@article {511, title = {matchbox: An open-source tool for patient matching via the Matchmaker Exchange.}, journal = {Hum Mutat}, volume = {39}, year = {2018}, month = {2018 Dec}, pages = {1827-1834}, abstract = {

Rare disease investigators constantly face challenges in identifying additional cases to build evidence for gene-disease causality. The Matchmaker Exchange (MME) addresses this limitation by providing a mechanism for matching patients across genomic centers via a federated network. The MME has revolutionized searching for additional cases by making it possible to query across institutional boundaries, so that what was once a laborious and manual process of contacting researchers is now automated and computable. However, while the MME network is beginning to scale, the growth of additional nodes is limited by the lack of easy-to-use solutions that can be implemented by any rare disease database owner, even one without significant software engineering resources. Here, we describe matchbox, which is an open-source, platform-independent, portable bridge between any given rare disease genomic center and the MME network, which has already led to novel gene discoveries. We also describe how matchbox greatly reduces the barrier to participation by overcoming challenges for new databases to join the MME.

}, issn = {1098-1004}, doi = {10.1002/humu.23655}, author = {Arachchi, Harindra and Wojcik, Monica H and Weisburd, Benjamin and Jacobsen, Julius O B and Valkanas, Elise and Baxter, Samantha and Byrne, Alicia B and O{\textquoteright}Donnell-Luria, Anne H and Haendel, Melissa and Smedley, Damian and MacArthur, Daniel G and Philippakis, Anthony A and Rehm, Heidi L} } @article {428, title = {"Matching" consent to purpose: The example of the Matchmaker Exchange.}, journal = {Hum Mutat}, volume = {38}, year = {2017}, month = {2017 10}, pages = {1281-1285}, abstract = {

The Matchmaker Exchange (MME) connects rare disease clinicians and researchers to facilitate the sharing of data from undiagnosed patients for the purpose of novel gene discovery. Such sharing raises the odds that two or more similar patients with candidate genes in common may be found, thereby allowing their condition to be more readily studied and understood. Consent considerations for data sharing in MME included both the ethical and legal differences between clinical and research settings and the level of privacy risk involved in sharing varying amounts of rare disease patient data to enable patient matches. In this commentary, we discuss these consent considerations and the resulting MME Consent Policy as they may be relevant to other international data sharing initiatives.

}, keywords = {Databases, Genetic, Genetic Association Studies, Genetic Diseases, Inborn, Genomics, Humans, Information Dissemination, Patient Selection, Physicians, Rare Diseases, Research Personnel, Translational Medical Research}, issn = {1098-1004}, doi = {10.1002/humu.23278}, author = {Dyke, Stephanie O M and Knoppers, Bartha M and Hamosh, Ada and Firth, Helen V and Hurles, Matthew and Brudno, Michael and Boycott, Kym M and Philippakis, Anthony A and Rehm, Heidi L} } @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} }