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

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

doi:10.20944/preprints202008.0220.v1

Cited by 14 publications

(16 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…All genomes, phylogenetic trees, basic metadata are available from the COG-UK consortium website (https://www.cogconsortium.uk/data). For con dentiality reasons, extended metadata 45 (Gri ths et al, 2020) is not publicly available, however some may be available upon request from Public Health England and the University of Cambridge, facilitated by authors.…”

Section: Author Contributionsmentioning

confidence: 99%

Genomic epidemiology of SARS-CoV-2 in a UK university identifies dynamics of transmission

Aggarwal

Warne²,

Jahun³

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

Understanding the drivers for spread of SARS-CoV-2 in higher education settings is important to limit transmission between students, and onward spread into at-risk populations. In this study, we prospectively sequenced 482 SARS-CoV-2 isolates derived from asymptomatic student screening and symptomatic testing of students and staff at the University of Cambridge from 5 October to 6 December 2020. We performed a detailed phylogenetic comparison with 972 isolates from the surrounding community, complemented with epidemiological and contact tracing data, to determine transmission dynamics. After a limited number of viral introductions into the university, the majority of student cases were linked to a single genetic cluster, likely dispersed across the university following social gatherings at a venue outside the university. We identified considerable onward transmission associated with student accommodation and courses; this was effectively contained using local infection control measures and dramatically reduced following a national lockdown. We observed that transmission clusters were largely segregated within the university or within the community. This study highlights key determinants of SARS-CoV-2 transmission and effective interventions in a higher education setting that will inform public health policy during pandemics.

show abstract

Section: Author Contributionsmentioning

confidence: 99%

Genomic epidemiology of SARS-CoV-2 in a UK university identifies dynamics of transmission

Aggarwal

Warne²,

Jahun³

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…There are already several well defined lists of metadata that are recommended for collection, for example submissions to the European Nucleotide Archive suggest following the “ENA virus pathogen reporting standard checklist” (ERC000033), and recently the Public Health Alliance for Genomic Epidemiology (PHA4GE) drafted a specification for sharing contextual data about SARS-CoV-2 genomes to advocate the openness and reusability of generated data sets [7].…”

Section: Resultsmentioning

confidence: 99%

MAJORA: Continuous integration supporting decentralised sequencing for SARS-CoV-2 genomic surveillance

Nicholls

Poplawski

Bull

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

Genomic epidemiology has become an increasingly common tool for epidemic response. Recent technological advances have made it possible to sequence genomes rapidly enough to inform outbreak response, and cheaply enough to justify dense sampling of even large epidemics. With increased availability of sequencing it is possible for agile networks of sequencing facilities to collaborate on the sequencing and analysis of epidemic genomic data.In response to the ongoing SARS-CoV-2 pandemic in the United Kingdom, the COVID-19 Genomics UK (COG-UK) consortium was formed with the aim of rapidly sequencing SARS-CoV-2 genomes as part of a national-scale genomic surveillance strategy. The network consists of universities, academic institutes, regional sequencing centres and the four UK Public Health Agencies.We describe the development and deployment of Majora, an encompassing digital infrastructure to address the challenge of collecting and integrating both genomic sequencing data and sample-associated metadata produced across the COG-UK network. The system was designed and implemented pragmatically to stand up capacity rapidly in a pandemic caused by a novel virus. This approach has underpinned the success of COG-UK, which has rapidly become the leading contributor of SARS-CoV-2 genomes to international databases and has generated over 60,000 sequences to date.

show abstract

“…This success has attracted contributions from the open source community that have allowed us to improve Augur’s functionality, documentation, and test coverage. To facilitate Augur’s continued use as part of wider bioinformatics pipelines in public health, we have committed to work with and contribute to open data standards such as PHA4GE ( Griffiths et al, 2020 ) and follow recommendations for open pathogen genomic analyses ( Black et al, 2020 ). Augur can be installed from PyPI (nextstrain-augur) and Bioconda (augur).…”

Section: Methodsmentioning

confidence: 99%

Augur: a bioinformatics toolkit for phylogenetic analyses of human pathogens

Huddleston¹,

Hadfield²,

Sibley³

et al. 2021

JOSS

Self Cite

171

123

View full text Add to dashboard Cite

Summary and statement of need The analysis of human pathogens requires a diverse collection of bioinformatics tools. These tools include standard genomic and phylogenetic software and custom software developed to handle the relatively numerous and short genomes of viruses and bacteria. Researchers increasingly depend on the outputs of these tools to infer transmission dynamics of human diseases and make actionable recommendations to public health officials ( Black et al., 2020 ; Gardy et al., 2015 ). In order to enable real-time analyses of pathogen evolution, bioinformatics tools must scale rapidly with the number of samples and be flexible enough to adapt to a variety of questions and organisms. To meet these needs, we developed Augur, a bioinformatics toolkit designed for phylogenetic analyses of human pathogens.

show abstract

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

Cited by 14 publications

References 19 publications

Genomic epidemiology of SARS-CoV-2 in a UK university identifies dynamics of transmission

Genomic epidemiology of SARS-CoV-2 in a UK university identifies dynamics of transmission

MAJORA: Continuous integration supporting decentralised sequencing for SARS-CoV-2 genomic surveillance

Augur: a bioinformatics toolkit for phylogenetic analyses of human pathogens

Contact Info

Product

Resources

About