enhancer (version 1.1.0)

add.diallel.vars: add.diallel.vars

Description

`add.diallel.vars` adds 4 columns to the provided diallel dataset. Specifically, the user provides a dataset with indicator variables for who is the male and female parent and the function returns the same dataset with 4 new dummy variables to allow the model fit of diallel models.

Usage

add.diallel.vars(df, par1="Par1", par2="Par2",sep.cross="-")

Value

A new data set with the following 4 new dummy variables to allow the fit of complex diallel models:

is.cross

returns a 0 if is a self and a 1 for a cross.

is.self

returns a 0 if is a cross and a 1 is is a self.

cross.type

returns a -1 for a direct cross, a 0 for a self and a 1 for a reciprocal cross.

cross.id

returns a column psting the par1 and par2 columns.

Arguments

df

a dataset with the two indicator variables for who is the male and female parent.

par1

the name of the column indicating who is the first parent (e.g. male).

par2

the name of the column indicating who is the second parent (e.g. female).

sep.cross

the character that should be used when creating the column for cross.id. A simple paste of the columns par1 and par2.

Author

Giovanny Covarrubias-Pazaran

References

Giovanny Covarrubias-Pazaran (2024). lme4breeding: enabling genetic evaluation in the age of genomic data. To be submitted to Bioinformatics.

Douglas Bates, Martin Maechler, Ben Bolker, Steve Walker (2015). Fitting Linear Mixed-Effects Models Using lme4. Journal of Statistical Software, 67(1), 1-48.

Examples

DT = data.frame(Block=c( rep(1,64), rep(2,64) ),
                Par1=c( sort(rep(1:8,8)), sort(rep(1:8,8)) ),
                Par2=rep(1:8, 16),
                Ftime=rnorm(128)
)
DT2 <- add.diallel.vars(DT,par1="Par1", par2="Par2")
head(DT2)