↓ Skip to main content

Properties of Consensus Methods for Inferring Species Trees from Gene Trees

Overview of attention for article published in Systematic Biology, February 2009
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (84th percentile)

Mentioned by

twitter
3 X users
wikipedia
1 Wikipedia page
q&a
1 Q&A thread

Readers on

mendeley
213 Mendeley
citeulike
3 CiteULike
connotea
1 Connotea
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Article details
Title
Properties of Consensus Methods for Inferring Species Trees from Gene Trees
Published in
Systematic Biology, February 2009
DOI 10.1093/sysbio/syp008
Pubmed ID
Authors
Abstract

Consensus methods provide a useful strategy for summarizing information from a collection of gene trees. An important application of consensus methods is to combine gene trees to estimate a species tree. To investigate the theoretical properties of consensus trees that would be obtained from large numbers of loci evolving according to a basic evolutionary model, we construct consensus trees from rooted gene trees that occur in proportion to gene-tree probabilities derived from coalescent theory. We consider majority-rule, rooted triple (R(*)), and greedy consensus trees obtained from known, rooted gene trees, both in the asymptotic case as numbers of gene trees approach infinity and for finite numbers of genes. Our results show that for some combinations of species-tree branch lengths, increasing the number of independent loci can make the rooted majority-rule consensus tree more likely to be at least partially unresolved. However, the probability that the R(*) consensus tree has the species-tree topology approaches 1 as the number of gene trees approaches infinity. Although the greedy consensus algorithm can be the quickest to converge on the correct species-tree topology when increasing the number of gene trees, it can also be positively misleading. The majority-rule consensus tree is not a misleading estimator of the species-tree topology, and the R(*) consensus tree is a statistically consistent estimator of the species-tree topology. Our results therefore suggest a method for using multiple loci to infer the species-tree topology, even when it is discordant with the most likely gene tree.

Login to access the Attention Digest and the Sentiment Analysis related to this output.

Timeline Attention over time Attention Score history
Login to access the full charts related to this output.
Activity
Login to access the full charts related to this output.
X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 213 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Login to view Mendeley reader trends over time.

Geographical breakdown

Geographical breakdown
Country Count As %
United States 12 6%
Spain 4 2%
Germany 2 <1%
Canada 2 <1%
Brazil 2 <1%
Turkey 1 <1%
New Zealand 1 <1%
United Kingdom 1 <1%
Chile 1 <1%
Other 2 <1%
Unknown 185 87%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 59 28%
Student > Ph. D. Student 44 21%
Professor > Associate Professor 20 9%
Student > Master 17 8%
Professor 14 7%
Other 43 20%
Unknown 16 8%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 136 64%
Biochemistry, Genetics and Molecular Biology 15 7%
Computer Science 13 6%
Mathematics 11 5%
Environmental Science 6 3%
Other 14 7%
Unknown 18 8%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 05 December 2023.
All research outputs
#6,032,119
of 29,212,704 outputs
Outputs from Systematic Biology
#697
of 1,938 outputs
Outputs of similar age
#32,392
of 209,195 outputs
Outputs of similar age from Systematic Biology
#1
of 3 outputs
Altmetric has tracked 29,212,704 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,938 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.1. This one has gotten more attention than average, scoring higher than 63% 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 209,195 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 84% of its contemporaries.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them