inst/md/SS_UN_UN.md

Spike slab

Fitting selection variable models with multi trait models with simulated data.


library(BGLR)
data(simulated3t)

y<-as.matrix(simulated3t.pheno[,1:3])
g<-as.matrix(simulated3t.pheno[,4:6])
cov(g)
y<-scale(y,center=TRUE,scale=FALSE)
y.orig<-y

X<-simulated3t.X
X<-scale(X)/sqrt(ncol(X))

ETA1<-list(list(X=X,model="SpikeSlab",
                inclusionProb=list(probIn=rep(1/100,ncol(y)),
                counts=rep(1E6,ncol(y)))))

#Fit the model

fm1<-Multitrait(y=y,ETA=ETA1,nIter=1000,burnIn=500)

#Residual covariance, UN
fm1$resCov

#Compare against the TRUE residual covariance matrix
#6.0 6.0 1.0
#6.0 8.0 2.0  
#1.0 2.0 1.0

#Genetic co-variance
crossprod(fm1$ETA[[1]]$beta)/fm1$ETA[[1]]$p

#Compare against the TRUE genetic co-variance matrix
#1.00   0.34   0.07
#0.34   1.00   0.21 
#0.07   0.21   1.00 

#Covariance matrix for b, UN
fm1$ETA[[1]]$Cov

Return to examples



Try the BGLR package in your browser

Any scripts or data that you put into this service are public.

BGLR documentation built on June 22, 2024, 12:15 p.m.