combineMap {ASMap}

Combine linkage maps from multiple qtl cross objects

Description

Combine map information, marker data and phenotype data from multiple qtl cross objects

Usage

combineMap(..., id = "Genotype", keep.all = TRUE,
           merge.by = "genotype")

Arguments

...

An unlimited set of arguments with each argument defining an qtl cross object. All qtl objects can have any class structure but it must be identical across objects. (see Details for more information.)

id

The name of the common column in the pheno element of each cross object representing the genotype names. Default is "Genotype".

keep.all

A logical value determining whether all genotypes should be kept in the final linkage map regardless of their absence in some linkage maps (see Details). Default is TRUE.

merge.by

A character string. If "genotype" then combining of maps occurs by common genotypes and if "marker" combining of maps occurs by common markers. Default is "genotype". (see Details for more information.)

Details

This function combines linkage maps from multiple qtl cross objects by merging marker data and map information as well as phenotypic data if present. The function contains some initial checks before proceeding with the combining. Firstly, all qtl cross objects must have the same class structure and have a column in the pheno element of the object named by the argument id. The symbol ";" should be avoided in markers as this is reserved for string manipulation within the function.

If merge.by = "genotype" then the combining occurs sequentially across linkage maps based on common genotype names. If keep.all=TRUE then the marker set and phenotypic data are "padded out" when genotype names are not shared between maps. If keep.all=FALSE then the marker set and phenotype data are shrunk to only include genotypes that are shared among all linkage maps. Marker names must be unique across the set of linkage maps. Non-matching genotype names between linkage maps will expand the final marker data and phenotypic data so it is prudent to check genotype names are correct in each of the linkage maps before combining.

If merge.by = "marker" then the combining occurs sequentially across linkage maps based on common markers. If keep.all=TRUE then the marker set is "padded out" when marker names are not shared between maps. If keep.all=FALSE then the marker set is shrunk to only include markers that are shared among all linkage maps. Genotypes must be unique across the set of linkage maps. It should be noted, this function does not use a consensus map algorithm to determine chromosome identification and genetic distances of common markers. These are both calculated using the first instance of the markers appearance across the sequential maps. This makes it ideal for potentially pushing additional genotypes into an established map.

For both merge.by types, if a linkage group name is shared across linkage maps then the marker data from the shared linkage group in each of the maps will be merged. If maps share the same linkage group names and do not require merging the duplicate linkage group names in one of the linkage maps will need to be altered before combining. As a final process, markers are ordered within linkage groups according to distances supplied in each of the linkage maps.

It should also be noted that this function does not re-construct the final linkage map after combining the set of linkage maps. For efficient linkage map reconstruction of a combined qtl object see mstmap.cross().

Value

A single R/qtl cross object is returned with identical class structure as the inputted cross objects.

Author(s)

Julian Taylor

References

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

See Also

breakCross and mergeCross

Examples

data(mapDH, package = "ASMap")

## create copy of mapDH with some different linkage groups
## and change marker names so they are unique

mapDH1 <- mapDH
names(mapDH1$geno)[5:14] <- paste("L",1:10, sep = "")
mapDH1$geno <- lapply(mapDH1$geno, function(el){
    nam <- paste(names(el$map), "A", sep = "")
    names(el$map) <- dimnames(el$data)[[2]] <- nam
    el})

mapDHc <- combineMap(mapDH, mapDH1)
nmar(mapDHc)