scanone.lmer: Conduct mixed effect QTL mapping.
In jtlovell/qtlTools: Data Processing and Plotting in Association with R/qtl

Description Usage Arguments Details Value Examples

scanone.lmer Use lmer linear mixed effect models as the engine for scanone

1	scanone.lmer(cross, base.formula, test.formula, ...)

`cross`	A cross object
`base.formula`	The formula of a model that serves as the baseline. Must contain at least one random effect per lmer's functionality. All terms in the formula must be contained in the 'cross' phenotype matrix slot.
`test.formula`	The formula containing an additional fixed effect to test. The word "QTL" must be contained here, and may also occur in the base.formula. This term is a placeholder and is replaced by the genotypes at each postion in the conditional probability matrix when lmer is called.
`...`	Additional arguments to pass on to lmer.

This function is still under development and is too slow for permutations as it stands now. An overly conservative approach is to adjust the p-values. However, since each marker is not independent, this results in a severe reduction in power.

An object of class scanone

## Not run: 
data(fake.f2)
cross<-fake.f2
cross<-subset(cross, ind = c(1:nind(cross),1:nind(cross)))
cross$pheno<-data.frame(cross$pheno, block = rep(1:(nind(cross)/2),2))
cross$pheno<-data.frame(cross$pheno, pheno2 = jitter(cross$pheno$phenotype))
sex<-data.frame(sex = pull.pheno(cross, pheno.col = "sex"))
cross = calc.genoprob(cross)

base.formula = "pheno2 ~ sex + (1|block)"
qtl.formula = "pheno2 ~ sex + QTL + sex*QTL + (1|block)"

s1<-scanone.lmer(cross, base.formula = base.formula, test.formula = qtl.formula)
par(mfrow = c(2,1))
plot(s1, main = "linear mixed effect model")
plot(scanone(cross, pheno.col = "pheno2", intcovar = sex), col = "grey", main = "scanone")

## End(Not run)