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

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, a...

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Autores: Corvò, Alberto, Matalonga, Leslie, Laurie, Steven, 1973-, Picó-Amador, Daniel, Fernández Callejo, Marcos, Paramonov, Ida, Gut, Ivo Glynne, Piscia, Davide, Beltran, Sergi
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2023
País:España
Institución:Universitat Pompeu Fabra
Repositorio:Repositorio Digital de la UPF
OAI Identifier:oai:repositori.upf.edu:10230/56245
Acceso en línea:http://hdl.handle.net/10230/56245
http://dx.doi.org/10.1016/j.xgen.2022.100246
Access Level:acceso abierto
Palabra clave:Data sharing
Data visualization
Diagnosis
Exome analysis
Federated infrastructures
Genome analysis
Rare diseases
Remote data access
Standards
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spelling Remote visualization of large-scale genomic alignments for collaborative clinical research and diagnosis of rare diseasesCorvò, AlbertoMatalonga, LeslieLaurie, Steven, 1973-Picó-Amador, DanielFernández Callejo, MarcosParamonov, IdaGut, Ivo GlynnePiscia, DavideBeltran, SergiData sharingData visualizationDiagnosisExome analysisFederated infrastructuresGenome analysisRare diseasesRemote data accessStandardsThe 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.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.Elsevier202320232023info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/10230/56245http://dx.doi.org/10.1016/j.xgen.2022.100246reponame:Repositorio Digital de la UPFinstname:Universitat Pompeu FabraInglésCell Genom. 2023 Jan 11;3(2):100246info:eu-repo/grantAgreement/EC/H2020/779257info:eu-repo/grantAgreement/EC/FP7/305444info:eu-repo/grantAgreement/EC/H2020/825575© 2023 The Authors. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).http://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:repositori.upf.edu:10230/562452026-06-12T07:21:37Z
dc.title.none.fl_str_mv Remote visualization of large-scale genomic alignments for collaborative clinical research and diagnosis of rare diseases
title Remote visualization of large-scale genomic alignments for collaborative clinical research and diagnosis of rare diseases
spellingShingle Remote visualization of large-scale genomic alignments for collaborative clinical research and diagnosis of rare diseases
Corvò, Alberto
Data sharing
Data visualization
Diagnosis
Exome analysis
Federated infrastructures
Genome analysis
Rare diseases
Remote data access
Standards
title_short Remote visualization of large-scale genomic alignments for collaborative clinical research and diagnosis of rare diseases
title_full Remote visualization of large-scale genomic alignments for collaborative clinical research and diagnosis of rare diseases
title_fullStr Remote visualization of large-scale genomic alignments for collaborative clinical research and diagnosis of rare diseases
title_full_unstemmed Remote visualization of large-scale genomic alignments for collaborative clinical research and diagnosis of rare diseases
title_sort Remote visualization of large-scale genomic alignments for collaborative clinical research and diagnosis of rare diseases
dc.creator.none.fl_str_mv Corvò, Alberto
Matalonga, Leslie
Laurie, Steven, 1973-
Picó-Amador, Daniel
Fernández Callejo, Marcos
Paramonov, Ida
Gut, Ivo Glynne
Piscia, Davide
Beltran, Sergi
author Corvò, Alberto
author_facet Corvò, Alberto
Matalonga, Leslie
Laurie, Steven, 1973-
Picó-Amador, Daniel
Fernández Callejo, Marcos
Paramonov, Ida
Gut, Ivo Glynne
Piscia, Davide
Beltran, Sergi
author_role author
author2 Matalonga, Leslie
Laurie, Steven, 1973-
Picó-Amador, Daniel
Fernández Callejo, Marcos
Paramonov, Ida
Gut, Ivo Glynne
Piscia, Davide
Beltran, Sergi
author2_role author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Data sharing
Data visualization
Diagnosis
Exome analysis
Federated infrastructures
Genome analysis
Rare diseases
Remote data access
Standards
topic Data sharing
Data visualization
Diagnosis
Exome analysis
Federated infrastructures
Genome analysis
Rare diseases
Remote data access
Standards
description 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.
publishDate 2023
dc.date.none.fl_str_mv 2023
2023
2023
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10230/56245
http://dx.doi.org/10.1016/j.xgen.2022.100246
url http://hdl.handle.net/10230/56245
http://dx.doi.org/10.1016/j.xgen.2022.100246
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Cell Genom. 2023 Jan 11;3(2):100246
info:eu-repo/grantAgreement/EC/H2020/779257
info:eu-repo/grantAgreement/EC/FP7/305444
info:eu-repo/grantAgreement/EC/H2020/825575
dc.rights.none.fl_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Repositorio Digital de la UPF
instname:Universitat Pompeu Fabra
instname_str Universitat Pompeu Fabra
reponame_str Repositorio Digital de la UPF
collection Repositorio Digital de la UPF
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,811543

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