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

Corvò, Alberto; Matalonga, Leslie; Laurie, Steven, 1973-; Picó-Amador, Daniel; Fernández Callejo, Marcos; Paramonov, Ida; Gut, Ivo Glynne; Piscia, Davide; Beltran, Sergi

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

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dc.contributor.author Corvò, Alberto
dc.contributor.author Matalonga, Leslie
dc.contributor.author Laurie, Steven, 1973-
dc.contributor.author Picó-Amador, Daniel
dc.contributor.author Fernández Callejo, Marcos
dc.contributor.author Paramonov, Ida
dc.contributor.author Gut, Ivo Glynne
dc.contributor.author Piscia, Davide
dc.contributor.author Beltran, Sergi
dc.date.accessioned 2023-03-16T07:16:35Z
dc.date.available 2023-03-16T07:16:35Z
dc.date.issued 2023
dc.description.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.
dc.description.sponsorship This study was partially funded by ELIXIR Implementation Studies “Remote real-time visualization of human RDs genomics data (RD-Connect) stored at the EGA ELIXIR” (2017–2018), “Integration of ELIXIR-IIB in ELIXIR Rare Disease activities (2017–2018),” and “Rare Disease Infrastructure ELIXIR (2019–2020)” and the Solve-RD project, which received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement no. 779257. Data were analyzed using the RD-Connect Genome-Phenome Analysis Platform, which has received funding from EU projects RD-Connect, Solve-RD, and EJP-RD (grant nos. FP7 305444, H2020 779257, and H2020 825575), Instituto de Salud Carlos III (grant nos. PT13/0001/0044 and PT17/0009/0019; Instituto Nacional de Bioinformática, INB), and ELIXIR Implementation Studies. We acknowledge the support of the Spanish Ministry of Economy, Industry and Competitiveness (MEIC) to the EMBL partnership, the Centro de Excelencia Severo Ochoa, and the CERCA Programme/Generalitat de Catalunya.
dc.format.mimetype application/pdf
dc.identifier.citation Corvò A, Matalonga L, Spalding D, Senf A, Laurie S, Picó-Amador D, et al. Remote visualization of large-scale genomic alignments for collaborative clinical research and diagnosis of rare diseases. Cell Genom. 2023 Jan 11;3(2):100246. DOI: 10.1016/j.xgen.2022.100246
dc.identifier.doi http://dx.doi.org/10.1016/j.xgen.2022.100246
dc.identifier.issn 2666-979X
dc.identifier.uri http://hdl.handle.net/10230/56245
dc.language.iso eng
dc.publisher Elsevier
dc.relation.ispartof Cell Genom. 2023 Jan 11;3(2):100246
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/779257
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/305444
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/825575
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject.keyword Data sharing
dc.subject.keyword Data visualization
dc.subject.keyword Diagnosis
dc.subject.keyword Exome analysis
dc.subject.keyword Federated infrastructures
dc.subject.keyword Genome analysis
dc.subject.keyword Rare diseases
dc.subject.keyword Remote data access
dc.subject.keyword Standards
dc.title Remote visualization of large-scale genomic alignments for collaborative clinical research and diagnosis of rare diseases
dc.type info:eu-repo/semantics/article
dc.type.version info:eu-repo/semantics/publishedVersion

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