Corvò, AlbertoMatalonga, LeslieLaurie, Steven, 1973-Picó-Amador, DanielFernández Callejo, MarcosParamonov, IdaGut, Ivo GlynnePiscia, DavideBeltran, Sergi2023-03-162023-03-162023Corvò 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.2022.1002462666-979Xhttp://hdl.handle.net/10230/56245The 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.application/pdfeng© 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/).info:eu-repo/semantics/articlehttp://dx.doi.org/10.1016/j.xgen.2022.100246Data sharingData visualizationDiagnosisExome analysisFederated infrastructuresGenome analysisRare diseasesRemote data accessStandardsinfo:eu-repo/semantics/openAccess