tess.sim.taxa: tess.sim.taxa.taxa: Simulate a reconstructed tree for a given...

Description Usage Arguments Value Author(s) References Examples

View source: R/tess.sim.taxa.R

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

1
2
3
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

1
2
3
4
5
6
7
l <- function(x) { if (x > 0.5 || x < 0.3) { return (1) } else { return (2) } }
e <- 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)

hoehna/TESS documentation built on Feb. 3, 2022, 5:59 a.m.