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Joint visualization of seasonal influenza serology and phylogeny to inform vaccine composition.

Joint visualization of seasonal influenza serology and phylogeny to inform vaccine composition.

Authors :
Lee J
Hadfield J
Black A
Sibley TR
Neher RA
Bedford T
Huddleston J
Source :
Frontiers in bioinformatics [Front Bioinform] 2023 Mar 22; Vol. 3, pp. 1069487. Date of Electronic Publication: 2023 Mar 22 (Print Publication: 2023).
Publication Year :
2023

Abstract

Seasonal influenza vaccines must be updated regularly to account for mutations that allow influenza viruses to escape our existing immunity. A successful vaccine should represent the genetic diversity of recently circulating viruses and induce antibodies that effectively prevent infection by those recent viruses. Thus, linking the genetic composition of circulating viruses and the serological experimental results measuring antibody efficacy is crucial to the vaccine design decision. Historically, genetic and serological data have been presented separately in the form of static visualizations of phylogenetic trees and tabular serological results to identify vaccine candidates. To simplify this decision-making process, we have created an interactive tool for visualizing serological data that has been integrated into Nextstrain's real-time phylogenetic visualization framework, Auspice. We show how the combined interactive visualizations may be used by decision makers to explore the relationships between complex data sets for both prospective vaccine virus selection and retrospectively exploring the performance of vaccine viruses.<br />Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.<br /> (Copyright © 2023 Lee, Hadfield, Black, Sibley, Neher, Bedford and Huddleston.)

Details

Language :
English
ISSN :
2673-7647
Volume :
3
Database :
MEDLINE
Journal :
Frontiers in bioinformatics
Publication Type :
Academic Journal
Accession number :
37035035
Full Text :
https://doi.org/10.3389/fbinf.2023.1069487