You can simulate most anything, provided you have a probability model. And you'll need to write your own code.
To simulate switched alleles, you could sample some set of markers and then apply switchAlleles():
# switch alleles at a random third of markers
data(hyper)
some_markers <- sample( markernames(hyper), round( totmar(hyper)/3 ), replace=FALSE)
hyper <- switchAlleles(hyper, some_markers)To simulate segregation distortion, the simplest model is maybe partial lethality of alleles at some position, and the simplest way is simulate this is probably "rejection sampling": Simulate a bunch extra of individuals, and then retain just a portion of them, based on genotype at the locus under selection. You could simulate a "QTL" genotype to use as the locus under selection, if you don't want it to be a specific marker. Maybe even easier: you could simulate some underlying "frailty" phenotype, and save just the individuals that have phenotype < some threshold.
data(map10)
n.ind <- 1000
x <- sim.cross(map10, model=rbind(c(1, 45, 2, -2)), type="f2", n.ind=n.ind)
x <- subset(x, ind = x$pheno[,1] < 0)
geno.table(x, chr=1)karl