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

Overview of attention for article published in Bioinformatics, July 2016
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Article details
Title
Estimating evolutionary rates using time-structured data: a general comparison of phylogenetic methods
Published in
Bioinformatics, July 2016
DOI 10.1093/bioinformatics/btw421
Pubmed ID
Authors
Abstract

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. 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. [email protected], [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 82 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 82 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 17 21%
Researcher 16 20%
Student > Master 12 15%
Student > Bachelor 8 10%
Student > Postgraduate 5 6%
Other 10 12%
Unknown 14 17%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 34 41%
Biochemistry, Genetics and Molecular Biology 11 13%
Computer Science 6 7%
Immunology and Microbiology 5 6%
Medicine and Dentistry 3 4%
Other 4 5%
Unknown 19 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 April 2020.
All research outputs
#8,471,961
of 27,263,779 outputs
Outputs from Bioinformatics
#6,530
of 13,247 outputs
Outputs of similar age
#109,306
of 330,925 outputs
Outputs of similar age from Bioinformatics
#148
of 249 outputs
Altmetric has tracked 27,263,779 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 13,247 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.1. This one has gotten more attention than average, scoring higher than 50% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 330,925 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.
We're also able to compare this research output to 249 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.