Dataset Information

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

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.

SUBMITTER: Buske OJ

PROVIDER: S-EPMC4775166 | biostudies-literature | 2015 Oct

REPOSITORIES: biostudies-literature

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

Buske Orion J OJ Schiettecatte François F Hutton Benjamin B Dumitriu Sergiu S Misyura Andriy A Huang Lijia L Hartley Taila T Girdea Marta M Sobreira Nara N Mungall Chris C Brudno Michael M

Human mutation 20151001 10

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 Interf ...[more]

PMID: 26255989

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Project description:Although polymicrobial infections, caused by combinations of viruses, bacteria, fungi and parasites, are being recognised with increasing frequency, little is known about the occurrence of within-species diversity in bacterial infections and the molecular and evolutionary bases of this diversity. We used multiple approaches to study the genomic and phenotypic diversity among 226 Escherichia coli isolates from deep and closed visceral infections occurring in 19 patients. We observed genomic variability among isolates from the same site within 11 patients. This diversity was of two types, as patients were infected either by several distinct E. coli clones (4 patients) or by members of a single clone that exhibit micro-heterogeneity (11 patients); both types of diversity were present in 4 patients. A surprisingly wide continuum of antibiotic resistance, outer membrane permeability, growth rate, stress resistance, red dry and rough morphotype characteristics and virulence properties were present within the isolates of single clones in 8 of the 11 patients showing genomic micro-heterogeneity. Many of the observed phenotypic differences within clones affected the trade-off between self-preservation and nutritional competence (SPANC). We showed in 3 patients that this phenotypic variability was associated with distinct levels of RpoS in co-existing isolates. Genome mutational analysis and global proteomic comparisons in isolates from a patient revealed a star-like relationship of changes amongst clonally diverging isolates. A mathematical model demonstrated that multiple genotypes with distinct RpoS levels can co-exist as a result of the SPANC trade-off. In the cases involving infection by a single clone, we present several lines of evidence to suggest diversification during the infectious process rather than an infection by multiple isolates exhibiting a micro-heterogeneity. Our results suggest that bacteria are subject to trade-offs during an infectious process and that the observed diversity resembled results obtained in experimental evolution studies. Whatever the mechanisms leading to diversity, our results have strong medical implications in terms of the need for more extensive isolate testing before deciding on antibiotic therapies.

Dataset Information

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

Publications

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

Similar Datasets

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