@article {440, title = {Matchmaker Exchange.}, journal = {Curr Protoc Hum Genet}, volume = {95}, year = {2017}, month = {2017 10 18}, pages = {9.31.1-9.31.15}, abstract = {

In well over half of the individuals with rare disease who undergo clinical or research next-generation sequencing, the responsible gene cannot be determined. Some reasons for this relatively low yield include unappreciated phenotypic heterogeneity; locus heterogeneity; somatic and germline mosaicism; variants of uncertain functional significance; technically inaccessible areas of the genome; incorrect mode of inheritance investigated; and inadequate communication between clinicians and basic scientists with knowledge of particular genes, proteins, or biological systems. To facilitate such communication and improve the search for patients or model organisms with similar phenotypes and variants in specific candidate genes, we have developed the Matchmaker Exchange (MME). MME was created to establish a federated network connecting databases of genomic and phenotypic data using a common application programming interface (API). To date, seven databases can exchange data using the API (GeneMatcher, PhenomeCentral, DECIPHER, MyGene2, matchbox, Australian Genomics Health Alliance Patient Archive, and Monarch Initiative; the latter included for model organism matching). This article guides usage of the MME for rare disease gene discovery. {\textcopyright} 2017 by John Wiley \& Sons, Inc.

}, keywords = {Animals, Computational Biology, Databases, Genetic, Genetic Association Studies, Genetic Predisposition to Disease, Genomics, Humans, Rare Diseases, Software, Web Browser}, issn = {1934-8258}, doi = {10.1002/cphg.50}, author = {Sobreira, Nara L M and Arachchi, Harindra and Buske, Orion J and Chong, Jessica X and Hutton, Ben and Foreman, Julia and Schiettecatte, Fran{\c c}ois and Groza, Tudor and Jacobsen, Julius O B and Haendel, Melissa A and Boycott, Kym M and Hamosh, Ada and Rehm, Heidi L} } @article {139, title = {GeneMatcher: a matching tool for connecting investigators with an interest in the same gene.}, journal = {Hum Mutat}, volume = {36}, year = {2015}, month = {2015 Oct}, pages = {928-30}, abstract = {

Here, we describe an overview and update on GeneMatcher (http://www.genematcher.org), a freely accessible Web-based tool developed as part of the Baylor-Hopkins Center for Mendelian Genomics. We created GeneMatcher with the goal of identifying additional individuals with rare phenotypes who had variants in the same candidate disease gene. We also wanted to facilitate connections to basic scientists working on orthologous genes in model systems with the goal of connecting their work to human Mendelian phenotypes. Meeting these goals will enhance the identification of novel Mendelian genes. Launched in September, 2013, GeneMatcher now has 2,178 candidate genes from 486 submitters spread across 38 countries entered in the database (June 1, 2015). GeneMatcher is also part of the Matchmaker Exchange (http://matchmakerexchange.org/) with an Application Programing Interface enabling submitters to query other databases of genetic variants and phenotypes without having to create accounts and data entries in multiple systems.

}, keywords = {Computational Biology, Databases, Genetic, Genetic Predisposition to Disease, Genetic Variation, Humans, Information Dissemination, Phenotype, Rare Diseases, Software, User-Computer Interface, Web Browser}, issn = {1098-1004}, doi = {10.1002/humu.22844}, author = {Sobreira, Nara and Schiettecatte, Fran{\c c}ois and Valle, David and Hamosh, Ada} } @article {131, title = {The Matchmaker Exchange: a platform for rare disease gene discovery.}, journal = {Hum Mutat}, volume = {36}, year = {2015}, month = {2015 Oct}, pages = {915-21}, abstract = {

There are few better examples of the need for data sharing than in the rare disease community, where patients, physicians, and researchers must search for "the needle in a haystack" to uncover rare, novel causes of disease within the genome. Impeding the pace of discovery has been the existence of many small siloed datasets within individual research or clinical laboratory databases and/or disease-specific organizations, hoping for serendipitous occasions when two distant investigators happen to learn they have a rare phenotype in common and can "match" these cases to build evidence for causality. However, serendipity has never proven to be a reliable or scalable approach in science. As such, the Matchmaker Exchange (MME) was launched to provide a robust and systematic approach to rare disease gene discovery through the creation of a federated network connecting databases of genotypes and rare phenotypes using a common application programming interface (API). The core building blocks of the MME have been defined and assembled. Three MME services have now been connected through the API and are available for community use. Additional databases that support internal matching are anticipated to join the MME network as it continues to grow.

}, keywords = {Database Management Systems, Databases, Genetic, Genetic Association Studies, Genetic Predisposition to Disease, Humans, Information Dissemination, Rare Diseases, Software}, issn = {1098-1004}, doi = {10.1002/humu.22858}, author = {Philippakis, Anthony A and Azzariti, Danielle R and Beltran, Sergi and Brookes, Anthony J and Brownstein, Catherine A and Brudno, Michael and Brunner, Han G and Buske, Orion J and Carey, Knox and Doll, Cassie and Dumitriu, Sergiu and Dyke, Stephanie O M and den Dunnen, Johan T and Firth, Helen V and Gibbs, Richard A and Girdea, Marta and Gonzalez, Michael and Haendel, Melissa A and Hamosh, Ada and Holm, Ingrid A and Huang, Lijia and Hurles, Matthew E and Hutton, Ben and Krier, Joel B and Misyura, Andriy and Mungall, Christopher J and Paschall, Justin and Paten, Benedict and Robinson, Peter N and Schiettecatte, Fran{\c c}ois and Sobreira, Nara L and Swaminathan, Ganesh J and Taschner, Peter E and Terry, Sharon F and Washington, Nicole L and Z{\"u}chner, Stephan and Boycott, Kym M and Rehm, Heidi L} } @article {136, title = {The Matchmaker Exchange API: automating patient matching through the exchange of structured phenotypic and genotypic profiles.}, journal = {Hum Mutat}, volume = {36}, year = {2015}, month = {2015 Oct}, pages = {922-7}, 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 = {Algorithms, Computational Biology, Databases, Genetic, Genetic Predisposition to Disease, Genotype, Humans, Information Dissemination, Phenotype, Rare Diseases, Web Browser}, issn = {1098-1004}, doi = {10.1002/humu.22850}, author = {Buske, Orion J and Schiettecatte, Fran{\c c}ois and Hutton, Benjamin and Dumitriu, Sergiu and Misyura, Andriy and Huang, Lijia and Hartley, Taila and Girdea, Marta and Sobreira, Nara and Mungall, Chris and Brudno, Michael} } @article {193, title = {New tools for Mendelian disease gene identification: PhenoDB variant analysis module; and GeneMatcher, a web-based tool for linking investigators with an interest in the same gene.}, journal = {Hum Mutat}, volume = {36}, year = {2015}, month = {2015 Apr}, pages = {425-31}, abstract = {

Identifying the causative variant from among the thousands identified by whole-exome sequencing or whole-genome sequencing is a formidable challenge. To make this process as efficient and flexible as possible, we have developed a Variant Analysis Module coupled to our previously described Web-based phenotype intake tool, PhenoDB (http://researchphenodb.net and http://phenodb.org). When a small number of candidate-causative variants have been identified in a study of a particular patient or family, a second, more difficult challenge becomes proof of causality for any given variant. One approach to this problem is to find other cases with a similar phenotype and mutations in the same candidate gene. Alternatively, it may be possible to develop biological evidence for causality, an approach that is assisted by making connections to basic scientists studying the gene of interest, often in the setting of a model organism. Both of these strategies benefit from an open access, online site where individual clinicians and investigators could post genes of interest. To this end, we developed GeneMatcher (http://genematcher.org), a freely accessible Website that enables connections between clinicians and researchers across the world who share an interest in the same gene(s).

}, keywords = {Computational Biology, Databases, Genetic, Genetic Association Studies, Genetic Diseases, Inborn, Genetic Variation, Genomics, Internet, Phenotype, Software, Web Browser}, issn = {1098-1004}, doi = {10.1002/humu.22769}, author = {Sobreira, Nara and Schiettecatte, Fran{\c c}ois and Boehm, Corinne and Valle, David and Hamosh, Ada} }