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The space of ultrametric phylogenetic trees

Overview of attention for article published in Journal of Theoretical Biology, May 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (80th percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

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Article details
Title
The space of ultrametric phylogenetic trees
Published in
Journal of Theoretical Biology, May 2016
DOI 10.1016/j.jtbi.2016.05.001
Pubmed ID
Authors
Abstract

The reliability of a phylogenetic inference method from genomic sequence data is ensured by its statistical consistency. Bayesian inference methods produce a sample of phylogenetic trees from the posterior distribution given sequence data. Hence the question of statistical consistency of such methods is equivalent to the consistency of the summary of the sample. More generally, statistical consistency is ensured by the tree space used to analyse the sample. In this paper, we consider two standard parameterisations of phylogenetic trees used in evolutionary models: using inter-coalescent intervals and using absolute times of divergence events. For each of these parameterisations we introduce a natural metric space on ultrametric phylogenetic trees. We compare the introduced spaces with existing models of tree space and formulate several formal requirements that a metric space on phylogenetic trees must possess in order to be a satisfactory space for statistical analysis, and justify them. We show that only a few known constructions of the space of phylogenetic trees satisfy these requirements. However, our results suggest that these basic requirements are not enough to distinguish between the two metric spaces we introduce and that the choice between metric spaces requires additional properties to be considered. Particularly, that the summary tree minimising the square distance to the trees from the sample might be different for different parameterisations. This suggests that further fundamental insight is needed into the problem of statistical consistency of phylogenetic inference methods.

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X Demographics

The data shown below were collected from the profiles of 16 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 46 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 %
United States 1 2%
Brazil 1 2%
Unknown 44 96%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 13 28%
Researcher 9 20%
Student > Master 7 15%
Professor 4 9%
Student > Bachelor 3 7%
Other 5 11%
Unknown 5 11%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 17 37%
Mathematics 9 20%
Computer Science 7 15%
Biochemistry, Genetics and Molecular Biology 4 9%
Engineering 2 4%
Other 1 2%
Unknown 6 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 12 January 2021.
All research outputs
#4,678,648
of 28,064,094 outputs
Outputs from Journal of Theoretical Biology
#519
of 4,081 outputs
Outputs of similar age
#62,634
of 317,780 outputs
Outputs of similar age from Journal of Theoretical Biology
#6
of 74 outputs
Altmetric has tracked 28,064,094 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,081 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. This one has done well, scoring higher than 87% 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 317,780 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 80% of its contemporaries.
We're also able to compare this research output to 74 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.