sim.null: Simulate under the null hypothesis of no QTLs.

In kbroman/qtlsim: Software for Testing QTL Analysis via Simulations

Simulate under the null hypothesis of no QTLs.

Description

Simulates genotype and phenotype data for a backcross experiment with no QTLs, and applies ANOVA and CIM, in order to estimate LOD thresholds.

Usage

sim.null(n.ind=100, n.mar=rep(11,9), mar.sp=rep(10,10*9),
         cim.steps=c(3,5,7,9,11), n.sim=10000)

Arguments

n.ind	Number of backcross individuals.
n.mar	Vector indicating the number of markers on each chromosome.
mar.sp	Vector of length sum(n.mar)-n.chr-1, giving the inter-marker spacings in cM.
cim.steps	Vector giving number of steps of forward selection to perform prior to CIM.
n.sim	Number of simulation replicates to perform.

Value

A matrix of size [n.sim x (1+length(cim.steps))] giving the maximum LOD score for ANOVA and CIM (with the different values of cim.steps) for each simulation replicate.

Author(s)

Karl W Broman, [e-mail]

References

Broman, K. W. (1997) Identifying quantitative trait loci in experimental crosses. PhD dissertation, Department of Statistics, University of California, Berkeley.

See Also

simbc, anal.multi

Examples

## Not run: output <- sim.null()

kbroman/qtlsim documentation built on May 17, 2023, 11:53 p.m.