Back to Search Start Over

The PHA4GE SARS-CoV-2 Contextual Data Specification for Open Genomic Epidemiology

Authors :
Anders Gonçalves da Silva
Emma Griffiths
Ana Tereza Ribeiro de Vasconcelos
Adam A. Witney
Allison Black
Emma B. Hodcroft
Amogelang R. Raphenya
Paul E. Oluniyi
Simon H. Tausch
Finlay Maguire
Thomas R. Connor
Gregory H. Tyson
Samuel M. Nicholls
Ruth Timme
Andrew J. Page
Josefina Campos
Catarina I. Mendes
Duncan MacCannell
Nabil-Fareed Alikhan
Idowu B. Olawoye
Daniel Fornika
Lee S. Katz
Brian Alcock
David M. Aanensen
Alan Christoffels
William W. L. Hsiao
Publication Year :
2020
Publisher :
Preprints, 2020.

Abstract

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 bioinformatic 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 clear and present need for a fit-for-purpose, open source SARS-CoV-2 contextual data standard. As such, we have developed an extension to the INSDC pathogen package, providing a SARS-CoV-2 contextual data specification based on harmonisable, publicly available, community standards. The specification is implementable via a collection template, as well as an array of protocols and tools to support the harmonisation and submission of sequence data and contextual information to public repositories. Well-structured, rich contextual data adds value, promotes reuse, and enables aggregation and integration of disparate data sets. 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.

Details

Language :
English
Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....2c7fd564f5c754a64cab410026d927c3