Evidence map›Paper›PMID 27774300›Full record

ArticleVirus evolution2016

Exploring the temporal structure of heterochronous sequences using TempEst (formerly Path-O-Gen).

Andrew Rambaut, Tommy T Lam, Luiz Max Carvalho, Oliver G Pybus

Abstract read
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Article in Virus evolution, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1,505 papers.

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1,505citing papers in PubMed
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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

1,505 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Andrew RambautInstitute of Evolutionary Biology,; Centre for Immunity, Infection and Evolution, University of Edinburgh, Ashworth Laboratories, King's Buildings, Edinburgh EH9 3JT, UK.
Tommy T LamSchool of Public Health, University of Hong Kong, Hong Kong SAR, China and.
Luiz Max CarvalhoInstitute of Evolutionary Biology.
Oliver G PybusDepartment of Zoology, University of Oxford, South Parks Road, Oxford OX1 3PS, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gene sequences sampled at different points in time can be used to infer molecular phylogenies on a natural timescale of months or years, provided that the sequences in question undergo measurable amounts of evolutionary change between sampling times. Data sets with this property are termed heterochronous and have become increasingly common in several fields of biology, most notably the molecular epidemiology of rapidly evolving viruses. Here we introduce the cross-platform software tool, TempEst (formerly known as Path-O-Gen), for the visualization and analysis of temporally sampled sequence data. Given a molecular phylogeny and the dates of sampling for each sequence, TempEst uses an interactive regression approach to explore the association between genetic divergence through time and sampling dates. TempEst can be used to (1) assess whether there is sufficient temporal signal in the data to proceed with phylogenetic molecular clock analysis, and (2) identify sequences whose genetic divergence and sampling date are incongruent. Examination of the latter can help identify data quality problems, including errors in data annotation, sample contamination, sequence recombination, or alignment error. We recommend that all users of the molecular clock models implemented in BEAST first check their data using TempEst prior to analysis.

Indexed as

evolutionary ratemodel selectionmolecular clockphylogenyregression

Identifiers

PMID27774300
PMCPMC4989882

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.