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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 principales: Corvò, Alberto, Matalonga, Leslie, Spalding, Dylan, Senf, Alexander, Laurie, Steven, Picó-Amador, Daniel, Fernandez-Callejo, Marcos, Paramonov, Ida, Romero, Anna Foix, Garcia-Rios, Emilio, Ciges, Jorge Izquierdo, Mohan, Anand, Thomas, Coline, Silva Valencia, Andres Felipe, Halmagyi, Csaba, Freeberg, Mallory Ann, Töpf, Ana, Horvath, Rita, Saunders, Gary, Gut, Ivo, Keane, Thomas, Piscia, Davide, Beltran, Sergi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9932977/
https://www.ncbi.nlm.nih.gov/pubmed/36819661
http://dx.doi.org/10.1016/j.xgen.2022.100246
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author Corvò, Alberto
Matalonga, Leslie
Spalding, Dylan
Senf, Alexander
Laurie, Steven
Picó-Amador, Daniel
Fernandez-Callejo, Marcos
Paramonov, Ida
Romero, Anna Foix
Garcia-Rios, Emilio
Ciges, Jorge Izquierdo
Mohan, Anand
Thomas, Coline
Silva Valencia, Andres Felipe
Halmagyi, Csaba
Freeberg, Mallory Ann
Töpf, Ana
Horvath, Rita
Saunders, Gary
Gut, Ivo
Keane, Thomas
Piscia, Davide
Beltran, Sergi
author_facet Corvò, Alberto
Matalonga, Leslie
Spalding, Dylan
Senf, Alexander
Laurie, Steven
Picó-Amador, Daniel
Fernandez-Callejo, Marcos
Paramonov, Ida
Romero, Anna Foix
Garcia-Rios, Emilio
Ciges, Jorge Izquierdo
Mohan, Anand
Thomas, Coline
Silva Valencia, Andres Felipe
Halmagyi, Csaba
Freeberg, Mallory Ann
Töpf, Ana
Horvath, Rita
Saunders, Gary
Gut, Ivo
Keane, Thomas
Piscia, Davide
Beltran, Sergi
author_sort Corvò, Alberto
collection PubMed
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.
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spelling pubmed-99329772023-02-17 Remote visualization of large-scale genomic alignments for collaborative clinical research and diagnosis of rare diseases Corvò, Alberto Matalonga, Leslie Spalding, Dylan Senf, Alexander Laurie, Steven Picó-Amador, Daniel Fernandez-Callejo, Marcos Paramonov, Ida Romero, Anna Foix Garcia-Rios, Emilio Ciges, Jorge Izquierdo Mohan, Anand Thomas, Coline Silva Valencia, Andres Felipe Halmagyi, Csaba Freeberg, Mallory Ann Töpf, Ana Horvath, Rita Saunders, Gary Gut, Ivo Keane, Thomas Piscia, Davide Beltran, Sergi Cell Genom Technology 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. Elsevier 2023-01-11 /pmc/articles/PMC9932977/ /pubmed/36819661 http://dx.doi.org/10.1016/j.xgen.2022.100246 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Technology
Corvò, Alberto
Matalonga, Leslie
Spalding, Dylan
Senf, Alexander
Laurie, Steven
Picó-Amador, Daniel
Fernandez-Callejo, Marcos
Paramonov, Ida
Romero, Anna Foix
Garcia-Rios, Emilio
Ciges, Jorge Izquierdo
Mohan, Anand
Thomas, Coline
Silva Valencia, Andres Felipe
Halmagyi, Csaba
Freeberg, Mallory Ann
Töpf, Ana
Horvath, Rita
Saunders, Gary
Gut, Ivo
Keane, Thomas
Piscia, Davide
Beltran, Sergi
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
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_short 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
topic Technology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9932977/
https://www.ncbi.nlm.nih.gov/pubmed/36819661
http://dx.doi.org/10.1016/j.xgen.2022.100246
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