Griffiths, Emma J., Timme, Ruth E, Mendes, Catarina Inês, Page, Andrew J., Alikhan, Nabil-Fareed, Fornika, Dan, Maguire, Finlay, Campos, Josefina, Park, Daniel, Olawoye, Idowu B., Oluniyi, Paul E, Anderson, Dominique, Christoffels, Alan, da Silva, Anders Gonçalves, Cameron, Rhiannon, Dooley, Damion, Katz, Lee S., Black, Allison, Karsch-Mizrachi, Ilene, Barrett, Tanya, Johnston, Anjanette, Connor, Thomas R. ORCID: https://orcid.org/0000-0003-2394-6504, Nicholls, Samuel M., Witney, Adam A, Tyson, Gregory H., Tausch, Simon H., Raphenya, Amogelang R., Alcock, Brian, Aanensen, David M., Hodcroft, Emma, Hsiao, William W. L., Vasconcelos, Ana Tereza R. and MacCannell, Duncan R. 2022. Future-proofing and maximizing the utility of metadata: The PHA4GE SARS-CoV-2 contextual data specification package. GigaScience 11 , giac003. 10.1093/gigascience/giac003 |
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Abstract
Background The Public Health Alliance for Genomic Epidemiology (PHA4GE) (https://pha4ge.org) is a global coalition that is actively working to establish consensus standards, document and share best practices, improve the availability of critical bioinformatics tools and resources, and advocate for greater openness, interoperability, accessibility, and reproducibility in public health microbial bioinformatics. In the face of the current pandemic, PHA4GE has identified a need for a fit-for-purpose, open-source SARS-CoV-2 contextual data standard. Results As such, we have developed a SARS-CoV-2 contextual data specification package based on harmonizable, publicly available community standards. The specification can be implemented via a collection template, as well as an array of protocols and tools to support both the harmonization and submission of sequence data and contextual information to public biorepositories. Conclusions Well-structured, rich contextual data add value, promote reuse, and enable aggregation and integration of disparate datasets. Adoption of the proposed standard and practices will better enable interoperability between datasets and systems, improve the consistency and utility of generated data, and ultimately facilitate novel insights and discoveries in SARS-CoV-2 and COVID-19. The package is now supported by the NCBI’s BioSample database.
Item Type: | Article |
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Date Type: | Published Online |
Status: | Published |
Schools: | Biosciences |
Additional Information: | This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) |
Publisher: | Oxford University Press |
ISSN: | 2047-217X |
Date of First Compliant Deposit: | 28 February 2022 |
Date of Acceptance: | 7 January 2022 |
Last Modified: | 19 May 2023 04:24 |
URI: | https://orca.cardiff.ac.uk/id/eprint/147841 |
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