| RRBLUP_D2 | R Documentation | 
Fits an RR-BLUP model for genomic predictions that includes
dominance effects. This implementation is meant for situations where
RRBLUP_D is too slow. Note that RRBLUP_D2
is only faster in certain situations. Most users should use
RRBLUP_D.
RRBLUP_D2(
  pop,
  traits = 1,
  use = "pheno",
  snpChip = 1,
  useQtl = FALSE,
  maxIter = 10,
  Va = NULL,
  Vd = NULL,
  Ve = NULL,
  useEM = TRUE,
  tol = 1e-06,
  simParam = NULL,
  ...
)
| pop | a  | 
| traits | an integer indicating the trait to model, a trait name, or a function of the traits returning a single value. | 
| 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. Only used when number of traits is greater than 1. | 
| Va | marker effect variance for additive effects. If value is NULL, a reasonable starting point is chosen automatically. | 
| Vd | marker effect variance for dominance effects. If value is NULL, a reasonable starting point is chosen automatically. | 
| Ve | error variance. If value is NULL, a reasonable starting point is chosen automatically. | 
| useEM | use EM to solve variance components. If false, the initial values are considered true. | 
| tol | tolerance for EM algorithm convergence | 
| simParam | an object of  | 
| ... | additional arguments if using a function for traits | 
#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=20)
#Set simulation parameters
SP = SimParam$new(founderPop)
SP$addTraitAD(10, meanDD=0.5)
SP$setVarE(h2=0.5)
SP$addSnpChip(10)
#Create population
pop = newPop(founderPop, simParam=SP)
#Run GS model and set EBV
ans = RRBLUP_D2(pop, simParam=SP)
pop = setEBV(pop, ans, simParam=SP)
#Evaluate accuracy
cor(gv(pop), ebv(pop))
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