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These function superTree allows the estimation of a supertree from a set of trees using either Matrix representation parsimony, Robinson-Foulds or SPR as criterion.

Usage

superTree(tree, method = "MRP", rooted = FALSE, trace = 0,
  start = NULL, multicore = FALSE, mc.cores = NULL, ...)

Arguments

tree

an object of class multiPhylo

method

An argument defining which algorithm is used to optimize the tree. Possible are "MRP", "RF", and "SPR".

rooted

should the resulting supertrees be rooted.

trace

defines how much information is printed during optimization.

start

a starting tree can be supplied.

multicore

logical, whether models should estimated in parallel.

mc.cores

The number of cores to use, i.e. at most how many child processes will be run simultaneously.

...

further arguments passed to or from other methods.

Value

The function returns an object of class phylo.

Details

The function superTree extends the function mrp.supertree from Liam Revells, with artificial adding an outgroup on the root of the trees. This allows to root the supertree afterwards. The functions is internally used in DensiTree. The implementation for the RF- and SPR-supertree are very basic so far and assume that all trees share the same set of taxa.

References

Baum, B. R., (1992) Combining trees as a way of combining data sets for phylogenetic inference, and the desirability of combining gene trees. Taxon, 41, 3-10.

Ragan, M. A. (1992) Phylogenetic inference based on matrix representation of trees. Molecular Phylogenetics and Evolution, 1, 53-58.

See also

mrp.supertree, densiTree, RF.dist, SPR.dist

Author

Klaus Schliep klaus.schliep@gmail.com Liam Revell

Examples


data(Laurasiatherian)
set.seed(1)
bs <- bootstrap.phyDat(Laurasiatherian,
                       FUN = function(x) upgma(dist.hamming(x)), bs=50)

mrp_st <- superTree(bs, minit = 25, maxit=50)
plot(mrp_st)

# \donttest{
rf_st <- superTree(bs, method = "RF")
spr_st <- superTree(bs, method = "SPR")
# }