`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)

## 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

## 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!

## 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

## Author

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

## Examples

```
tree1 <- rtree(100, rooted=FALSE)
tree2 <- rSPR(tree1, 3)
RF.dist(tree1, tree2)
#> [1] 42
treedist(tree1, tree2)
#> symmetric.difference branch.score.difference path.difference
#> 42.000000 3.803442 246.428489
#> quadratic.path.difference
#> 121.432291
sprdist(tree1, tree2)
#> spr spr_extra rf hdist
#> 3 0 42 68
trees <- rSPR(tree1, 1:5)
SPR.dist(tree1, trees)
#> [1] 1 2 3 4 5
```