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Freely accessible ready to use global infrastructure for SARS-CoV-2 monitoring
Wolfgang Maier; Simon Bray; Marius van den Beek; Dave Bouvier; Nathaniel Coraor; Milad Miladi; Babita Singh; Jordi Rambla De Argila; Dannon Baker; Nathan Roach; Simon Gladman; Frederik Coppens; Darren Martin; Andrew Lonie; Bjorn Gruning; Sergei Kosakovsky Pond; Anton Nekrutenko.
Afiliação
  • Wolfgang Maier; University of Freiburg
  • Simon Bray; University of Freiburg
  • Marius van den Beek; Penn State University
  • Dave Bouvier; Penn State University
  • Nathaniel Coraor; Penn State University
  • Milad Miladi; University of Freiburg
  • Babita Singh; Centre for Genomic Regulation
  • Jordi Rambla De Argila; Centre for Genomic Regulation
  • Dannon Baker; Johns Hopkins University
  • Nathan Roach; GalaxyWorks, LLC
  • Simon Gladman; University of Melbourne
  • Frederik Coppens; Ghent University
  • Darren Martin; University of Cape Town
  • Andrew Lonie; University of Melbourne
  • Bjorn Gruning; University of Freiburg
  • Sergei Kosakovsky Pond; Temple University
  • Anton Nekrutenko; Penn State University
Preprint em Inglês | bioRxiv | ID: ppbiorxiv-437046
ABSTRACT
The COVID-19 pandemic is the first global health crisis to occur in the age of big genomic data.Although data generation capacity is well established and sufficiently standardized, analytical capacity is not. To establish analytical capacity it is necessary to pull together global computational resources and deliver the best open source tools and analysis workflows within a ready to use, universally accessible resource. Such a resource should not be controlled by a single research group, institution, or country. Instead it should be maintained by a community of users and developers who ensure that the system remains operational and populated with current tools. A community is also essential for facilitating the types of discourse needed to establish best analytical practices. Bringing together public computational research infrastructure from the USA, Europe, and Australia, we developed a distributed data analysis platform that accomplishes these goals. It is immediately accessible to anyone in the world and is designed for the analysis of rapidly growing collections of deep sequencing datasets. We demonstrate its utility by detecting allelic variants in high-quality existing SARS-CoV-2 sequencing datasets and by continuous reanalysis of COG-UK data. All workflows, data, and documentation is available at https//covid19.galaxyproject.org.
Licença
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Texto completo: Disponível Coleções: Preprints Base de dados: bioRxiv Tipo de estudo: Experimental_studies Idioma: Inglês Ano de publicação: 2021 Tipo de documento: Preprint
Texto completo: Disponível Coleções: Preprints Base de dados: bioRxiv Tipo de estudo: Experimental_studies Idioma: Inglês Ano de publicação: 2021 Tipo de documento: Preprint
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