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A Critical Review on the Use of Support Values in Tree Viewers and Bioinformatics Toolkits

Overview of attention for article published in Molecular Biology and Evolution, March 2017
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

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63 X users

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208 Mendeley
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Title
A Critical Review on the Use of Support Values in Tree Viewers and Bioinformatics Toolkits
Published in
Molecular Biology and Evolution, March 2017
DOI 10.1093/molbev/msx055
Pubmed ID
Authors

Lucas Czech, Jaime Huerta-Cepas, Alexandros Stamatakis

Abstract

Phylogenetic trees are routinely visualized to present and interpret the evolutionary relationships of species. Most empirical evolutionary data studies contain a visualization of the inferred tree with branch support values. Ambiguous semantics in tree file formats can lead to erroneous tree visualizations and therefore to incorrect interpretations of phylogenetic analyses. Here, we discuss problems that arise when displaying branch values on trees after rerooting. Branch values are typically stored as node labels in the widely-used Newick tree format. However, such values are attributes of branches. Storing them as node labels can therefore yield errors when rerooting trees. This depends on the mostly implicit semantics that tools deploy to interpret node labels. We reviewed ten tree viewers and ten bioinformatics toolkits that can display and reroot trees. We found that 14 out of 20 of these tools do not permit users to select the semantics of node labels. Thus, unaware users might obtain incorrect results when rooting trees. We illustrate such incorrect mappings for several test cases and real examples taken from the literature. This review has already led to improvements in eight tools. We suggest tools should provide options that explicitly force users to define the semantics of node labels.

X Demographics

X Demographics

The data shown below were collected from the profiles of 63 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 208 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 <1%
Switzerland 1 <1%
Mexico 1 <1%
Russia 1 <1%
Spain 1 <1%
United States 1 <1%
Unknown 202 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 56 27%
Student > Bachelor 34 16%
Researcher 26 13%
Student > Master 24 12%
Student > Doctoral Student 9 4%
Other 24 12%
Unknown 35 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 90 43%
Biochemistry, Genetics and Molecular Biology 42 20%
Environmental Science 8 4%
Immunology and Microbiology 6 3%
Computer Science 5 2%
Other 11 5%
Unknown 46 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 37. 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 19 August 2021.
All research outputs
#1,120,790
of 25,756,911 outputs
Outputs from Molecular Biology and Evolution
#468
of 5,255 outputs
Outputs of similar age
#22,169
of 323,858 outputs
Outputs of similar age from Molecular Biology and Evolution
#8
of 80 outputs
Altmetric has tracked 25,756,911 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,255 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.9. This one has done particularly well, scoring higher than 91% 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 323,858 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 80 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 90% of its contemporaries.