#' Quartet
#'
#' '[Quartet](https://ms609.github.io/Quartet/)' is an R package that calculates
#' the quartet distance between two trees (Estabrook _et al._ 1985),
#' a measure of their similarity based on the number of shared four-taxon subtrees.
#'
#' The quartet distance outperforms a number of widely used tree distances
#' (e.g. the Robinson–Foulds, path, and rearrangement distances) against a number
#' theoretical and practical measures (Steel & Penny 1993; Smith 2020),
#' and is particularly valuable in the construction of tree spaces (Smith 2021).
#'
#' 'Quartet' uses the 'tqDist' algorithm (Brodal _et al._ 2004; Sand _et al._ 2014).
#' 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; see Smith 2019).
#' 'Quartet' makes this distinction in both the quartet metric (function
#' `QuartetStatus()`) and the partition metric (i.e. Robinson-Foulds distance;
#' function `SplitStatus()`).
#'
#' ## Using Quartet
#'
#' View the [function reference](https://ms609.github.io/Quartet/reference/)
#' and [basic usage instructions](https://ms609.github.io/Quartet/articles/Using-Quartet.html).
#'
#' ## 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](https://github.com/ms609/Quartet/issues/new/) 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.
#'
#' - 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
#'
#' - Smith, M.R. 2020. Information theoretic generalized Robinson–Foulds metrics
#' for comparing phylogenetic trees. Bioinformatics 36:5007–5013.
#' https://dx.doi.org/10.1093/bioinformatics/btaa614/5866976
#'
#' - Smith, M.R. 2022. Robust analysis of phylogenetic tree space.
#' Syst. Biol. 71: 1255-1270.
#' https://dx.doi.org/10.1093/sysbio/syab100
#'
#' - Steel, M. and Penny, D. 1993. Distributions of tree comparison metrics:
#' some new results. Syst. Biol. 42: 126-141.
#' https://doi.org/10.1093/sysbio/42.2.126
#'
#' @keywords internal
"_PACKAGE"
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