gxeGGE: GGE analysis

Description

The Genotype plus Genotype by Environment interaction (GGE) model fits a model with trial as main fixed effect. Then a principal component analysis is done on the residuals. This results in an interaction characterized by Interaction Principal Components (IPCA) enabling simultaneous plotting of genotypes and trials.

The parameter nPC is used to indicate the number of principal components that is used in the principal component analysis (PCA). By setting this parameter to NULL the algorithm determines the best number of principal components (see Details).

By specifying the parameter byYear = TRUE, a separate analysis will be done for every year in the data. Combining the option with nPC = NULL may result in different numbers of principal components per year. The GGE estimates will still be returned as a single data.frame, but the other results will be either lists or arrays.

Usage

gxeGGE(
  TD,
  trials = names(TD),
  trait,
  nPC = 2,
  byYear = FALSE,
  center = TRUE,
  excludeGeno = NULL,
  useWt = FALSE
)

Arguments

TD: An object of class TD.
trials: A character string specifying the trials to be analyzed. If not supplied, all trials are used in the analysis.
trait: A character string specifying the trait to be analyzed.
nPC: An integer specifying the number of principal components used as multiplicative term of genotype-by-trial interaction. If NULL, the number of principal components is determined by the algorithm using forward selection. See details.
byYear: Should the analysis be done by year? If TRUE the data is split by the variable year, analysis is performed and the results are merged together and returned.
center: Should the variables be shifted to be zero centered?
excludeGeno: An optional character vector with names of genotypes to be excluded from the analysis. If NULL, all genotypes are used.
useWt: Should weighting be used when modeling? Requires a column wt in TD.

Details

First a linear model \(trait = trial + \epsilon\) is fitted with trial a fixed component in the model.
The residuals from the fitted model are then used in a PCA. If nPC is not NULL a single PCA is done using prcomp with maximum rank nPC.
In case nPC = NULL, the PCA is first done with one PC. Then using forward selection one by one the number of PCs is increased as long as the added component is significant in the analysis.
GGE estimates are then computed using the results of the PCA.