Laurie, S;
Piscia, D;
Matalonga, L;
Corvó, A;
Fernández-Callejo, M;
Garcia-Linares, C;
Hernandez-Ferrer, C;
... Beltran, S; + view all
(2022)
The RD-Connect Genome-Phenome Analysis Platform: Accelerating diagnosis, research, and gene discovery for rare diseases.
Human Mutation: Variation, Informatics and Disease
, 43
(6)
pp. 717-733.
10.1002/humu.24353.
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Abstract
Rare disease patients are more likely to receive a rapid molecular diagnosis nowadays thanks to the wide adoption of next generation sequencing. However, many cases remain undiagnosed even after exome or genome analysis, because the methods used missed the molecular cause in a known gene, or a novel causative gene could not be identified and/or confirmed. To address these challenges, the RD-Connect Genome-Phenome Analysis Platform (GPAP) facilitates the collation, discovery, sharing and analysis of standardised genome-phenome data within a collaborative environment. Authorised clinicians and researchers submit pseudonymised phenotypic profiles encoded using the Human Phenotype Ontology, and raw genomic data which is processed through a standardised pipeline. After an optional embargo period, the data is shared with other platform users, with the objective that similar cases in the system and queries from peers may help diagnose the case. Additionally, the platform enables bidirectional discovery of similar cases in other databases from the Matchmaker Exchange network. To facilitate genome-phenome analysis and interpretation by clinical researchers, the RD-Connect GPAP provides a powerful user-friendly interface and leverages tens of information sources. As a result, the resource has already helped diagnose hundreds of rare disease patients and discover new disease causing genes.
| Type: | Article |
|---|---|
| Title: | The RD-Connect Genome-Phenome Analysis Platform: Accelerating diagnosis, research, and gene discovery for rare diseases |
| Location: | United States |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1002/humu.24353 |
| Publisher version: | https://doi.org/10.1002/humu.24353 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Rare diseases, genome analysis, data sharing, patient matchmaking, NGS, diagnostics, data standardization |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health > Developmental Neurosciences Dept UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10146646 |
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