The RD-Connect Genome-Phenome Analysis Platform: Accelerating diagnosis, research, and gene discovery for rare diseases
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. ; We acknowledge the support of the developers of PhenoTips, which was used in the past by RD-Connect and NeurOmics as the primary tool to collate phenotypic data. We would also like to thank the leaders and members of the Instituto Nacional de Bioinformática (INB) and ELIXIR for their support and collaboration throughout the years. RD-Connect (RD-Connect, an integrated platform connecting registries, biobanks, and clinical bioinformatics) received funding from the Seventh Framework (FP7) Programme of the European Union under grant agreement No 305444. Data were analyzed using the RD-Connect GPAP, which received funding from EU ...