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The Matchmaker Exchange API: automating patient matching through the exchange of structured phenotypic and genotypic profiles.
Buske, Orion J; Schiettecatte, François; Hutton, Benjamin; Dumitriu, Sergiu; Misyura, Andriy; Huang, Lijia; Hartley, Taila; Girdea, Marta; Sobreira, Nara; Mungall, Chris; Brudno, Michael.
Afiliação
  • Buske OJ; Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, Canada.
  • Schiettecatte F; Department of Computer Science, University of Toronto, Toronto, Canada.
  • Hutton B; Centre for Computational Medicine, The Hospital for Sick Children, Toronto, Canada.
  • Dumitriu S; FS Consulting LLC, Salem, Massachusetts.
  • Misyura A; Wellcome Trust Sanger Institute, Cambridge, UK.
  • Huang L; Centre for Computational Medicine, The Hospital for Sick Children, Toronto, Canada.
  • Hartley T; Centre for Computational Medicine, The Hospital for Sick Children, Toronto, Canada.
  • Girdea M; Children's Hospital of Eastern Ontario Research Institute, Ottawa, Ontario, Canada.
  • Sobreira N; Children's Hospital of Eastern Ontario Research Institute, Ottawa, Ontario, Canada.
  • Mungall C; Department of Computer Science, University of Toronto, Toronto, Canada.
  • Brudno M; Centre for Computational Medicine, The Hospital for Sick Children, Toronto, Canada.
Hum Mutat ; 36(10): 922-7, 2015 Oct.
Article em En | MEDLINE | ID: mdl-26255989
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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Biologia Computacional / Doenças Raras / Disseminação de Informação Idioma: En Ano de publicação: 2015 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Biologia Computacional / Doenças Raras / Disseminação de Informação Idioma: En Ano de publicação: 2015 Tipo de documento: Article