anal.multi2: Simulations to test QTL analyses

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

Simulations to test QTL analyses

Description

Run multiple simulations of a backcross, analyzed using ANOVA, CIM, forward selection (with both BIC and permutation tests) and MCMC.

Usage

anal.multi2(n.sim=1000, cim.steps=c(3,5,7,9,11), bic.mult=c(2,2.5,3),
            max.steps=13, n.perm=1000, alpha=0.05, thresh=NULL, drop=1.5,
            n.ind=100, n.mar=rep(11,9), mar.sp=rep(10,10*9),
            n.mcmc=1000, mcmc.bic=2.56,
            qtl.chr=c(1,1,2,2,3,4,5), qtl.mar=c(4,8,4,8,6,4,1),
            qtl.dist=rep(0,7), qtl.eff=c(1,1,1,-1,1,1,1)/2,
            sigma=1)

Arguments

n.sim	Number of simulation replicates.
cim.steps	Number of steps in forward selection prior to CIM analysis.
bic.mult	Multipliers for BIC.
max.steps	Maximum number of steps in forward selection.
n.perm	Number of permutation replicates in permutation tests.
alpha	Significance level in permutation tests.
thresh	LOD thresholds for ANOVA and CIM. Should be length 1 or 1+length(cim.steps). If NULL and the chromosome structure and number of individuals match simulations that I've already done, we use my estimated LOD thresholds.
drop	Drop in LOD that is required between inferred QTLs. Should be length 1 or 1+length(cim.steps).
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.
n.mcmc	Number of steps in MCMC
mcmc.bic	Delta value in BIC in the MCMC runs
qtl.chr	Chromosomes on which qtls are sitting.
qtl.mar	Markers to the left of each qtl, numbered 1, 2, ...
qtl.dist	Distance between qtl and marker to left, in cM.
qtl.eff	QTL effects.
sigma	Residual (environmental) standard deviation.

Value

A list of length 3+n.cim+n.bic, whose components correspond to the results of ANOVA, CIM, forward selection with BIC, forward selection with permutation tests, and MCMC with BIC. Each component of this list is itself a list of length n.sim, with each component giving the chromosome numbers and marker numbers of the identified QTLs.

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, sim.null, sim.mcmc, anal.multi

Examples

## Not run: results <- anal.multi2(n.sim=10)

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