fastRRBLUP {AlphaSimR} | R Documentation |
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.
fastRRBLUP(pop, traits = 1, use = "pheno", snpChip = 1, useQtl = FALSE, maxIter = 1000, Vu = NULL, Ve = NULL, simParam = NULL, ...)
pop |
a |
traits |
an integer indicating the trait to model 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 |
... |
additional arguments if using a function for traits |
#Create founder haplotypes founderPop = quickHaplo(nInd=10, nChr=1, segSites=10) #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))