sim.geno {qtl} | R Documentation |

## Simulate genotypes given observed marker data

### Description

Uses the hidden Markov model technology to simulate from the joint
distribution Pr(g | O) where g is the underlying genotype vector and O
is the observed multipoint marker data, with possible allowance for
genotyping errors.

### Usage

sim.geno(cross, n.draws=16, step=0, off.end=0, error.prob=0,
map.function=c("haldane","kosambi","c-f","morgan"))

### Arguments

`cross` |
An object of class `cross` . See
`read.cross` for details. |

`n.draws` |
Number of simulation replicates to perform. |

`step` |
Maximum distance (in cM) between positions at which the
simulated genotypes will be drawn, though for `step = 0` ,
genotypes are drawn only at the marker locations. |

`off.end` |
Distance (in cM) past the terminal markers on each
chromosome to which the genotype simulations will be carried. |

`error.prob` |
Assumed genotyping error rate used in the calculation
of the penetrance Pr(observed genotype | true genotype). |

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

### Details

After performing the forward-backward equations, we draw from
*Pr(g[1] = v | O)* and then *Pr(g[k+1] = v | O, g[k] = u)*.

In the case of the 4-way cross, with a sex-specific map, we assume a
constant ratio of female:male recombination rates within the
inter-marker intervals.

### Value

The input `cross`

object is returned with a component,
`draws`

, added to each component of `cross$geno`

.
`draws`

is array of size [n.ind x n.pos x n.draws] where n.pos is
the number of positions at which the simulations were performed and
n.draws is the number of replicates. Attributes `"error.prob"`

,
`"step"`

, and `"off.end"`

are set to the values of the
corresponding arguments, for later reference.

### Author(s)

Karl W Broman, kbroman@jhsph.edu

### See Also

`calc.genoprob`

,
`argmax.geno`

### Examples

data(fake.f2)
fake.f2 <- sim.geno(fake.f2, step=2, n.draws=8)

[Package

*qtl* version 0.98-57

Index]