BLUP

Category:R

r-BLUP

1. computation of BLUP's, using seedling dry weight data as example

library(lme4)

d <- read.table('SeedlingDryWeight2.txt',as.is=T, header=T)

1. create factors

d$g <- as.factor(d$Genotype) d$t <- as.factor(d$Tray) d$s <- as.factor(d$Seedling)

1. fit the mixed effects model model

temp <- lmer(SeedlingWeight~g+(1|t),data=d)

1. BLUPs

blup <- ranef(temp)

1. look at ranef() output to see its structure

str(blup)

1. there are options to ranef(drop=T) to simplify structure of output

1. compare BLUP to genotype averages

gmean <- tapply(d$SeedlingWeight,d$t,mean)

plot(gmean,blup$t$'(Intercept)')

1. BLUPs + fixed effects
2. there is no predict() for an lmer object
3. these are the equivalents

betau <- coef(temp)

1. values are beta + u for each row

trayX <- cbind(rep(1,8), rep(c(0,1),c(4,4)))

1. model.matrix with one row per tray

pred.tray <- apply(betau$t*trayX,1,sum)

plot(gmean, pred.tray)