Literature DB >> 27412094

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

Sebastián Duchêne1,2,3, Jemma L Geoghegan1,2, Edward C Holmes1,2, Simon Y W Ho2.   

Abstract

MOTIVATION: 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.
RESULTS: Although estimates from these three methods were often congruent, this largely relied on the choice of clock model. In particular, relaxed-clock models tended to produce higher rate estimates than methods that assume constant rates. Discrepancies in rate estimates were also associated with high among-lineage rate variation, and phylogenetic and temporal clustering. These results provide insights into the factors that affect the reliability of rate estimates from time-structured sequence data, emphasizing the importance of clock-model testing. CONTACT: sduchene@unimelb.edu.au or garzonsebastian@hotmail.comSupplementary information: Supplementary data are available at Bioinformatics online.
© The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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Year:  2016        PMID: 27412094     DOI: 10.1093/bioinformatics/btw421

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  18 in total

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Authors:  Simon Y W Ho; Amanda X Y Chen; Luana S F Lins; David A Duchêne; Nathan Lo
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5.  Estimating evolutionary rates in giant viruses using ancient genomes.

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Journal:  Virus Evol       Date:  2018-02-27

6.  Inferring demographic parameters in bacterial genomic data using Bayesian and hybrid phylogenetic methods.

Authors:  Sebastian Duchene; David A Duchene; Jemma L Geoghegan; Zoe A Dyson; Jane Hawkey; Kathryn E Holt
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7.  The phylogeography and incidence of multi-drug resistant typhoid fever in sub-Saharan Africa.

Authors:  Se Eun Park; Duy Thanh Pham; Christine Boinett; Vanessa K Wong; Gi Deok Pak; Ursula Panzner; Ligia Maria Cruz Espinoza; Vera von Kalckreuth; Justin Im; Heidi Schütt-Gerowitt; John A Crump; Robert F Breiman; Yaw Adu-Sarkodie; Ellis Owusu-Dabo; Raphaël Rakotozandrindrainy; Abdramane Bassiahi Soura; Abraham Aseffa; Nagla Gasmelseed; Karen H Keddy; Jürgen May; Amy Gassama Sow; Peter Aaby; Holly M Biggs; Julian T Hertz; Joel M Montgomery; Leonard Cosmas; Beatrice Olack; Barry Fields; Nimako Sarpong; Tsiriniaina Jean Luco Razafindrabe; Tiana Mirana Raminosoa; Leon Parfait Kabore; Emmanuel Sampo; Mekonnen Teferi; Biruk Yeshitela; Muna Ahmed El Tayeb; Arvinda Sooka; Christian G Meyer; Ralf Krumkamp; Denise Myriam Dekker; Anna Jaeger; Sven Poppert; Adama Tall; Aissatou Niang; Morten Bjerregaard-Andersen; Sandra Valborg Løfberg; Hye Jin Seo; Hyon Jin Jeon; Jessica Fung Deerin; Jinkyung Park; Frank Konings; Mohammad Ali; John D Clemens; Peter Hughes; Juliet Nsimire Sendagala; Tobias Vudriko; Robert Downing; Usman N Ikumapayi; Grant A Mackenzie; Stephen Obaro; Silvia Argimon; David M Aanensen; Andrew Page; Jacqueline A Keane; Sebastian Duchene; Zoe Dyson; Kathryn E Holt; Gordon Dougan; Florian Marks; Stephen Baker
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9.  A comparison of methods for estimating substitution rates from ancient DNA sequence data.

Authors:  K Jun Tong; David A Duchêne; Sebastián Duchêne; Jemma L Geoghegan; Simon Y W Ho
Journal:  BMC Evol Biol       Date:  2018-05-16       Impact factor: 3.260

10.  Temporal signal and the phylodynamic threshold of SARS-CoV-2.

Authors:  Sebastian Duchene; Leo Featherstone; Melina Haritopoulou-Sinanidou; Andrew Rambaut; Philippe Lemey; Guy Baele
Journal:  Virus Evol       Date:  2020-08-19
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