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Rooting phylogenetic trees under the coalescent model using site pattern probabilities

Overview of attention for article published in BMC Ecology and Evolution, December 2017
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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 (85th percentile)
  • Good Attention Score compared to outputs of the same age and source (73rd percentile)

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Title
Rooting phylogenetic trees under the coalescent model using site pattern probabilities
Published in
BMC Ecology and Evolution, December 2017
DOI 10.1186/s12862-017-1108-7
Pubmed ID
Authors

Yuan Tian, Laura Kubatko

Abstract

Phylogenetic tree inference is a fundamental tool to estimate ancestor-descendant relationships among different species. In phylogenetic studies, identification of the root - the most recent common ancestor of all sampled organisms - is essential for complete understanding of the evolutionary relationships. Rooted trees benefit most downstream application of phylogenies such as species classification or study of adaptation. Often, trees can be rooted by using outgroups, which are species that are known to be more distantly related to the sampled organisms than any other species in the phylogeny. However, outgroups are not always available in evolutionary research. In this study, we develop a new method for rooting species tree under the coalescent model, by developing a series of hypothesis tests for rooting quartet phylogenies using site pattern probabilities. The power of this method is examined by simulation studies and by application to an empirical North American rattlesnake data set. The method shows high accuracy across the simulation conditions considered, and performs well for the rattlesnake data. Thus, it provides a computationally efficient way to accurately root species-level phylogenies that incorporates the coalescent process. The method is robust to variation in substitution model, but is sensitive to the assumption of a molecular clock. Our study establishes a computationally practical method for rooting species trees that is more efficient than traditional methods. The method will benefit numerous evolutionary studies that require rooting a phylogenetic tree without having to specify outgroups.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 29%
Student > Bachelor 3 13%
Researcher 3 13%
Professor > Associate Professor 2 8%
Student > Master 2 8%
Other 5 21%
Unknown 2 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 54%
Biochemistry, Genetics and Molecular Biology 2 8%
Chemical Engineering 1 4%
Unspecified 1 4%
Veterinary Science and Veterinary Medicine 1 4%
Other 3 13%
Unknown 3 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 23 December 2017.
All research outputs
#3,080,344
of 25,382,440 outputs
Outputs from BMC Ecology and Evolution
#816
of 3,714 outputs
Outputs of similar age
#65,218
of 447,047 outputs
Outputs of similar age from BMC Ecology and Evolution
#19
of 72 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,714 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.5. This one has done well, scoring higher than 78% 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 447,047 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 85% of its contemporaries.
We're also able to compare this research output to 72 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.