Title |
PhenomeCentral: A Portal for Phenotypic and Genotypic Matchmaking of Patients with Rare Genetic Diseases
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Published in |
Human Mutation, August 2015
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DOI | 10.1002/humu.22851 |
Pubmed ID | |
Authors |
Orion J Buske, Marta Girdea, Sergiu Dumitriu, Bailey Gallinger, Taila Hartley, Heather Trang, Andriy Misyura, Tal Friedman, Chandree Beaulieu, William P Bone, Amanda E Links, Nicole L Washington, Melissa A Haendel, Peter N Robinson, Cornelius F Boerkoel, David Adams, William A Gahl, Kym M Boycott, Michael Brudno |
Abstract |
The discovery of disease-causing mutations typically requires confirmation of the variant or gene in multiple unrelated individuals, and a large number of rare genetic diseases remain unsolved due to difficulty identifying second families. To enable the secure sharing of case records by clinicians and rare disease scientists, we have developed the PhenomeCentral portal (https://phenomecentral.org). Each record includes a phenotypic description and relevant genetic information (exome or candidate genes). PhenomeCentral identifies similar patients in the database based on semantic similarity between clinical features, automatically prioritized genes from whole-exome data, and candidate genes entered by the users, enabling both hypothesis-free and hypothesis-driven matchmaking. Users can then contact other submitters to follow up on promising matches. PhenomeCentral incorporates data for over 1,000 patients with rare genetic diseases, contributed by the FORGE and Care4Rare Canada projects, the US NIH Undiagnosed Diseases Program, the EU Neuromics and ANDDIrare projects, as well as numerous independent clinicians and scientists. Though the majority of these records have associated exome data, most lack a molecular diagnosis. PhenomeCentral has already been used to identify causative mutations for several patients, and its ability to find matching patients and diagnose these diseases will grow with each additional patient that is entered. This article is protected by copyright. All rights reserved. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Spain | 1 | 10% |
Canada | 1 | 10% |
United States | 1 | 10% |
Argentina | 1 | 10% |
Unknown | 6 | 60% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 5 | 50% |
Scientists | 5 | 50% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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United Kingdom | 4 | 3% |
United States | 1 | <1% |
Iceland | 1 | <1% |
Unknown | 122 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 28 | 22% |
Student > Ph. D. Student | 21 | 16% |
Student > Master | 16 | 13% |
Other | 10 | 8% |
Professor | 9 | 7% |
Other | 23 | 18% |
Unknown | 21 | 16% |
Readers by discipline | Count | As % |
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Medicine and Dentistry | 30 | 23% |
Biochemistry, Genetics and Molecular Biology | 29 | 23% |
Agricultural and Biological Sciences | 23 | 18% |
Computer Science | 11 | 9% |
Neuroscience | 3 | 2% |
Other | 6 | 5% |
Unknown | 26 | 20% |