maxL_IBD: Wrapper function to run estimate_IBD function over multiple...

In polyqtlR: QTL Analysis in Autopolyploid Bi-Parental F1 Populations

Description

Function to run the estimate_IBD function over a range of possible error priors. The function returns a merged set of results that maximise the marginal likelihood per individual, i.e. allowing a per-individual error rate within the options provided in the errors argument.

Usage

maxL_IBD(errors = c(0.01, 0.05, 0.1, 0.2), ...)

Arguments

errors	Vector of offspring error priors to test (each between 0 and 1)
...	Arguments passed to estimate_IBD.

Value

A list containing the following components:

• maxL_IBD : A nested list as would have been returned by the estimate_IBD function, but composite across error priors to maximise the marginal likelihoods. Note that the $error values per linkage group are now the average error prior across the population per linkage group

• MML : A 3d array of the maximal marginal likelihoods, per error prior. Dimensions are individuals, linkage groups, error priors.

• error_per_ind : A matrix of the most likely genotyping error rates per individual (in rows) for each linkage group (in columns)

• errors : The error priors used (i.e. the input vector is returned for later reference.)

Examples

## Not run: 
data("phased_maplist.4x","SNP_dosages.4x")
maxL_IBD(phased_maplist=phased_maplist.4x,genotypes=SNP_dosages.4x,
ploidy=4,errors=c(0.01,0.02,0.05,0.1))

## End(Not run)

polyqtlR documentation built on Feb. 2, 2022, 5:09 p.m.