Any R software package that can perform GxE and stability analysis? I am looking for a software package that can perform stability analysis as done by:
Eberhart, S.A. and W.A. Russell, 1966. Stability parameters for comparing varieties. Crop Sci., 6: 36-40. 
Is a quite old method but still much appreciated. Also I would like to perform AMMI model analysis for GxE analysis.
Is there any R software package can do this ? 
 A: Check plant breeding package, on Rforge. The following is example from the package: 
on Stability, AMMI analysis 
# stability analysis 
require(plantbreeding)
data(multienv)
out <- stability (dataframe = multienv , yvar = "yield", genotypes = "genotypes", 
environments = "environments", replication =  "replication")
out
# AMMI analysis 
results <- ammi.full(dataframe = multienv , environment = "environments", genotype = "genotypes", 
replication = "replication", yvar = "yield")

You can follow the developer on the Rforge and the blog (http://rplantbreeding.blogspot.com/) 
A: Please, take a look at my R package metan (multi-environment trial analysis). You may perform Eberhart and Russell regression analysis with the function ge_reg(). The following code reproduces the example of the package. Note that it works naturally with the forward-pipe operator %>% and allows analyzing several traits at the same time.
# Install from Github (require devtools package)
devtools::install_github("TiagoOlivoto/metan")

library(metan)
reg <- data_ge2 %>% 
  ge_reg(ENV, GEN, REP,
         resp = c(PH, EH))
print(reg)

AMMI analysis is performed with the function performs_ammi(). The following code reproduces the example of the package.
ammi <- data_ge2 %>% 
  performs_ammi(ENV, GEN, REP,
                resp = c(PH, EH))

# Significance of IPCA
get_model_data(ammi, "ipca_pval")

# Explained sum of squares
get_model_data(ammi, "ipca_expl")

# Predict the response variables (say using 2 IPCA)
pred <- predict(ammi, naxis = c(2, 2))
pred$GY

# Biplots (variable GY)
# AMMI1
plot_scores(ammi)

# AMMI2
plot_scores(ammi, type = 2)


You may find the complete description of the package at https://tiagoolivoto.github.io/metan/index.html
