qtl (version 0.85-4)

sim.cross: Simulate a QTL experiment

Description

Simulates data for a QTL experiment using a model in which QTLs act additively. A backcross, intercross, or phase-known 4-way cross may be simulated.

Usage

sim.cross(map, model=NULL, n.ind=100, type=c("f2", "bc", "4way"),
          error.prob=0, missing.prob=0, partial.missing.prob=0,
          keep.qtlgeno=FALSE,error.ind=TRUE,
	  map.function=c("haldane","kosambi","c-f"))

Arguments

map

A list of length n.chr; its components are vectors containing the marker locations on each of the chromosomes.

model

A matrix where each row corresponds to a different QTL, and gives the chromosome number, cM position and effects of the QTL.

n.ind

Number of individuals to simulate.

type

Indicates whether to simulate an intercross ("f2"), a backcross ("bc"), or a 4-way cross ("4way").

error.prob

The genotyping error rate to simulate.

missing.prob

The rate of missing genotypes to simulate.

partial.missing.prob

When simulating an intercross or 4-way cross, this gives the rate at which markers will be incompletely informative (i.e., dominant or recessive).

keep.qtlgeno

If TRUE, genotypes for the simulated QTLs are not removed from the marker genotype data or genetic maps.

error.ind

If TRUE, and if error.prob > 0, the components of geno will each contain a matrix, errors, with 1's indicating a simulated genotyping error.

map.function

Indicates whether to use the Haldane, Kosambi or Carter-Falconer map function when converting genetic distances into recombination fractions.

Value

• An object of class cross. See read.cross for details.

Details

Meiosis is assumed to exhibit no crossover interference. If one of the chromosomes has class X, it is assumed to be the X chromosome, and is assumed to be segregating in the cross. Thus, in an intercross, it is segregating like a backcross chromosome. In a 4-way cross, a second phenotype, sex, will be generated. In order to ensure that the code is relatively easy to read, simulation is actually performed in a set of subfunctions, sim.cross.bc, sim.cross.f2, and sim.cross.4way.

See Also

read.cross, fake.f2, fake.bc fake.4way

Examples

map <- sim.map()
fake <- sim.cross(map,type="f2", model = rbind(c(1,20,1,2),c(5,20,0.5,0.5)))