Evidence map›Paper›PMID 26630483›Full record

ArticlePloS one2015

Time Clustered Sampling Can Inflate the Inferred Substitution Rate in Foot-And-Mouth Disease Virus Analyses.

Casper-Emil T Pedersen, Peter Frandsen, Sabenzia N Wekesa, Rasmus Heller, Abraham K Sangula, Jemma Wadsworth, Nick J Knowles, Vincent B Muwanika, Hans R Siegismund

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Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

9 authors.

Casper-Emil T PedersenDepartment of Biology, University of Copenhagen, Copenhagen, Denmark.
Peter FrandsenDepartment of Biology, University of Copenhagen, Copenhagen, Denmark.
Sabenzia N WekesaFoot-and-Mouth Disease Laboratory, Embakasi, Nairobi, Kenya.
Rasmus HellerDepartment of Biology, University of Copenhagen, Copenhagen, Denmark.
Abraham K SangulaFoot-and-Mouth Disease Laboratory, Embakasi, Nairobi, Kenya.
Jemma WadsworthThe Pirbright Institute, Ash Road, Pirbright, United Kingdom.
Nick J KnowlesThe Pirbright Institute, Ash Road, Pirbright, United Kingdom.
Vincent B MuwanikaDepartment of Environmental Management, College of Agricultural and Environmental Sciences, Makerere University, Kampala, Uganda.
Hans R SiegismundDepartment of Biology, University of Copenhagen, Copenhagen, Denmark.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the emergence of analytical software for the inference of viral evolution, a number of studies have focused on estimating important parameters such as the substitution rate and the time to the most recent common ancestor (tMRCA) for rapidly evolving viruses. Coupled with an increasing abundance of sequence data sampled under widely different schemes, an effort to keep results consistent and comparable is needed. This study emphasizes commonly disregarded problems in the inference of evolutionary rates in viral sequence data when sampling is unevenly distributed on a temporal scale through a study of the foot-and-mouth (FMD) disease virus serotypes SAT 1 and SAT 2. Our study shows that clustered temporal sampling in phylogenetic analyses of FMD viruses will strongly bias the inferences of substitution rates and tMRCA because the inferred rates in such data sets reflect a rate closer to the mutation rate rather than the substitution rate. Estimating evolutionary parameters from viral sequences should be performed with due consideration of the differences in short-term and longer-term evolutionary processes occurring within sets of temporally sampled viruses, and studies should carefully consider how samples are combined.

Indexed as

Evolution, MolecularAfricaAnimalsDisease OutbreaksFoot-and-Mouth DiseaseFoot-and-Mouth Disease VirusModels, GeneticPhylogenyRecombination, GeneticRNA, ViralSelection, GeneticSequence AlignmentSerotypingTime FactorsRNA, Viral

Identifiers

PMID26630483
PMCPMC4667911

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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.