‘Quartet’ is an R package that calculates the Quartet distance between two trees: a measure of their similarity based on the number of shared four-taxon subtrees.
The package uses the tqDist algorithm. Unlike many other implementations, it distinguishes between quartets that are contradicted by one tree, and quartets that are simply absent due to a lack of resolution ( i.e. the presence of polytomies). ‘Quartet’ makes this distinction in both the quartet metric (function QuartetStatus()) and the partition metric (i.e. Robinson-Foulds distance; function SplitStatus()).
Using the package
Install and load the library from CRAN as follows:
install.packages('Quartet')
library('Quartet')If you’re feeling brave, you can install the development version thus:
if(!require(devtools)) install.packages("devtools") devtools::install_github('ms609/Quartet')
You will need Rtools installed in order to build the development version from source.
View the function reference and basic usage instructions.
Known limitations
Quartet supports trees with up to 477 leaves. Larger trees contain more quartets than can be represented by R’s signed 32-bit integers.
The underlying ‘tqDist’ library may handle trees with up to 568 leaves, and 64-bit integer representations could increase this number further.
Making either of these improvements within the R package would require substantial additional work, but could be implemented – do file an issue if this would be useful to you.
References
Brodal G.S., Fagerberg R., Pedersen C.N.S. 2004. Computing the quartet distance between evolutionary trees in time O(n log n). Algorithmica. 38:377–395.
Estabrook G.F., McMorris F.R., Meacham C.A. 1985. Comparison of undirected phylogenetic trees based on subtrees of four evolutionary units. Syst. Zool. 34:193–200.
Robinson D.F., Foulds L.R. 1981. Comparison of phylogenetic trees. Math. Biosci. 53:131–147.
Sand A., Holt M.K., Johansen J., Brodal G.S., Mailund T., Pedersen C.N.S. 2014. tqDist: a library for computing the quartet and triplet distances between binary or general trees. Bioinformatics. 30:2079–2080. https://doi.org/10.1093/bioinformatics/btu157
Smith, M.R. (2019) Bayesian and parsimony approaches reconstruct informative trees from simulated morphological datasets. Biol. Lett. 15:20180632. https://doi.org/10.1098/rsbl.2018.0632
Steel, M. and Penny, D. Distributions of tree comparison metrics: some new results. Syst. Biol. (1993) 42 (2): 126-141. https://doi.org/10.1093/sysbio/42.2.126
Please note that the ‘Quartet’ project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
