Future-proofing and maximizing the utility of metadata: The PHA4GE SARS-CoV-2 contextual data specification package

• Published in: Gigascience Vol. 11
• Main Authors: 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, 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, MacCannell, Duncan R
• Format: Journal Article
• Language: English
• Published: United States Oxford University Press 16.02.2022
• Subjects: Availability; Best practice; Bioinformatics; COVID-19; Datasets; Epidemiology; Genomics; Humans; Interoperability; Metadata; Microorganisms; Public Health; Reproducibility of Results; SARS-CoV-2; Severe acute respiratory syndrome coronavirus 2; Specifications; Technical Note; genomics; metadata; SARS-CoV-2; data standards; bioinformatics
• ISSN: 2047-217X; 2047-217X
• DOI: 10.1093/gigascience/giac003

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.