predCrossMeanGVsOneTrait: predCrossMeanGVsOneTrait

In wolfemd/predCrossVar: Prediction of family genomic variances and covariances

Description

Predict the total genetic merit of the cross based on a model with additive+dominance marker effects. For each family , for a single trait, given parental allelic dosages and (posterior mean) marker effects. Eqn. 14.6 Falconer+MacKay, and elsewhere G = sum( 𝑎(𝑝 − 𝑞 − 𝑦) + 𝑑[2𝑝𝑞 + 𝑦(𝑝 − 𝑞)] ) a and d being the additive and dominance effects p and q being the allele frequencies of one parent y is the difference of freq. between the two parents

Usage

predCrossMeanGVsOneTrait(
  Trait,
  CrossesToPredict,
  doseMat,
  postMeanAddEffects,
  postMeanDomEffects
)

Arguments

Trait	string, label of trait (name in list of postMeanAddEffects) to compute
CrossesToPredict	data.frame or tibble, col/colnames: sireID, damID. sireID and damID must both be in the haploMat.
doseMat	dosage matrix. Assumes SNPs in M coded 0, 1, 2 (requires rounding dosages to integers). M is Nind x Mrow, numeric matrix, with row/colnames to indicate SNP/ind ID
postMeanAddEffects	list of named vectors (or column matrices) with the posterior mean ADDITIVE marker effects.
postMeanDomEffects	list of named vectors (or column matrices) with the posterior mean DOMINANCE marker effects.

Value

tibble with predicted mean GV for each family

wolfemd/predCrossVar documentation built on Dec. 21, 2020, 10:14 a.m.