The RD-Connect Genome-Phenome Analysis Platform: Accelerating diagnosis, research, and gene discovery for rare diseases.
Authors
Bros-Facer, Virginie
Lair-Préterre, Séverine
Pérez-Jurado, Luis A
Salgado, David
Publication Date
2022-06Journal Title
Hum Mutat
ISSN
1059-7794
Publisher
Hindawi Limited
Volume
43
Issue
6
Pages
717-733
Language
en
Type
Article
This Version
AO
VoR
Metadata
Show full item recordCitation
Laurie, S., Piscia, D., Matalonga, L., Corvó, A., Fernández-Callejo, M., Garcia-Linares, C., Hernandez-Ferrer, C., et al. (2022). The RD-Connect Genome-Phenome Analysis Platform: Accelerating diagnosis, research, and gene discovery for rare diseases.. Hum Mutat, 43 (6), 717-733. https://doi.org/10.1002/humu.24353
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 standardized genome-phenome data within a collaborative environment. Authorized clinicians and researchers submit pseudonymised phenotypic profiles encoded using the Human Phenotype Ontology, and raw genomic data which is processed through a standardized pipeline. After an optional embargo period, the data are 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.
Keywords
NGS, data sharing, data standardization, diagnostics, genome analysis, patient matchmaking, rare diseases, Exome, Genetic Association Studies, Genomics, Humans, Phenotype, Rare Diseases
Sponsorship
European Commission (305121)
Identifiers
humu24353
External DOI: https://doi.org/10.1002/humu.24353
This record's URL: https://www.repository.cam.ac.uk/handle/1810/337352
Rights
Licence:
http://creativecommons.org/licenses/by-nc/4.0/
Statistics
Total file downloads (since January 2020). For more information on metrics see the
IRUS guide.
Recommended or similar items
The current recommendation prototype on the Apollo Repository will be turned off on 03 February 2023. Although the pilot has been fruitful for both parties, the service provider IKVA is focusing on horizon scanning products and so the recommender service can no longer be supported. We recognise the importance of recommender services in supporting research discovery and are evaluating offerings from other service providers. If you would like to offer feedback on this decision please contact us on: support@repository.cam.ac.uk