@article {722, title = {Enabling Global Clinical Collaborations on Identifiable Patient Data: The Minerva Initiative.}, journal = {Front Genet}, volume = {10}, year = {2019}, month = {2019}, pages = {611}, abstract = {

The clinical utility of computational phenotyping for both genetic and rare diseases is increasingly appreciated; however, its true potential is yet to be fully realized. Alongside the growing clinical and research availability of sequencing technologies, precise deep and scalable phenotyping is required to serve unmet need in genetic and rare diseases. To improve the lives of individuals affected with rare diseases through deep phenotyping, global big data interrogation is necessary to aid our understanding of disease biology, assist diagnosis, and develop targeted treatment strategies. This includes the application of cutting-edge machine learning methods to image data. As with most digital tools employed in health care, there are ethical and data governance challenges associated with using identifiable personal image data. There are also risks with failing to deliver on the patient benefits of these new technologies, the biggest of which is posed by data siloing. The Minerva Initiative has been designed to enable the public good of deep phenotyping while mitigating these ethical risks. Its open structure, enabling collaboration and data sharing between individuals, clinicians, researchers and private enterprise, is key for delivering precision public health.

}, issn = {1664-8021}, doi = {10.3389/fgene.2019.00611}, author = {Nellaker, Christoffer and Alkuraya, Fowzan S and Baynam, Gareth and Bernier, Raphael A and Bernier, Francois P J and Boulanger, Vanessa and Brudno, Michael and Brunner, Han G and Clayton-Smith, Jill and Cogn{\'e}, Benjamin and Dawkins, Hugh J S and deVries, Bert B A and Douzgou, Sofia and Dudding-Byth, Tracy and Eichler, Evan E and Ferlaino, Michael and Fieggen, Karen and Firth, Helen V and FitzPatrick, David R and Gration, Dylan and Groza, Tudor and Haendel, Melissa and Hallowell, Nina and Hamosh, Ada and Hehir-Kwa, Jayne and Hitz, Marc-Phillip and Hughes, Mark and Kini, Usha and Kleefstra, Tjitske and Kooy, R Frank and Krawitz, Peter and K{\"u}ry, S{\'e}bastien and Lees, Melissa and Lyon, Gholson J and Lyonnet, Stanislas and Marcadier, Julien L and Meyn, Stephen and Moslerov{\'a}, Veronika and Politei, Juan M and Poulton, Cathryn C and Raymond, F Lucy and Reijnders, Margot R F and Robinson, Peter N and Romano, Corrado and Rose, Catherine M and Sainsbury, David C G and Schofield, Lyn and Sutton, Vernon R and Turnovec, Marek and Van Dijck, Anke and Van Esch, Hilde and Wilkie, Andrew O M} } @article {508, title = {ClinGen advancing genomic data-sharing standards as a GA4GH driver project.}, journal = {Hum Mutat}, volume = {39}, year = {2018}, month = {2018 11}, pages = {1686-1689}, abstract = {

The Clinical Genome Resource (ClinGen){\textquoteright}s work to develop a knowledge base to support the understanding of genes and variants for use in precision medicine and research depends on robust, broadly applicable, and adaptable technical standards for sharing data and information. To forward this goal, ClinGen has joined with the Global Alliance for Genomics and Health (GA4GH) to support the development of open, freely-available technical standards and regulatory frameworks for secure and responsible sharing of genomic and health-related data. In its capacity as one of the 15 inaugural GA4GH "Driver Projects," ClinGen is providing input on the key standards needs of the global genomics community, and has committed to participate on GA4GH Work Streams to support the development of: (1) a standard model for computer-readable variant representation; (2) a data model for linking variant data to annotations; (3) a specification to enable sharing of genomic variant knowledge and associated clinical interpretations; and (4) a set of best practices for use of phenotype and disease ontologies. ClinGen{\textquoteright}s participation as a GA4GH Driver Project will provide a robust environment to test drive emerging genomic knowledge sharing standards and prove their utility among the community, while accelerating the construction of the ClinGen evidence base.

}, issn = {1098-1004}, doi = {10.1002/humu.23625}, author = {Dolman, Lena and Page, Angela and Babb, Lawrence and Freimuth, Robert R and Arachchi, Harindra and Bizon, Chris and Brush, Matthew and Fiume, Marc and Haendel, Melissa and Hansen, David P and Milosavljevic, Aleksandar and Patel, Ronak Y and Pawliczek, Piotr and Yates, Andrew D and Rehm, Heidi L} } @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} }