Abstract

The response of the global virus genomics community to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has been unprecedented, with significant advances made towards the ‘real-time’ generation and sharing of SARS-CoV-2 genomic data. The rapid growth in virus genome data production has necessitated the development of new analytical methods that can deal with orders of magnitude of more genomes than previously available. Here, we present and describe Phylogenetic Assignment of Named Global Outbreak Lineages (pangolin), a computational tool that has been developed to assign the most likely lineage to a given SARS-CoV-2 genome sequence according to the Pango dynamic lineage nomenclature scheme. To date, nearly two million virus genomes have been submitted to the web-application implementation of pangolin, which has facilitated the SARS-CoV-2 genomic epidemiology and provided researchers with access to actionable information about the pandemic’s transmission lineages.

Details

Title
Assignment of epidemiological lineages in an emerging pandemic using the pangolin tool
Author
Áine O’Toole 1 ; Scher, Emily 1 ; Underwood, Anthony 2 ; Jackson, Ben 1 ; Hill, Verity 1 ; McCrone, John T 1 ; Colquhoun, Rachel 1 ; Ruis, Chris 3 ; Abu-Dahab, Khalil 2 ; Taylor, Ben 2 ; Yeats, Corin 2 ; Louis du Plessis 4 ; Maloney, Daniel 1 ; Medd, Nathan 1 ; Attwood, Stephen W 4 ; Aanensen, David M 2 ; Holmes, Edward C 5 ; Pybus, Oliver G 4 ; Rambaut, Andrew 1 

 Institute of Evolutionary Biology, University of Edinburgh , Edinburgh EH93FL, UK 
 The Centre for Genomic Pathogen Surveillance, Big Data Institute, University of Oxford , Oxford, Oxfordshire OX3 7LF, UK 
 Department of Medicine, University of Cambridge , Cambridge CB2 0SP, UK 
 Department of Zoology, University of Oxford , Oxford, Oxfordshire OX1 3SZ, UK 
 School of Life and Environmental Sciences and School of Medical Sciences, University of Sydney , Sydney, NSW 2006, Australia 
Publication year
2021
Publication date
2021
Publisher
Oxford University Press
e-ISSN
20571577
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3171771156
Copyright
© The Author(s) 2021. Published by Oxford University Press. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.