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Data proliferation, reconciliation, and synthesis in viral ecology

Rory Gibb, View ORCID ProfileGregory F. Albery, View ORCID ProfileDaniel J. Becker, Liam Brierley, Ryan Connor, Tad A. Dallas, View ORCID ProfileEvan A. Eskew, Maxwell J. Farrell, Angela L. Rasmussen, View ORCID ProfileSadie J. Ryan, Amy Sweeny, Colin J. Carlson, View ORCID ProfileTimothée Poisot
doi: https://doi.org/10.1101/2021.01.14.426572
Rory Gibb
1Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK
2Centre on Climate Change and Planetary Health, London School of Hygiene and Tropical Medicine, London, UK
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  • For correspondence: rory.j.gibb@gmail.com colin.carlson@georgetown.edu
Gregory F. Albery
3Department of Biology, Georgetown University, Washington DC, USA
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Daniel J. Becker
4Department of Biology, University of Oklahoma, Norman OK, USA
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Liam Brierley
5Department of Health Data Science, University of Liverpool, Liverpool, UK
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Ryan Connor
6National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
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Tad A. Dallas
7Department of Biological Sciences, Louisiana State University, Baton Rouge, LA, 70806 USA
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Evan A. Eskew
8Department of Biology, Pacific Lutheran University, Tacoma WA, USA
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Maxwell J. Farrell
9Department of Ecology & Evolutionary Biology, University of Toronto, Toronto, Ontario, Canada
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Angela L. Rasmussen
10Vaccine Infectious Disease Organization and International Vaccine Centre, University of Saskatchewan, Saskatoon, Canada
15Center for Global Health Science and Security, Georgetown University Medical Center, Georgetown University, Washington, D.C., U.S.A.
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Sadie J. Ryan
11Quantitative Disease Ecology and Conservation (QDEC) Lab, Department of Geography, University of Florida, Gainesville, FL 32601
12Emerging Pathogens Institute, University of Florida, Gainesville, FL 32611
13College of Life Sciences, University of KwaZulu Natal, Durban, 4041, South Africa
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Amy Sweeny
14Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
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Colin J. Carlson
15Center for Global Health Science and Security, Georgetown University Medical Center, Georgetown University, Washington, D.C., U.S.A.
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  • For correspondence: rory.j.gibb@gmail.com colin.carlson@georgetown.edu
Timothée Poisot
16Université de Montréal, Département de Sciences Biologiques, Montréal QC, Canada
17Québec Centre for Biodiversity Sciences, Montréal QC, Canada
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Abstract

The fields of viral ecology and evolution have rapidly expanded in the last two decades, driven by technological improvements, and motivated by efforts to discover potentially zoonotic wildlife viruses under the rubric of pandemic prevention. One consequence has been a massive proliferation of host-virus association data, which comprise the backbone of research in viral macroecology and zoonotic risk prediction. These data remain fragmented across numerous data portals and projects, each with their own scope, structure, and reporting standards. Here, we propose that synthesis of host-virus association data is a central challenge to improve our understanding of the global virome and develop foundational theory in viral ecology. To illustrate this, we build an open reconciled mammal-virus database from four key published datasets, applying a standardized taxonomy and metadata. We show that reconciling these datasets provides a substantially richer view of the mammal virome than that offered by any one individual database. We argue for a shift in best practice towards the incremental development and use of synthetic datasets in viral ecology research, both to improve comparability and replicability across studies, and to facilitate future efforts to use machine learning to predict the structure and dynamics of the global virome.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • Author biography: All the authors are members of the Viral Emergence Research Initiative (VERENA) consortium, a global scientific collaboration to predict which viruses could infect humans, which animals host them, and where they could emerge.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted January 16, 2021.
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Data proliferation, reconciliation, and synthesis in viral ecology
Rory Gibb, Gregory F. Albery, Daniel J. Becker, Liam Brierley, Ryan Connor, Tad A. Dallas, Evan A. Eskew, Maxwell J. Farrell, Angela L. Rasmussen, Sadie J. Ryan, Amy Sweeny, Colin J. Carlson, Timothée Poisot
bioRxiv 2021.01.14.426572; doi: https://doi.org/10.1101/2021.01.14.426572
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Data proliferation, reconciliation, and synthesis in viral ecology
Rory Gibb, Gregory F. Albery, Daniel J. Becker, Liam Brierley, Ryan Connor, Tad A. Dallas, Evan A. Eskew, Maxwell J. Farrell, Angela L. Rasmussen, Sadie J. Ryan, Amy Sweeny, Colin J. Carlson, Timothée Poisot
bioRxiv 2021.01.14.426572; doi: https://doi.org/10.1101/2021.01.14.426572

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