sommer (version 3.1)

HDdata: half diallel data for corn hybrids

Description

This dataset contains phenotpic data for 21 corn hybrids, with 2 technical repetitions, coming from a half diallel design and evaluated for sugar content. The column geno indicates the hybrid and male and female origin columns are included as well. Since there's 2 technical reps the error variance obtained by REML/ML has to be divided over 2.

Usage

data("HDdata")

Format

The format is: chr "HDdata"

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 mmer2

Examples

# NOT RUN {
####=========================================####
#### For CRAN time limitations most lines in the 
#### examples are silenced with one '#' mark, 
#### remove them and run the examples
####=========================================####

####=========================================####
#### Example 1 (formula-based)
#### using overlay with mmer2 function
####=========================================####
data(HDdata)
head(HDdata)
HDdata$female <- as.factor(HDdata$female)
HDdata$male <- as.factor(HDdata$male)
HDdata$geno <- as.factor(HDdata$geno)
#### model using overlay
modh <- mmer2(sugar~1, random=~female + and(male) + geno, 
              data=HDdata)
summary(modh)

#### model using overlay [and(.)] and covariance structures [g(.)]

# A <- diag(7); A[1,2] <- 0.5; A[2,1] <- 0.5 # fake covariance structure
# colnames(A) <- as.character(1:7); rownames(A) <- colnames(A);A
# 
# modh2 <- mmer2(sugar~1, random=~g(female) + and(g(male)) + geno,
#                G=list(female=A, male=A),data=HDdata)
# summary(modh2)

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# ####=========================================####
# #### Example 2 (matrix-based)
# #### using overlay with mmer function
# ####=========================================####
# 
# #### GCA matrix for half diallel using male and female columns
# #### use the 'overlay' function to create the half diallel matrix
# Z1 <- overlay(HDdata[,c(3:4)])
# 
# #### Obtain the SCA matrix
# Z2 <- model.matrix(~as.factor(geno)-1, data=HDdata)
# 
# #### Define the response variable and run
# y <- HDdata$sugar
# ETA <- list(list(Z=Z1), list(Z=Z2)) # Zu component
# modHD <- mmer(Y=y, Z=ETA, draw=FALSE, silent=TRUE)
# summary(modHD)

# }