R/predCrossVar.R
predOneCrossVarA.Rd
User specifies a trait variance (or trait-trait covariance) to predict for a specific pair of parents. Predicts the addtiive genetic variance (or covariance) among full-siblings of that cross.
predOneCrossVarA( Trait1, Trait2, sireID, damID, haploMat, recombFreqMat, predType, postMeanAlleleSubEffects, postVarCovarOfAlleleSubEffects = NULL, ... )
Trait1 | string, label for Trait1. When Trait1==Trait2 computes the genomic variance of the trait, when Trait1!=Trait2 computes the genomic covariance between traits. |
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Trait2 | string, label for Trait2. When Trait1==Trait2 computes the genomic variance of the trait, when Trait1!=Trait2 computes the genomic covariance between traits. |
sireID | string, Sire genotype ID. Needs to correspond to renames in haploMat |
damID | string, Dam genotype ID. Needs to correspond to renames in haploMat |
haploMat | matrix of phased haplotypes, 2 rows per sample, cols = loci, 0,1, rownames assumed to contain GIDs with a suffix, separated by "_" to distinguish haplotypes |
recombFreqMat | a square symmetric matrix with values = (1-2*c1), where c1=matrix of expected recomb. frequencies. The choice to do 1-2c1 outside the function was made for computation efficiency; every operation on a big matrix takes time. |
predType | string, "VPM" or "PMV". Choose option "VPM" if you have REML marker effect estimates (or posterior-means from MCMC) one set of marker effect estimates per trait. Variance of posterior means is faster but the alternative predType=="PMV" is expected to be less biassed. PMV requires user to supply a (probably LARGE) variance-covariance matrix of effects estimates. |
postMeanAlleleSubEffects | list of named vectors (or column matrices) with the allele substitution marker effects (can posterior-mean effects from MCMC _or_ from REML, if if setting predType="PMV". |
postVarCovarOfAlleleSubEffects | Only if setting predType="PMV". Matrix of dimension N SNP x N SNP. ALLELE SUBSTITUTION Posterior Sample Variance-Covariance Matrix of Marker Effects Estimates. |
... |
tibble with predicted additive variance for one cross, one variance parameter