sim.cross {qtl} | R Documentation |

Simulates data for a QTL experiment using a model in which QTLs act additively.

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=TRUE, keep.errorind=TRUE, map.function=c("haldane","kosambi","c-f","morgan"))

`map` |
A list whose 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 phase-known 4-way cross (`4way` ). |

`error.prob` |
The genotyping error rate. |

`missing.prob` |
The rate of missing genotypes. |

`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 will be included in the output. |

`keep.errorind` |
If TRUE, and if `error.prob > 0` , the
identity of genotyping errors will be included in the output. |

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

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.

QTLs are assumed to act additively, and the residual phenotypic variation is assumed to be normally distributed with variance 1.

For a backcross, the effect of a QTL is a single number corresponding to half the difference between the homozygote and the heterozygote.

For an intercross, the effect of a QTL is a pair of numbers,
(*a,d*), where *a* is the additive effect (half the difference
between the homozygotes) and *d* is the dominance deviation (the
difference between the heterozygote and the midpoint between the
homozygotes).

For a four-way cross, the effect of a QTL is a set of three numbers,
(*a,b,c*), where, in the case of one QTL, the mean phenotype,
conditional on the QTL genotyping being AC, BC, AD or BD, is *a*,
*b*, *c* or 0, respectively.

An object of class `cross`

. See `read.cross`

for
details.

If `keep.qtlgeno`

is TRUE, the cross object will contain a
component `qtlgeno`

which is a matrix containing the QTL
genotypes (with complete data and no errors), coded as in the genotype
data.

If `keep.errorind`

is TRUE and errors were simulated, each
component of `geno`

will each contain a matrix `errors`

,
with 1's indicating simulated genotyping errors.

Karl W Broman, kbroman@jhsph.edu

`sim.map`

, `read.cross`

,
`fake.f2`

, `fake.bc`

`fake.4way`

# simulate a genetic map map <- sim.map() # simulate 250 intercross individuals with 2 QTLs fake <- sim.cross(map, type="f2", n.ind=250, model = rbind(c(1,45,1,1),c(5,20,0.5,-0.5)))

[Package *qtl* version 0.98-57 Index]