

Hi, I'm analyzing a dataset of 50 samples. Each of these samples has a dye-swapped replicate. All the replicates are side by side in the dataset (1, -1, 2, -2, 3, -3, etc...)
I'm interested in some contrasts between predefined groups.
I built a design matrix with the 1 and -1 that correspond to the samples (without or with dye-swap) belonging to a each group (sick1, sick2, sick3):

sick1   sick2  sick3
1    0    0
-1   0    0
0    1    0    
0    -1    0
1    0    0
-1    0   0
0     0    1
0     0    -1
0     0    1
0     0    -1
...
..

But this is not enough to proceed the analysis, because the 1s and -1s are replicates.

So I tried to estimate the correlation within replication block:

biolrep <- c(1,1,2,2,3,3,..... 50,50)
corfit <- duplicateCorrelation(data, design, ndups = 1, block = biolrep)

And I have
corfit$consensus = -0.84
(good, they are dye swapped)

And I fit the model

fit <- lmFit(data, design, block = biolrep, cor = corfit$consensus)

Then I create and extract my contrasts:

cont.matrix <- makeContrasts( sick1.2 = sick1-sick2 ...etc)                              
fit2 <- contrasts.fit(fit, cont.matrix)
fit2 <- eBayes(fit2)

I'm not sure I understood very well everything. There's some mistakes I'm making?

Any suggestion will be really appreciated...

Thanks

Giulio

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