After a day of googling, I've decided that it'd be better to ask the question here.

So the experiment is I have bulk RNA seq data from 3 patients: A, B, C. And their RNA seq data is obtained for pre-treatment, treatment cycle 1, treatment cycle 2, treatment cycle 3.

So in total I have 12 samples of bulk RNA seq:

A.PreTreat -> A.Cycle1 -> A.Cycle2 -> A.Cycle3

B.PreTreat -> B.Cycle1 -> B.Cycle2 -> B.Cycle3

C.PreTreat -> C.Cycle1 -> C.Cycle2 -> C.Cycle3

I want to get a differential gene list between different cycles (i.e. cycle 3 to pretreatment, cycle 3 to cycle 2) using `model.matrix(), lmFit(), makeContrasts(), contrasts.fit(), eBayes()`

, all of which are in the limma package.

Here is my minimal working example.

```
library(limma)
# Already normalized expression set: rows are genes, columns are the 12 samples`
normalized_expression <- matrix(data=sample(1:100), nrow=10, ncol=12)
colnames(normalized_expression) <- c("A.PreTreat", "A.Cycle1", "A.Cycle2", "A.Cycle3",
"B.PreTreat", "B.Cycle1", "B.Cycle2", "B.Cycle3",
"C.PreTreat", "C.Cycle1", "C.Cycle2", "C.Cycle3")
patient_and_treatment <- factor(colnames(normalized_expression), levels = colnames(normalized_expression))
design.matrix <- model.matrix(~0 + patient_and_treatment)
colnames(design.matrix) <- patient_and_treatment
fit <- lmFit(normalized_expression, design.matrix)
# I want to get a contrast matrix to get differential genes between cycle 3 treatment and pre-treatment in all patients
contrast.matrix <- makeContrasts("A.Cycle3+B.Cycle3+C.Cycle3-A.PreTreat-B.PreTreat-C.PreTreat",
levels = levels(patient_and_treatment))
# Outputs Error of no residual degree of freedom
fit2 <- eBayes( contrasts.fit( fit, contrast.matrix ) )
# Want to run but cannot
summary(decideTests(fit2))
```

So far I am stuck on no residual degree of freedom error.

I am not even sure if this is the statistically right way in limma to address my question of getting differential gene list between cycle 3 treatment to pre-treatment in all patients.

Any help will be greatly appreciated.

Thanks!