qtl.simulate: Simulate a QTL in the DO
In DOQTL: Genotyping and QTL Mapping in DO Mice

Description Usage Arguments Details Value Author(s) See Also Examples

Using a set of real DO genomes, simulate a QTL with a given minor allele frequency (MAFALSE), sample size and effect size.

1 2	qtl.simulate(probs, snps, K, sample.size = dim(probs)[[1]], effect.size = 1, maf = 4, num.poly = 18, num.sims = 1000)

`probs`	Numeric three dimensional array, containing the founder haplotype contributions or genotype probabilities. The sample IDs, founder letter codes and markers IDs must be in dimnames.
`snps`	Data.frame containing 4 columns with marker location information. SNP ID, chr, Mb, cM in columns 1 through 4, respectively.
`K`	Numeric matrix, containing the additive kinship matrix. The samples IDs must be in rownames and colnames.
`sample.size`	Numeric vector sample sizes. Must be less than or equal to the number of samples in probs.
`effect.size`	Numeric vector containing the effect sizes as the number of standard deviations from the phenotype mean.
`maf`	Numeric value containing the minor allele frequecy as the number of founders. FALSEor DO, the value must be between 1 and 4.
`num.poly`	Numeric value containing the number of autosomes on which to simulate a polygenic background.
`num.sims`	Numeric value containing the number of simulations to run.

This function will simulate a phenotype with a QTL. It will output a phenotype vector with sample IDs and a data.frame called qtl describing the simulated loci.

Writes pheno and qtl lists to an R binary file.

Daniel Gatti

scanone

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  ## Not run:  qtl.simulate(probs, snps, K, sample.size = dim(probs)[[1]], 
  effect.size = 1, maf = 4, num.poly = 18, num.sims = 1000) 
## End(Not run)