Last data update: 2014.03.03

R: LTT.plot: Plots the lineages through time of a set of...
LTT.plotR Documentation

LTT.plot: Plots the lineages through time of a set of phylogenetic trees.

Description

LTT.plot plots the lineages through time (LTT) for a set of phylogenetic trees in black (complete or reconstructed; with or without polytomies) together with the average LTT plot in red. The trees may be simulated using any function in TreeSim, or may be empirical trees. The method works for ultrametric and non-ultrametric trees which are binary or have polytomies. NOTE: you probably need to adapt the code such that the plot is pretty for your particular data (range of axes etc).

Usage

LTT.plot(trees,width,precalc,bound=10^(-12),timemax,nmax,avg)

Arguments

trees

List with one or two entries. First component: list of phylogenetic trees; second component: vector with time of origins (can be empty).

width

Width of lines in plot.

precalc

Default = 0. If = 1, then parse 'LTT.plot.gen(trees)' instead of 'trees' for the input variable 'trees'.

bound

Determines the value by which leaf times may differ in an ultrametric tree. If two tips are further apart than 'bound', they are considered as sequentially sampled tips.

timemax

Time axis is drawn from present=0 to timemax years in the past.

nmax

Axis with number of species is drawn from 1 to nmax.

avg

Default=FALSE. If true then the average LTT plot of all individual LTT plots is drawn in red.

Author(s)

Tanja Stadler

References

T. Stadler. Simulating trees on a fixed number of extant species. Syst. Biol., 60: 676-684, 2011.

See Also

LTT.plot.gen, sim.bd.taxa, sim.bd.age, sim.rateshift.taxa, sim.gsa.taxa, birthdeath.tree

Examples

# Simulation of a tree of age 10 under the density-dependent model
numbsim<-3
age<-10
lambda<-0.3
mu<-0
K<-40
tree<- sim.bd.age(age,numbsim,lambda,mu,mrca=FALSE,complete=FALSE,K=K)
# Plot of tree
LTT.plot(c(list(tree),list(c(age,age,age))))
#
# Simulation of a tree with 10 tips under the constant rate birth-death model
numbsim<-3
n<-10
lambda<-0.3
mu<-0
tree<- sim.bd.taxa(10,numbsim,lambda,mu,complete=FALSE,stochsampling=TRUE)
# Plot of tree
ages<-c()
for (i in 1:length(tree)){
	ages<-c(ages,tree[[i]]$root.edge+max(getx(tree[[i]])))
}
LTT.plot(c(list(tree),list(ages)),avg=TRUE)

Results