# Produce a design matrix
design <- model.matrix(~ 0 + factor(rep(1:2, each = 3)))
colnames(design) <- paste0("ng", c(50, 100))
# Normalize and log transform the data
yeast %>%
# Remove missing data
# Note that this could be replaced with imputation
tidyr::drop_na() %>%
# Normalize
psrn("identifier") %>%
plot_gamma_regression(design)
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