Run genomic predictions

Run GBLUP model using mmer, potentially on multiple traits. Returns genomic BLUPs (GEBV and GETGV). If requested, returns backsolved marker effects (equivalent to ridge regression / SNP-BLUP). Three models are enabled: additive-only ("A"), additive-plus-dominance ("AD") and a directional-dominance model that incorporates a genome-wide homozygosity effect ("DirDom"). Inbreeding effect is included in output GEBV/GETGV predictions *after* backsolving SNP effects. If requested, returns GEBV/GETGV computed for a selection index using selInd=TRUE and supplying SIwts.

runGenomicPredictions(
  modelType,
  selInd,
  SIwts = NULL,
  getMarkEffs = FALSE,
  returnPEV = FALSE,
  blups,
  grms,
  dosages = NULL,
  gid = "GID",
  ncores = 1,
  nBLASthreads = NULL
)

Arguments

modelType: string, "A", "AD", "DirDom". modelType="A": additive-only, GEBVS modelType="AD": the "classic" add-dom model, GEBVS+GEDDs = GETGVs modelType="DirDom": the "genotypic" add-dom model with prop. homozygous fit as a fixed-effect, to estimate a genome-wide inbreeding effect. obtains add-dom effects, computes allele sub effects (\(\alpha = a + d(q-p)\)) incorporates into GEBV and GETGV
selInd: logical, TRUE/FALSE, selection index accuracy estimates, requires input weights via SIwts
SIwts: required if selInd=FALSE, named vector of selection index weights, names match the "Trait" variable in blups
getMarkEffs: T/F return marker effects, backsolved from GBLUP
returnPEV: T/F return PEVs in GBLUP
blups: nested data.frame with list-column "TrainingData" containing BLUPs. Each element of "TrainingData" list, is data.frame with de-regressed BLUPs, BLUPs and weights (WT) for training and test.
grms: list of genomic relation matrices (GRMs, aka kinship matrices). Any genotypes in the GRMs get predicted with, or without phenotypes. Each element is named either A or D. Matrices supplied must match required by A, AD and DirDom models. e.g. grms=list(A=A,D=D).
dosages: dosage matrix. required only for modelType=="DirDom". Also required if getMarkEffs==TRUE. Assumes SNPs coded 0, 1, 2. Nind rows x Nsnp cols, numeric matrix, with rownames and colnames to indicate SNP/ind ID
gid: string variable name used for genotype ID's in e.g. blups (default="GID")
ncores: number of cores
nBLASthreads: number of cores for each worker to use for multi-thread BLAS

Value

tibble, one row, two list columns (basically a named two-element list of lists): gblups[[1]] and genomicPredOut[[1]]. codegblups[[1]]: tibble of predicted GEBV/GETGV, all traits and potentially SELIND genomic BLUPs along the columns. genomicPredOut[[1]] is a tibble that contains some combination of lists-columns:

gblups
varcomps,
fixeffs,
allelesubsnpeff,
addsnpeff,
domstar_snpeff,
domsnpeff

Arguments

Value

See also