Dataset Information

Remote visualization of large-scale genomic alignments for collaborative clinical research and diagnosis of rare diseases.

ABSTRACT: The Solve-RD project objectives include solving undiagnosed rare diseases (RD) through collaborative research on shared genome-phenome datasets. The RD-Connect Genome-Phenome Analysis Platform (GPAP), for data collation and analysis, and the European Genome-Phenome Archive (EGA), for file storage, are two key components of the Solve-RD infrastructure. Clinical researchers can identify candidate genetic variants within the RD-Connect GPAP and, thanks to the developments presented here as part of joint ELIXIR activities, are able to remotely visualize the corresponding alignments stored at the EGA. The Global Alliance for Genomics and Health (GA4GH) htsget streaming application programming interface (API) is used to retrieve alignment slices, which are rendered by an integrated genome viewer (IGV) instance embedded in the GPAP. As a result, it is no longer necessary for over 11,000 datasets to download large alignment files to visualize them locally. This work highlights the advantages, from both the user and infrastructure perspectives, of implementing interoperability standards for establishing federated genomics data networks.

SUBMITTER: Corvo A

PROVIDER: S-EPMC9932977 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

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Remote visualization of large-scale genomic alignments for collaborative clinical research and diagnosis of rare diseases.

Corvò Alberto A Matalonga Leslie L Spalding Dylan D Senf Alexander A Laurie Steven S Picó-Amador Daniel D Fernandez-Callejo Marcos M Paramonov Ida I Romero Anna Foix AF Garcia-Rios Emilio E Ciges Jorge Izquierdo JI Mohan Anand A Thomas Coline C Silva Valencia Andres Felipe AF Halmagyi Csaba C Freeberg Mallory Ann MA Töpf Ana A Horvath Rita R Saunders Gary G Gut Ivo I Keane Thomas T Piscia Davide D Beltran Sergi S

Cell genomics 20230111 2

The Solve-RD project objectives include solving undiagnosed rare diseases (RD) through collaborative research on shared genome-phenome datasets. The RD-Connect Genome-Phenome Analysis Platform (GPAP), for data collation and analysis, and the European Genome-Phenome Archive (EGA), for file storage, are two key components of the Solve-RD infrastructure. Clinical researchers can identify candidate genetic variants within the RD-Connect GPAP and, thanks to the developments presented here as part of ...[more]

PMID: 36819661

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Project description:Background: The Rare Disease Research Partnership (RAinDRoP) was established in 2018 to bring together a wide variety of diverse voices in the rare disease community in Ireland and form a research partnership. This approach enabled clinicians, patients, carers and researchers to work together to identify top research priorities for rare diseases, which focused on a life-course perspective rather than a disease-specific need. Methods: A participatory multiple phase approach was used to identify research priorities for rare diseases. The research process involved three main phases: Phase I, Public Consultation Survey on Research in Rare Diseases in Ireland (PCSRRDI); Phase II, Research Prioritisation Workshop (RPW); Phase III, Follow-up Public Consultation and Prioritisation Survey (FWPCPS). Results: In total, 240 individuals completed the phase I PCSRRDI, which comprised of a cross-section of health care professionals, researchers and people living with rare diseases. One thousand and fifteen statements were collected, reflecting issues and shared challenges in rare diseases. A shortlisting step by step was used to identify any statements that had received a total score of above 50% into 10-12 researchable questions or statements per the theme for the phase II workshop. Phase II was focused on three main themes: (1) Route to Diagnosis, (2) Living with Rare Disease, (3) Integrated and Palliative Care. In total, 62 individuals attended the overall workshop; 42 participated in the prioritisation sessions. A cross-section of health care professionals, researchers and people living with rare diseases were engaged at each workshop. Seventy-five individuals completed the final phase III public ranking by priority responses, and they ranked the top 15 research priorities defined by the multi-stakeholders at the phase II consensus meeting. Conclusions: This study identified priorities for rare diseases research aimed at improving the health and wellbeing of people living with rare diseases.

Dataset Information

Remote visualization of large-scale genomic alignments for collaborative clinical research and diagnosis of rare diseases.

Publications

Remote visualization of large-scale genomic alignments for collaborative clinical research and diagnosis of rare diseases.

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