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PMID: 26255989 Published · ppublish English Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

The Matchmaker Exchange API: automating patient matching through the exchange of structured phenotypic and genotypic profiles.

Human mutation ·Vol. 36 ·No. 10 ·2015-10-00 ·Pages 922-7

Buske OJ, Schiettecatte F, Hutton B, Dumitriu S, Misyura A, Huang L, Hartley T, Girdea M, Sobreira N, Mungall C, Brudno M

Abstract

Despite the increasing prevalence of clinical sequencing, the difficulty of identifying additional affected families is a key obstacle to solving many rare diseases. There may only be a handful of similar patients worldwide, and their data may be stored in diverse clinical and research databases. Computational methods are necessary to enable finding similar patients across the growing number of patient repositories and registries. We present the Matchmaker Exchange Application Programming Interface (MME API), a protocol and data format for exchanging phenotype and genotype profiles to enable matchmaking among patient databases, facilitate the identification of additional cohorts, and increase the rate with which rare diseases can be researched and diagnosed. We designed the API to be straightforward and flexible in order to simplify its adoption on a large number of data types and workflows. We also provide a public test data set, curated from the literature, to facilitate implementation of the API and development of new matching algorithms. The initial version of the API has been successfully implemented by three members of the Matchmaker Exchange and was immediately able to reproduce previously identified matches and generate several new leads currently being validated. The API is available at https://github.com/ga4gh/mme-apis.

Keywords
GA4GH HPO Matchmaker Exchange genomic API patient matchmaking rare disease
MeSH Terms
Algorithms Computational Biology/methods Databases, Genetic Genetic Predisposition to Disease Genotype Humans Information Dissemination/methods Phenotype Rare Diseases/genetics,pathology Web Browser
Authors & Affiliations
11 authors, click to expand affiliations / ORCID
Buske Orion J
Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, Canada. | Department of Computer Science, University of Toronto, Toronto, Canada. | Centre for Computational Medicine, The Hospital for Sick Children, Toronto, Canada.
Schiettecatte François
FS Consulting LLC, Salem, Massachusetts.
Hutton Benjamin
Wellcome Trust Sanger Institute, Cambridge, UK.
Dumitriu Sergiu
Centre for Computational Medicine, The Hospital for Sick Children, Toronto, Canada.
Misyura Andriy
Centre for Computational Medicine, The Hospital for Sick Children, Toronto, Canada.
Huang Lijia
Children's Hospital of Eastern Ontario Research Institute, Ottawa, Ontario, Canada.
Hartley Taila
Children's Hospital of Eastern Ontario Research Institute, Ottawa, Ontario, Canada.
Girdea Marta
Department of Computer Science, University of Toronto, Toronto, Canada. | Centre for Computational Medicine, The Hospital for Sick Children, Toronto, Canada.
Sobreira Nara
McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Mungall Chris
Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, California.
Brudno Michael
Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, Canada. | Department of Computer Science, University of Toronto, Toronto, Canada. | Centre for Computational Medicine, The Hospital for Sick Children, Toronto, Canada.
References (9)
9 references, click to expand
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Article Info
Journal
Human mutation
Abbr.
Hum Mutat
ISSN
1098-1004
Published
2015-10-00
Pages
922-7
Language
English
Region
United States
NLM ID
9215429
PMCID
PMC4775166
Subset
IM
Grants
NHGRI NIH HHS · U54 HG006542 · United States
NHGRI NIH HHS · 1U54HG006542 · United States
Canadian Institutes of Health Research · Canada
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