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Create a breeding experiment

Source: R/constructor.R
BreedingExperiment.Rd

Builds a BreedingExperiment from a marker genotype matrix, with optional phenotypes, pedigree and marker coordinates.

Usage

BreedingExperiment(
  genotypes,
  phenotypes = NULL,
  pedigree = NULL,
  rowRanges = NULL,
  ...
)

Arguments

genotypes

A numeric matrix of allele dosages, markers in rows and individuals in columns, with column names identifying the individuals.

phenotypes

Optional data frame or S4Vectors::DataFrame of individual-level variables, with one row per column of genotypes.

pedigree

Optional data frame with columns id, sire and dam. Unknown parents may be NA or 0.

rowRanges

Optional GenomicRanges::GRanges giving the position of each marker, of the same length as nrow(genotypes).

...

Further assays, passed to SummarizedExperiment::SummarizedExperiment().

Value

A BreedingExperiment object.

Details

Genotypes are allele dosages: usually the integers 0, 1 and 2, with NA for missing calls. Fractional values in between are accepted, so expected dosages from imputation can be stored directly. Markers are rows and individuals are columns, matching the Bioconductor convention that features are rows.

If rowRanges is not supplied, markers are given placeholder coordinates on a single sequence so that the object is still a valid ranged experiment; pass real coordinates whenever you have them, because that is what allows a data set to be subset by genomic region.

The pedigree may name ancestors that were never genotyped. Those extra individuals are exactly what Hmatrix() needs in order to combine pedigree and genomic information.

See also

Gmatrix(), Amatrix(), Hmatrix(), simulateBreeding()

Examples

set.seed(1)
geno <- matrix(rbinom(40 * 12, 2, 0.3), nrow = 40, ncol = 12,
               dimnames = list(paste0("snp", 1:40), paste0("ind", 1:12)))
pheno <- data.frame(yield = rnorm(12))
be <- BreedingExperiment(geno, phenotypes = pheno)
be
#> class: BreedingExperiment
#> markers: 40  individuals genotyped: 12 
#> assays(1): genotype
#> phenotypes(1): yield
#> sequences(1): unknown
#> pedigree: none
dim(be)
#> [1] 40 12