I am trying fit a linear model with limma, where I do adjust for a batch variable. Then I want o calculate statistics for all pair-wise comparisons. Here, I'm wondering whether the way I create the model and its contrast-fits make sense and looks correct.

Could anyone consider the example below and give me a feedback on that?

# Fit many adjusted statistics with limma. Here we adjust for the day effect (a surrogate for a batch effect):

##---------------------

#Covariate of interest:

Condition <- as.factor(pData(ExpressionSet$Condition) 

#Adjusting variable:

Batch <- (pData(ExpressionSet)$Scan_date)

##---------------------

# The adjusted model

(design_adj <- model.matrix(~0+ Condition + as.factor(Batch))) ##Zero: do not include the intercept

##---------------------

# Fitting the model

fit_adj = lmFit (ExpressionSet, design_adj)

##---------------------

# Making all contrasts

(cont.matrix_adj = t(makeAllContrasts(design_adj, Condition))) ###Question: is this a correct matrix?

# Compute Contrasts from Linear Model Fit:

fit2_adj= contrasts.fit(fit_adj, cont.matrix_adj)

##---------------------

# call eBayes

fit2_adj= eBayes(fit2_adj)

##---------------------

# Write all results:

write.fit(fit2_adj, results = NULL, file="adj_Limma_global.txt", digits = 5,

adjust = "BH", method = "global", F.adjust = "none", 

quote = FALSE, sep = "\t", row.names = TRUE,col.names=NA)

I don't know where you got makeAllContrasts from, that's not a limma function. I assume that you're using the function from the EMA package, but I can't say that it's giving you what you want. I would do it manually:

# Making up an example design.
Cond <- gl(4, 4)
Batch <- factor(rep(1:4, 4))
design <- model.matrix(~0 + Cond + Batch)

# Making a contrast for each pairwise comparison.
cont.set <- list()
for (i in seq_len(nlevels(Cond))) {
   for (j in seq_len(i-1L)) {
       new.cont <- integer(ncol(design))
       new.cont[i] <- 1
       new.cont[j] <- -1
       cont.set <- c(cont.set, list(new.cont))
   }
}
cont.mat <- do.call(cbind, cont.set)

... and use that in contrasts.fit.