mmer.diallel {lmDiallel}

Fitting random diallel linear models

Description

Wrapper function for the function 'mmer()' in the 'sommer' package. It can be used to fit random diallel models and retreive variance components for main effects.

Usage

mmer.diallel(formula, Block, Env, fct, data, type = "all")

Arguments

formula

an object of class "formula" (or one that can be coerced to that class): a symbolic description of the model to be fitted.'formula' uses the regular R syntax to specify the response variable and the two variables for parentals (e.g., Yield ~ Par1 + Par2)

Block

used to specify an optional variable coding for blocks

Env

used to specify an optional variable coding for environments

data

a 'data.frame' where to look for explanatory variables

fct

a string variable coding for the selected model. 8 main diallel models: Hayman's model 1 (="HAYMAN1"), Hayman's model 2 (="HAYMAN2"), Griffing's model 1 (="GRIFFING1"), Griffing's model 2 (="GRIFFING2"), Griffing's model 3 (="GRIFFING3"), Griffing's model 4 (="GRIFFING4"), Gardner-Eberhart model 2 (="GE2") and Gardner-Eberhart model 3 (="GE3"). The strings "GE2r" and "GE3r" can be used to specify the 'enhanced' GE2 and GE3 models, including the effect of reciprocals (REC).

type

a string variable coding for the selected model. It is only used for multi-environment experiments and it is equal to "all" when both the environment and genetical effects are random or "environment" when the environment is random and genetical effects are fixed.

Value

Returns a data frame of variance components with standard errors

Author(s)

Andrea Onofri, Niccolo' Terzaroli, Luigi Russi

References

Covarrubias-Pazaran, G., 2016. Genome-Assisted Prediction of Quantitative Traits Using the R Package sommer. PLOS ONE 11, e0156744. https://doi.org/10.1371/journal.pone.0156744

Examples

data("hayman54")
rMod <- mmer.diallel(Ftime ~ Par1 + Par2, Block = Block,
                  data = hayman54,
                  fct = "HAYMAN1")
rMod