Publication:
The RD-connect genome-phenome analysis platform: accelerating diagnosis, research, and gene discovery for rare diseases

Date

2022

Authors

Laurie, Steven
Piscia, davide
Matalonga, Leslie
Corvó, Alberto
Fernández-Callejo, Marcos
Garcia-Linares, Carles
Hernandez-Ferrer, Carles
Luengo, Cristina
Martínez, Inés
Papakonstantinou, Anastasios

Director

Publisher

Wiley
Acceso abierto / Sarbide irekia
Artículo / Artikulua
Versión publicada / Argitaratu den bertsioa

Project identifier

European Commission/Horizon 2020 Framework Programme/779257openaire
European Commission/Horizon 2020 Framework Programme/825575openaire
European Commission/Horizon 2020 Framework Programme/676559openaire

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.

Description

Keywords

Data sharing, Data standardization, Diagnostics, Genome analysis, NGS, Patient matchmaking, Rare diseases

Department

Ciencias de la Salud / Osasun Zientziak

Faculty/School

Degree

Doctorate program

item.page.cita

Laurie, S.; Piscia, D.; Matalonga, L.; Corvó, A.; Fernández-Callejo, M.; Garcia-Linares, C.; Hernandez-Ferrer, C.; Luengo, C.; Martínez, I.; Papakonstantinou, A.; Picó-Amador, D.; Protasio, J.; Thompson, R.; Tonda, R.; Bayés, M.; Bullich, G.; Camps-Puchadas, J.; Paramonov, I.; Trotta, J. R.; Alonso-Sánchez, A. M.; Attimonelli, M.; Béroud, C.; Bros-Facer, V.; Buske, O. J.; Cañada-Pallarés, A.; Fernández, J. M.; Hansson, M. G.; Horvath, R.; Jacobsen, J. O. B.; Kaliyaperumal, R.; Lair-Préterre, S.; Licata, L.; Lopes, P.; López-Martín, E.; Mascalzoni, D.; Monaco, L.; Pérez-Jurado, L. A.; Posada-de-la-Paz, M.; Rambla, J.; Rath, A.; Riess, O.; Robinson, P. N.; Salgado, D.; Smedley, D.; Spalding, D.; 't Hoen, P. A. C.; Töpf, A.; Zaharieva, I.; Graessner,, H.; Gut, I. G.; Lochmüller, H.; Beltran, S.. (2022). The RD-connect genome-phenome analysis platform: accelerating diagnosis, research, and gene discovery for rare diseases. Human Mutation. 43,6 717-733 .

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