RD-Connect: An Integrated Platform Connecting Databases, Registries, Biobanks and Clinical Bioinformatics for Rare Disease Research

Thompson, Rachel; Johnston, Louise; Taruscio, Domenica; Monaco, Lucía; Béroud, Christophe; Gut, Marta; Hansson, Mats; Hoen, Peter-Bram A. ’t; Patrinos, George P.; Dawkins, Hugh; Ensini, Monica; Zatloukal, Kurt; Koubi, David; Heslop, Emma; Paschall, Justin; Paz, Manuel Posada de la; Robinson, Peter N.; Bushby, Kate; Lochmüller, Hanns

doi:10.1007/s11606-014-2908-8

Cited by 169 publications

(163 citation statements)

References 33 publications

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“…For example, many resources within the International Rare Disease Research Consortium participate in the RD Connect platform (Thompson et al, 2014) which has defined the ''disease card''-a metadata object that gives overall information about the individual disease registries, which is then incorporated into a ''disease matrix''. The disease matrix provides aggregate data about what disease variants are in the registry, how many individuals represent each disease, and other high-level descriptive data that allows, for example, researchers to determine if they should approach the registry to request full data access.…”

Section: Overview Of Technical Decisions and Their Justificationmentioning

confidence: 99%

Interoperability and FAIRness through a novel combination of Web technologies

Wilkinson

Verborgh

Santos³

et al. 2017

PeerJ Computer Science

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Data in the life sciences are extremely diverse and are stored in a broad spectrum of repositories ranging from those designed for particular data types (such as KEGG for pathway data or UniProt for protein data) to those that are general-purpose (such as FigShare, Zenodo, Dataverse or EUDAT). These data have widely different levels of sensitivity and security considerations. For example, clinical observations about genetic mutations in patients are highly sensitive, while observations of species diversity are generally not. The lack of uniformity in data models from one repository to another, and in the richness and availability of metadata descriptions, makes integration and analysis of these data a manual, time-consuming task with no scalability. Here we explore a set of resource-oriented Web design patterns for data discovery, accessibility, transformation, and integration that can be implemented by any general-or specialpurpose repository as a means to assist users in finding and reusing their data holdings. We show that by using off-the-shelf technologies, interoperability can be achieved atthe level of an individual spreadsheet cell. We note that the behaviours of this architecture compare favourably to the desiderata defined by the FAIR Data Principles, and can therefore represent an exemplar implementation of those principles. The proposed interoperability design patterns may be used to improve discovery and integration of both new and legacy data, maximizing the utility of all scholarly outputs.

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Section: Overview Of Technical Decisions and Their Justificationmentioning

confidence: 99%

Interoperability and FAIRness through a novel combination of Web technologies

Wilkinson

Verborgh

Santos³

et al. 2017

PeerJ Computer Science

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show abstract

“…However, this approach is limited by the fact that these disorders are often extremely rare, making it difficult for a single clinical research team to connect the disease to the gene. Significant efforts are currently being made to establish international networks for sharing sequencing and phenotypic data in order to accelerate rare myopathy-causing gene discovery and identify the best diagnostic approaches [82].…”

Section: Sequencing and Phenotypic Data Sharingmentioning

confidence: 99%

Clinical massively parallel sequencing for the diagnosis of myopathies

et al. 2015

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“…This project is proceeding in close collaboration with other major European research initiatives, such as RD-Connect [21,22], in order to harmonize and develop common standards for databases and patient registries for rare diseases, and most importantly, to develop clinical bioinformatics solutions, including data-mining and knowledge-discovery tools for the analysis and integration of molecular and clinical data in order to promote the discovery of new disease genes, pathways and therapeutic druggable targets.…”

Section: Current Research Projects Among Gma Membersmentioning

confidence: 99%

Bridging Genomics Research Between Developed and Developing Countries: The Genomic Medicine Alliance

et al. 2014

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The Genomic Medicine Alliance is a global academic research network that aims to establish and strengthen collaborative ties between the various genomic medicine stakeholders. Its focus lies on the translation of scientific research findings into clinical practice. It brings together experts from disciplines including genome informatics, pharmacogenomics, public health genomics, ethics in genomics and health economics, and it is supervised by a 14-member International Scientific Advisory Committee comprising internationally renowned scientists. The Alliance's official journal, Public Health Genomics, offers members a highly respected publication forum for their original research findings. In the short-to-medium term, the Genomic Medicine Alliance hopes to harmonize research activities between developed and developing countries and to organize educational activities in the field of genomic medicine.

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RD-Connect: An Integrated Platform Connecting Databases, Registries, Biobanks and Clinical Bioinformatics for Rare Disease Research

Cited by 169 publications

References 33 publications

Interoperability and FAIRness through a novel combination of Web technologies

Interoperability and FAIRness through a novel combination of Web technologies

Clinical massively parallel sequencing for the diagnosis of myopathies

Bridging Genomics Research Between Developed and Developing Countries: The Genomic Medicine Alliance

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