# treedist: Distances between trees In phangorn: Phylogenetic Reconstruction and Analysis

 treedist R Documentation

## Distances between trees

### Description

`treedist` computes different tree distance methods and `RF.dist` the Robinson-Foulds or symmetric distance. The Robinson-Foulds distance only depends on the topology of the trees. If edge weights should be considered `wRF.dist` calculates the weighted RF distance (Robinson & Foulds 1981). and `KF.dist` calculates the branch score distance (Kuhner & Felsenstein 1994). `path.dist` computes the path difference metric as described in Steel and Penny 1993). `sprdist` computes the approximate SPR distance (Oliveira Martins et al. 2008, de Oliveira Martins 2016).

### Usage

```treedist(tree1, tree2, check.labels = TRUE)

sprdist(tree1, tree2)

SPR.dist(tree1, tree2 = NULL)

RF.dist(tree1, tree2 = NULL, normalize = FALSE, check.labels = TRUE,
rooted = FALSE)

wRF.dist(tree1, tree2 = NULL, normalize = FALSE, check.labels = TRUE,
rooted = FALSE)

KF.dist(tree1, tree2 = NULL, check.labels = TRUE, rooted = FALSE)

path.dist(tree1, tree2 = NULL, check.labels = TRUE, use.weight = FALSE)
```

### Arguments

 `tree1` A phylogenetic tree (class `phylo`) or vector of trees (an object of class `multiPhylo`). See details `tree2` A phylogenetic tree. `check.labels` compares labels of the trees. `normalize` compute normalized RF-distance, see details. `rooted` take bipartitions for rooted trees into account, default is unrooting the trees. `use.weight` use edge.length argument or just count number of edges on the path (default)

### Details

The Robinson-Foulds distance between two trees T_1 and T_2 with n tips is defined as (following the notation Steel and Penny 1993):

d(T_1, T_2) = i(T_1) + i(T_2) - 2v_s(T_1, T_2)

where i(T_1) denotes the number of internal edges and v_s(T_1, T_2) denotes the number of internal splits shared by the two trees. The normalized Robinson-Foulds distance is derived by dividing d(T_1, T_2) by the maximal possible distance i(T_1) + i(T_2). If both trees are unrooted and binary this value is 2n-6.

Functions like `RF.dist` returns the Robinson-Foulds distance (Robinson and Foulds 1981) between either 2 trees or computes a matrix of all pairwise distances if a `multiPhylo` object is given.

For large number of trees the distance functions can use a lot of memory!

### Value

`treedist` returns a vector containing the following tree distance methods

 `symmetric.difference` symmetric.difference or Robinson-Foulds distance `branch.score.difference` branch.score.difference `path.difference` path.difference `weighted.path.difference` weighted.path.difference

### Author(s)

Klaus P. Schliep klaus.schliep@gmail.com, Leonardo de Oliveira Martins

### References

de Oliveira Martins L., Leal E., Kishino H. (2008) Phylogenetic Detection of Recombination with a Bayesian Prior on the Distance between Trees. PLoS ONE 3(7). e2651. doi: 10.1371/journal.pone.0002651

de Oliveira Martins L., Mallo D., Posada D. (2016) A Bayesian Supertree Model for Genome-Wide Species Tree Reconstruction. Syst. Biol. 65(3): 397-416, doi:10.1093/sysbio/syu082

Steel M. A. and Penny P. (1993) Distributions of tree comparison metrics - some new results, Syst. Biol., 42(2), 126–141

Kuhner, M. K. and Felsenstein, J. (1994) A simulation comparison of phylogeny algorithms under equal and unequal evolutionary rates, Molecular Biology and Evolution, 11(3), 459–468

D.F. Robinson and L.R. Foulds (1981) Comparison of phylogenetic trees, Mathematical Biosciences, 53(1), 131–147

D.F. Robinson and L.R. Foulds (1979) Comparison of weighted labelled trees. In Horadam, A. F. and Wallis, W. D. (Eds.), Combinatorial Mathematics VI: Proceedings of the Sixth Australian Conference on Combinatorial Mathematics, Armidale, Australia, 119–126

`dist.topo`, `nni`, `superTree`, `mast`

### Examples

```
tree1 <- rtree(100, rooted=FALSE)
tree2 <- rSPR(tree1, 3)
RF.dist(tree1, tree2)
treedist(tree1, tree2)
sprdist(tree1, tree2)
trees <- rSPR(tree1, 1:5)
SPR.dist(tree1, trees)

```

phangorn documentation built on June 16, 2022, 5:11 p.m.