BreedingExperiment: breeding data and relationship matrices
Source:R/BreedingExperiment-package.R
BreedingExperiment-package.RdKeeps marker genotypes, phenotypes, pedigree and marker coordinates in one object, and computes the relationship matrices that quantitative genetics runs on.
Details
The container, BreedingExperiment, extends SummarizedExperiment::RangedSummarizedExperiment, so markers are genomic ranges and the usual Bioconductor accessors apply. The methods that matter are:
Amatrix()pedigree numerator relationship matrix
Gmatrix()genomic relationship matrix from markers
Dmatrix()dominance relationship matrix
Hmatrix()single-step matrix combining pedigree and genomic information, so genotyped and ungenotyped individuals can be analysed together
simulateBreeding() produces a small pedigreed population for trying these
out, and filterMarkers() and imputeMarkers() cover routine quality
control.
Provenance
A substantial part of this package was written with the assistance of an AI
coding assistant (Assisted-by: Claude, Anthropic). The author defined the
scope, chose the statistical methods, and reviewed, tested and validated the
result, and is responsible for the correctness and maintenance of the code.
Every method implemented here is an established, published technique in
quantitative genetics, cited in the documentation of the function that
implements it. The relationship matrices are checked in the test suite
against values that follow from theory rather than from a previous run: a
parent-offspring relationship of one half, a grandparent relationship of one
quarter, full sibs related by one half, the offspring of a full-sib mating
inbred at \(F = 0.25\), a positive definite \(H\), and
Hmatrix(blend = 1) reproducing \(A_{22}\) exactly.
Author
Maintainer: Muhammad Farooqi mqfarooqi@gmail.com (ORCID)
Authors:
Muhammad Farooqi mqfarooqi@gmail.com (ORCID)