sommer (version 4.3.5)

DT_example: Broad sense heritability calculation.

Description

This dataset contains phenotpic data for 41 potato lines evaluated in 3 environments in an RCBD design. The phenotypic trait is tuber quality and we show how to obtain an estimate of DT_example for the trait.

Usage

data("DT_example")

Format

The format is: chr "DT_example"

References

Covarrubias-Pazaran G (2016) Genome assisted prediction of quantitative traits using the R package sommer. PLoS ONE 11(6): doi:10.1371/journal.pone.0156744

See Also

The core functions of the package mmer and mmec

Examples

####=========================================####
#### For CRAN time limitations most lines in the 
#### examples are silenced with one '#' mark, 
#### remove them and run the examples
####=========================================####
####=========================================####
#### EXAMPLES
#### Different models with sommer
####=========================================####

data(DT_example)
DT <- DT_example
A <- A_example
head(DT)

####=========================================####
#### Univariate homogeneous variance models  ####
####=========================================####

## Compound simmetry (CS) model
ans1 <- mmer(Yield~Env,
             random= ~ Name + Env:Name,
             rcov= ~ units,
             data=DT)
summary(ans1)$varcomp

ans1b <- mmec(Yield~Env,
             random= ~ Name + Env:Name,
             rcov= ~ units,
             data=DT)
summary(ans1b)$varcomp

# ####===========================================####
# #### Univariate heterogeneous variance models  ####
# ####===========================================####
# 
# ## Compound simmetry (CS) + Diagonal (DIAG) model
# ans2 <- mmer(Yield~Env,
#              random= ~Name + vsr(dsr(Env),Name),
#              rcov= ~ vsr(dsr(Env),units),
#              data=DT)
# summary(ans2)
# 
# DT=DT[with(DT, order(Env)), ]
# ans2b <- mmec(Yield~Env,
#              random= ~Name + vsc(dsc(Env),isc(Name)) +
#                       vsc(atc(Env, c("CA.2011") ),isc(Block)) ,
#              rcov= ~ vsc(dsc(Env),isc(units)),
#              data=DT)
# summary(ans2b)
# 
# ####==========================================####
# #### Multivariate homogeneous variance models ####
# ####==========================================####
# 
# ## Multivariate Compound simmetry (CS) model
# DT$EnvName <- paste(DT$Env,DT$Name)
# ans4 <- mmer(cbind(Yield, Weight) ~ Env,
#               random= ~ vsr(Name) + vsr(EnvName),
#               rcov= ~ vsr(units),
#               data=DT)
# summary(ans4)