runCrossVarPredsA: Single-trait prediction of the additive genetic variance for...
In wolfemd/predCrossVar: Prediction of family genomic variances and covariances

View source: R/predCrossVar_frequentist_univar.R

Wraps around 'predCrossVarA()' to predict multiple crosses. Option for parallelizing prediction across families. If outprefix and outpath are supplied, writes output to disk so impatient users can see results.

runCrossVarPredsA(
  outprefix = NULL,
  outpath = NULL,
  ped,
  addEffects,
  haploMat,
  recombFreqMat,
  ncores = 1,
  ...
)

`ped`	pedigree data.frame, cols: sireID, damID. sireID and damID must both be in the haploMat.
`addEffects`	vector of _additive_ SNP effects estimate. Ideally vector is named with SNP IDs and matches the order of related SNP matrices.
`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.
`ncores`	If ncores set > 1 parallelizes across families, but beware it is memory intensive and options(future.globals.maxSize=___) may need to be adjusted.
`...`