phytools (version 0.3-72.1)

bmPlot: Simulates and visualizes discrete-time Brownian evolution on a phylogeny

Description

This function conducts discrete-time Brownian motion simulation on an input tree, plots the outcome, and returns the tip and internal node states to the user as a named vector. The function will first rescale and round the branch lengths to integer length, if they are not already in integer values. If integer branch lengths are provided, the user should also set ngen=max(nodeHeights(tree)). For type="threshold" the visualization is of the threshold model (Felsenstein 2012), in which the evolving character is liability and the segments of evolution are colored by their value for the threshold trait. If type="threshold" is used, the function requires at least one addition input: thresholds, a vector containing the ordered thresholds between states. The user can also provide the colors for plotting in colors. Note that one more color than threshold should be provided as one threshold implies two states; two thresholds, three states; etc. If no value for colors is provided, the function will recycle a set of four colors up to the number of times required by thresholds. Finally, the optional argument return.tree=TRUE will tell the function to return a list with the tip and note states and an object of class "phylo" with (for type="threshold"), the state for the threshold model through time mapped on the branches of the tree in discrete time.

Usage

bmPlot(tree, type="BM", anc=0, sig2=1/1000, ngen=1000, ...)

Arguments

tree

a phylogenetic tree in "phylo" format.

type

the type of plot to create. See Description.

anc

the ancestral value for the root node.

sig2

the BM rate (variance of the Brownian evolution process).

ngen

number of generations for the simulation: will rescale the tree to this total length.

...

arguments to be passed to different methods.

Value

• This function conducts and plots discrete time Brownian simulation and returns a vector containing the simulated states at internal nodes and tips of the tree.

References

Felsenstein, J. 2012. A comparative method for both discrete and continuous characters using the threshold model. American Naturalist, 179, 145-156.

See Also

fastBM, pbtree, phenogram, threshBayes

Examples

# plot BM simulation on 20 taxon tree
tree<-pbtree(n=20)
x<-bmPlot(tree)

# plot simulation of a threshold character
tree<-pbtree(n=20)
x<-bmPlot(tree,type="threshold",thresholds=c(0,1,2))