An extention of RRBLUP_GCA
that adds dominance effects.
Note that we have not seen any consistent benefit of this model over
RRBLUP_GCA
.
Usage
RRBLUP_SCA(
pop,
traits = 1,
use = "pheno",
snpChip = 1,
useQtl = FALSE,
maxIter = 40L,
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.
- 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 for convergence.
- simParam
an object of
SimParam
- ...
additional arguments if using a function for traits
Examples
#Create founder haplotypes
founderPop = quickHaplo(nInd=2, 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 = RRBLUP_SCA(pop, simParam=SP)
pop = setEBV(pop, ans, simParam=SP)
#Evaluate accuracy
cor(gv(pop), ebv(pop))
#> est_GV_Trait1
#> Trait1 NA