Data Proliferation, Reconciliation, and Synthesis in Viral Ecology
Author(s) -
Rory Gibb,
Gregory F. Albery,
Daniel J. Becker,
Liam Brierley,
Ryan Connor,
Tad Dallas,
Evan A. Eskew,
Maxwell J. Farrell,
Angela L. Rasmussen,
Sadie J. Ryan,
Amy R. Sweeny,
Colin J. Carlson,
Timothée Poisot
Publication year - 2021
Publication title -
bioscience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.761
H-Index - 209
eISSN - 1525-3244
pISSN - 0006-3568
DOI - 10.1093/biosci/biab080
Subject(s) - human virome , host (biology) , ecology , macroecology , biology , evolutionary ecology , evolutionary biology , data science , computer science , metagenomics , biodiversity , genetics , gene
The fields of viral ecology and evolution are rapidly expanding, motivated in part by concerns around emerging zoonoses. One consequence is the proliferation of host–virus association data, which underpin viral macroecology and zoonotic risk prediction but remain fragmented across numerous data portals. In the present article, we propose that synthesis of host–virus data is a central challenge to characterize the global virome and develop foundational theory in viral ecology. To illustrate this, we build an open database of mammal host–virus associations that reconciles four published data sets. We show that this offers a substantially richer view of the known virome than any individual source data set but also that databases such as these risk becoming out of date as viral discovery accelerates. We argue for a shift in practice toward the development, incremental updating, and use of synthetic data sets in viral ecology, to improve replicability and facilitate work to predict the structure and dynamics of the global virome.
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