Hi, I am trying to build a model matrix in limma to perform differential analysis of my features. I have a simple phenodata like this:

Sample  condition
dmso_1  control
dmso_2  control
dmso_3  control
pi3_1   drug
pi3_2   drug
pi3_3   drug

I want to see differential changes 2 conditions control and drug. I have seen from tutorial videos that you can either include the intercept or not. What I don't understand is sometimes ~-1 is used, sometimes ~1 or ~0 is used. Can you tell whether my matrix will work and what exactly is the difference between coefficients?

design <- model.matrix(~-1 + factor(rep(1:2, each=3)))
colnames(design) <- c("dmso","pi3")
contrast <- makeContrasts(dmso - pi3, levels = design)
fit <- lmFit(file.mat, design)
fit2 <- contrasts.fit(fit, contrast)
fit2 <- eBayes(fit2)

Also if I don't want to use the intercept, how can I build the matrix?

Thanks

See Section 9.2 of the limma User's Guide.

In R, ~0 and ~-1 are the same thing while ~1 is superfluous and possibly an error in whatever tutorial you have read.