TiPS (version 1.2.3)

simulate_tree: Simulates a phylogeny using a beackward-in-time process using sampling dates and a trajectory

Description

Simulates a phylogeny using a beackward-in-time process using sampling dates and a trajectory

Usage

simulate_tree(
  simuResults,
  dates,
  deme,
  sampled,
  root,
  isFullTrajectory = FALSE,
  nTrials = 1,
  addInfos = FALSE,
  resampling = FALSE,
  verbose = FALSE,
  seed = 0,
  outFile = "",
  format = "newick"
)

Value

An object of class ape::phylo.

Arguments

simuResults

Object of class simutraj resulting from running a simulator of trajectories built using the build_simulator function.

dates

Contains the sampling dates. Can be a vector (for example using seq function), can be a named list or a file with header.

deme

A vector with the compartments that contribute to the simulation of phylogeny.

sampled

A named vector with the proportions of sampling for each compartment. This is used in case there are multiple deme compartments where the sampling dates will be randomly associated to a compartment to sample. Sum of sampled must be 1.

root

Name of the compartment from which the phylogeny is rooted.

isFullTrajectory

Boolean to define if death events generate or not leaves. By default, isFullTrajectory=FALSE.

nTrials

Integer indicating the number of unsuccessful simulation trials allowed before giving up.

addInfos

Boolean to define if each internal node' name will be the reaction. By default, addInfos=FALSE.

resampling

Boolean to allow a sampled individual to transmit the pathogen once again. By default, resampling=FALSE.

verbose

Boolean to allow printing time execution of simulation

seed

Seed to initialize the random generator, for better reproducibility. By default, seed=0 and the seed value is randomly generated.

outFile

Output file name to write tree. By default, tree is not written in output file.

format

Output tree format if output file is given. Values are either format = "newick" ou format = "nexus". By default, format = "newick"

Author

Gonche Danesh

Examples

if (FALSE) {
# A multi-type birth-death model with birth rate beta,
# death rate gamma, mutation rates m1 and m2
# and I1 and I2 the number of infected individuals of each type.
# With parameter beta varying over 2 time intervals.
reactions <- c("0 [beta1 * I1] -> I1","I1 [gamma1 * I1] -> 0",
"I1 [mu1 * I1] -> I2","0 [beta2 * I2] -> I2",
"I2 [gamma2 * I2] -> 0","I2 [mu2 * I2] -> I1")

BD_simu <- build_simulator(reactions)
initialStates <- c(I1 = 0, I2 = 1)
times <- c(1975, 1998, 2018)
theta <- list(gamma1 = c(0.2, 0.09), gamma2 = 0.1, mu1 = 0.025,
mu2 = 0.021, beta1 = c(0.26,0.37), beta2 = 0.414)
BDres <- BD_simu(paramValues = theta,
                  initialStates = initialStates,
                  times = times,
                  tau = 0.08,
                  method = "approximate",
								 seed = 994543)
# Let's generate 100 sampling dates from 2015 and 2018
dates_bd <- seq(from=2015, to=2018, length.out=100)
BD_tree <- simulate_tree(simuResults = BDres,
                         dates = dates,
                         deme = c("I"),
                         sampled = c(I=1),
                         root = "I",
                         isFullTrajectory = FALSE,
                         seed = 973360)
BD_tree$seed
# Plot the simulated phylogeny using the \code{ape::plot.phylo} function.
ape::plot.phylo(BD_tree)
}