`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.
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.
See Also
The core function of the package lmebreed function and the DT_mohring example.
data(DT_mohring)
DT <- DT_mohring
head(DT)
DT2 <- add.diallel.vars(DT,par1="Par1", par2="Par2")
head(DT2)
## see ?DT_mohring for an example on how to use the data to fit diallel models.