run.threshold.scans: Runs threshold scans from a matrix of outcomes, either...
In gkeele/kqtl: Suite of QTL Mapping Functions

Description Usage Arguments Examples

This function takes an object produced from either generate.null.bootstrap.matrix() or generate.perm.matrix(), and runs genome scans on the outcomes contained in them.

1
2
3

run.threshold.scans(sim.threshold.object, keep.full.scans = TRUE, genomecache,
  data, model = c("additive", "full"), use.multi.impute = TRUE,
  num.imp = 11, chr = "all", just.these.loci = NULL, scan.seed = 1, ...)

`sim.threshold.object`	An object created by either generate.null.bootstrap.matrix() or generate.perm.matrix().
`keep.full.scans`	DEFAULT: TRUE. Returns full genome scans for every outcome sample in the sim.threshold.object. Can be used for visualization of the procedure, but greatly increases the size of the output object.
`genomecache`	The path to the genome cache directory. The genome cache is a particularly structured directory that stores the haplotype probabilities/dosages at each locus. It has an additive model subdirectory and a full model subdirectory. Each contains subdirectories for each chromosome, which then store .RData files for the probabilities/dosages of each locus.
`data`	A data frame with outcome and potential covariates. Should also have IDs that link to IDs in the genome cache, often the individual-level ID named "SUBJECT.NAME".
`model`	DEFAULT: additive. Specifies how to model the founder haplotype probabilities. The additive options specifies use of haplotype dosages, and is most commonly used. The full option regresses the phenotype on the actual diplotype probabilities.
`use.multi.impute`	DEFAULT: TRUE. This option specifies whether to use ROP or multiple imputations.
`num.imp`	DEFAULT: 11. IF multiple imputations are used, this specifies the number of imputations to perform.
`chr`	DEFAULT: "all". The chromosomes to conduct scans over.
`just.these.loci`	DEFAULT: NULL. Specifies a reduced set of loci to fit. If loci is just one locus, the alternative model fit will also be output as fit1.
`scan.seed`	DEFAULT: 1. The sampling process is random, thus a seed must be set for samples to be consistent across machines.