Estimating evolutionary rates using time-structured data: a general comparison of phylogenetic methods | Zendy

Sebastián Duchêne | Zendy; Jemma L. Geoghegan | Zendy; Edward C. Holmes | Zendy; Simon Y. W. Ho | Zendy

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Estimating evolutionary rates using time-structured data: a general comparison of phylogenetic methods

Author(s) -

Sebastián Duchêne,

Jemma L. Geoghegan,

Edward C. Holmes,

Simon Y. W. Ho

Publication year - 2016

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btw421

Subject(s) - molecular clock , phylogenetic tree , biology , bayesian inference , bayesian probability , inference , rate of evolution , cluster analysis , statistics , mutation rate , bayes' theorem , regression , variation (astronomy) , phylogenetics , evolutionary biology , computer science , genetics , artificial intelligence , mathematics , physics , gene , astrophysics

In rapidly evolving pathogens, including viruses and some bacteria, genetic change can accumulate over short time-frames. Accordingly, their sampling times can be used to calibrate molecular clocks, allowing estimation of evolutionary rates. Methods for estimating rates from time-structured data vary in how they treat phylogenetic uncertainty and rate variation among lineages. We compiled 81 virus data sets and estimated nucleotide substitution rates using root-to-tip regression, least-squares dating and Bayesian inference.

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