Consensus genotypes for clonal genotype groups

Consensus genotypes for clonal genotype groups of an R/qtl object.

Usage

fixClones(object, gc, id = "Genotype", consensus = TRUE)

Arguments

object: An qtl object object with any class structure.
gc: A data frame of genotype clone infomation usually from a call to genClones (see Details).
id: Character string defining the column of object$pheno containing the genotype names.
consensus: A logical value. If TRUE then consensus genotypes will be calculated for each clonal group by intelligently collapsing alleles for each marker (see Details). If FALSE then for each clonal group the genotype with the least missing alleles across the genome will be retained and the remaining genotypes from each group will be removed.

Details

This function provides a very efficient way of dealing with genotype clones in a genetic marker set. This function can be used at any stage of the map construction process as it retains linkage group and marker position information.

The gc argument needs to be a data frame of clone information and is easily obtained from a call to genClones. If this function is not used then the data frame must contain at least three columns with the first two columns named "G1" and "G2" containing the pairs of genotypes that are clones and a "group" column that indicates the clonal group the pairs of genotypes belongs to.

If consensus = TRUE then the function will intelligently collapse the alleles for each marker to form a consensus genotype. Specifically, the allele value will remain unchanged when there are observed allele values across all genotypes in the clone group. For cases where there are missing alleles for some but not all of the genotypes, the consensus genotype will be given the common allele value from the genotypes that contained observed allele values. If there is more than one unique allele value across the genotypes for any marker then it is set to missing.

Value

The cross object is returned with identical class structure as the imputted cross object.

References

Taylor, J., Butler, D. (2017) R Package ASMap: Efficient Genetic Linkage Map Construction and Diagnosis. Journal of Statistical Software, 79(6), 1–29.

Author

Julian Taylor

Examples


data(mapDH, package = "ASMap")

gc <- genClones(mapDH)
mapDHf <- fixClones(mapDH, gc$cgd, consensus = TRUE)