tess.sim.taxa {TESS}

tess.sim.taxa.taxa: Simulate a reconstructed tree for a given number of taxa under a global, time-dependent birth-death process.

Description

tess.sim.taxa simulates a reconstructed phylogenetic tree under a global, time-dependent birth-death process conditioned on the number of taxa sampled. The rates may be any positive function of time or a constant. The process starts at time 0 and goes forward in time, hence the rates and events should be interpreted in the time after the origin. Additionally, mass-extinction event can be provided and a uniform taxon sampling probability. It is possible to start either with the origin (1 species) or with the most recent common ancestor (2 species).

Usage

tess.sim.taxa(n, nTaxa, max, lambda, mu, massExtinctionTimes = c(), 
   massExtinctionSurvivalProbabilities = c(), samplingProbability = 1, 
   samplingStrategy = "uniform", SURVIVAL = TRUE, MRCA = TRUE, t_crit = c())

Arguments

n

Number of simulations.

nTaxa

Number of species sampled.

max

Maximum time/height of the tree.

lambda

The speciation rate function or constant.

mu

The extinction rate function or constant.

massExtinctionTimes

The set of mass-extinction times after the start of the process.

massExtinctionSurvivalProbabilities

The set of survival probabilities for each speciation event. The set must have the same length as the set of mass-extinction times.

samplingProbability

The probability for a species to be included in the sample.

samplingStrategy

The strategy how samples were obtained. Options are: uniform|diversified.

SURVIVAL

Do you want to condition on survival of the process?

MRCA

Does the process start with the most recent common ancestor?

t_crit

The critical time points when a jump in the rate function occurs. Only a help for the numerical integration routine.

Value

Returns a tree in 'phylo' format.

Author(s)

Sebastian Hoehna

References

S. Hoehna: Fast simulation of reconstructed phylogenies under global, time-dependent birth-death processes. 2013, Bioinformatics, 29:1367-1374

Examples

l <- Vectorize(function(x) { if (x > 0.5 || x < 0.3) { return (1) } else { return (2) } })
e <- Vectorize(function(x) { if (x > 0.5 || x < 0.3) { return (0.95) } else { return (0.5) } })

tess.sim.taxa(n=1,nTaxa=10,max=10,l,e,MRCA=TRUE)

# simulation under constant rates
tess.sim.taxa(n=1,nTaxa=10,max=10,2.0,1.0,MRCA=TRUE)