draw.clone {flan}

Graphic representation of clone growing upon a finite time.

Description

Simulates a clone up to a time t and represents the clone as a binary tree.

Usage

  draw.clone(t,mutprob=1.e-2,fitness=1.,death=0.,
	     dist=list("lnorm",meanlog=-0.3795851,sdlog=0.3016223),
	     col=c("green4","orange4"),
       with.lab = TRUE,
       with.pch = FALSE
     )

Arguments

t

time of end of experiment .

mutprob

mutation probability: numeric between 0 and 1. By default 1.e-2.

fitness

fitness parameter: numeric positive. By default 1.

death

death probability: numeric between 0 and 0.5. By default 0.

dist

lifetime distribution for mutant cells. See Details.

col

vector of size 2 of colors. The first is for the normal cells, the second for the mutant cells.

,

with.lab

logical. If TRUE, parameters will appear as title.

,

with.pch

logical. If TRUE, mutant cells will be represented with triangles, normal cells with regular dots.

Details

This function does not provide a representation of a realistic realization of a mutation model (mutation probability too high, time of end of experiment to small).

The argument dist is a list beginning with the distribution name followed by its parameters, and must be one the 4 following distributions: "dirac", "exp", "lnorm"(meanlog, sdlog), "gamma"(shape, scale). Note that the parameters related to the "dirac" and "exp" cases are directly computed with inputs fitness and death.

See Also

rflan

Examples

# Luria-Delbrück model, mutation probability 1e-2, fitness 1
draw.clone(t=9,dist=list(name="exp",rate=1))

# Luria-Delbrück model, mutation probability 0.1, fitness 0.6
draw.clone(t=9,mutprob=0.1,fitness=0.6,dist=list(name="exp",rate=1))

# Haldane model, mutation probability 1e-2, fitness 1
draw.clone(t=7,dist=list(name="dirac",location=1))

# Lognormal lifetime distribution
draw.clone(t=7,fitness=0.5,death=0.1)

# Luria-Delbrück model with positive cell death probability
draw.clone(t=7,dist=list(name="exp",rate=1),death=0.2)