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TreeKnit: Inferring ancestral reassortment graphs of influenza viruses.
Barrat-Charlaix, Pierre; Vaughan, Timothy G; Neher, Richard A.
Afiliación
  • Barrat-Charlaix P; Biozentrum, Universität Basel, Basel, Switzerland.
  • Vaughan TG; Swiss Institute of Bioinformatics, Basel, Switzerland.
  • Neher RA; Swiss Institute of Bioinformatics, Basel, Switzerland.
PLoS Comput Biol ; 18(8): e1010394, 2022 08.
Article en En | MEDLINE | ID: mdl-35984845
When two influenza viruses co-infect the same cell, they can exchange genome segments in a process known as reassortment. Reassortment is an important source of genetic diversity and is known to have been involved in the emergence of most pandemic influenza strains. However, because of the difficulty in identifying reassortment events from viral sequence data, little is known about their role in the evolution of the seasonal influenza viruses. Here we introduce TreeKnit, a method that infers ancestral reassortment graphs (ARG) from two segment trees. It is based on topological differences between trees, and proceeds in a greedy fashion by finding regions that are compatible in the two trees. Using simulated genealogies with reassortments, we show that TreeKnit performs well in a wide range of settings and that it is as accurate as a more principled bayesian method, while being orders of magnitude faster. Finally, we show that it is possible to use the inferred ARG to better resolve segment trees and to construct more informative visualizations of reassortments.
Asunto(s)

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Orthomyxoviridae / Gripe Humana Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: PLoS Comput Biol Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2022 Tipo del documento: Article País de afiliación: Suiza

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Orthomyxoviridae / Gripe Humana Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: PLoS Comput Biol Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2022 Tipo del documento: Article País de afiliación: Suiza