330
  • Agency: NIH HHS, United States
    Id: R24 OD011883
  • Agency: Department of Health, United Kingdom
    Id: RP-PG-0310-1002

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This is a list of tools and resources that we have found mentioned in this publication.


Human Phenotype Ontology (tool)

RRID:SCR_006016

Provides standardized vocabulary of phenotypic abnormalities encountered in human disease. Structured and controlled vocabulary for phenotypic features encountered in human hereditary and other disease. HPO is being developed in collaboration with members of OBO Foundry (Open Biological and Biomedical Ontologies), and logical definitions for HPO terms are being developed using PATO and a number of other ontologies including FMA, GO, ChEBI, and MPATH.

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Deciphering Developmental Disorders (tool)

RRID:SCR_006171

The Deciphering Developmental Disorders (DDD) study aims to find out if using new genetic technologies can help doctors understand why patients get developmental disorders. To do this we have brought together doctors in the 23 NHS Regional Genetics Services throughout the UK and scientists at the Wellcome Trust Sanger Institute, a charitably funded research institute which played a world-leading role in sequencing (reading) the human genome. The DDD study involves experts in clinical, molecular and statistical genetics, as well as ethics and social science. It has a Scientific Advisory Board consisting of scientists, doctors, a lawyer and patient representative, and has received National ethical approval in the UK. Over the next few years, we are aiming to collect DNA and clinical information from 12,000 undiagnosed children in the UK with developmental disorders and their parents. The results of the DDD study will provide a unique, online catalogue of genetic changes linked to clinical features that will enable clinicians to diagnose developmental disorders. Furthermore, the study will enable the design of more efficient and cheaper diagnostic assays for relevant genetic testing to be offered to all such patients in the UK and so transform clinical practice for children with developmental disorders. Over time, the work will also improve understanding of how genetic changes cause developmental disorders and why the severity of the disease varies in individuals. The Sanger Institute will contribute to the DDD study by performing genetic analysis of DNA samples from patients with developmental disorders, and their parents, recruited into the study through the Regional Genetics Services. Using microarray technology and the latest DNA sequencing methods, research teams will probe genetic information to identify mutations (DNA errors or rearrangements) and establish if these mutations play a role in the developmental disorders observed in patients. The DDD initiative grew out of the groundbreaking DECIPHER database, a global partnership of clinical genetics centres set up in 2004, which allows researchers and clinicians to share clinical and genomic data from patients worldwide. The DDD study aims to transform the power of DECIPHER as a diagnostic tool for use by clinicians. As well as improving patient care, the DDD team will empower researchers in the field by making the data generated securely available to other research teams around the world. By assembling a solid resource of high-quality, high-resolution and consistent genomic data, the leaders of the DDD study hope to extend the reach of DECIPHER across a broader spectrum of disorders than is currently possible.

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DECIPHER (tool)

RRID:SCR_006552

Interactive database which incorporates a suite of tools designed to aid the interpretation of submicroscopic chromosomal imbalance. Used to enhance clinical diagnosis by retrieving information from bioinformatics resources relevant to the imbalance found in the patient. Contributing to the DECIPHER database is a Consortium, comprising an international community of academic departments of clinical genetics. Each center maintains control of its own patient data (which are password protected within the center''''s own DECIPHER project) until patient consent is given to allow anonymous genomic and phenotypic data to become freely viewable within Ensembl and other genome browsers. Once data are shared, consortium members are able to gain access to the patient report and contact each other to discuss patients of mutual interest, thus facilitating the delineation of new microdeletion and microduplication syndromes.

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International Mouse Phenotyping Consortium (IMPC) (tool)

RRID:SCR_006158

Center that produces knockout mice and carries out high-throughput phenotyping of each line in order to determine function of every gene in mouse genome. These mice will be preserved in repositories and made available to scientific community representing valuable resource for basic scientific research as well as generating new models for human diseases.

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