Fast RR-BLUP — fastRRBLUP • AlphaSimR

Solves an RR-BLUP model for genomic predictions given known variance components. This implementation is meant as a fast and low memory alternative to RRBLUP or RRBLUP2. Unlike the those functions, the fastRRBLUP does not fit fixed effects (other than the intercept) or account for unequal replication.

Usage

fastRRBLUP(
  pop,
  traits = 1,
  use = "pheno",
  snpChip = 1,
  useQtl = FALSE,
  maxIter = 1000,
  Vu = NULL,
  Ve = NULL,
  simParam = NULL,
  ...
)

Arguments

pop: a Pop-class to serve as the training population
traits: an integer indicating the trait to model, a trait name, or a function of the traits returning a single value. Only univariate models are supported.
use: train model using phenotypes "pheno", genetic values "gv", estimated breeding values "ebv", breeding values "bv", or randomly "rand"
snpChip: an integer indicating which SNP chip genotype to use
useQtl: should QTL genotypes be used instead of a SNP chip. If TRUE, snpChip specifies which trait's QTL to use, and thus these QTL may not match the QTL underlying the phenotype supplied in traits.
maxIter: maximum number of iterations.
Vu: marker effect variance. If value is NULL, a reasonable value is chosen automatically.
Ve: error variance. If value is NULL, a reasonable value is chosen automatically.
simParam: an object of SimParam
...: additional arguments if using a function for traits

Examples

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=20)

#Set simulation parameters
SP = SimParam$new(founderPop)
SP$addTraitA(10)
SP$setVarE(h2=0.5)
SP$addSnpChip(10)

#Create population
pop = newPop(founderPop, simParam=SP)

#Run GS model and set EBV
ans = fastRRBLUP(pop, simParam=SP)
pop = setEBV(pop, ans, simParam=SP)

#Evaluate accuracy
cor(gv(pop), ebv(pop))
#>        est_GV_Trait1
#> Trait1     0.4520165