Hi BioC List,

I'm working with an affymetrix data set where the batches are completely confounded with the factor of interest for one contrast, treatment time.  From my understanding I can use something like fRMA to partially mitigate the effect, but otherwise not much I can do.

However, we do have the original tissue samples and the option to re-extract/reprocess some samples in a new batch.  Due to the study size, rerunning all samples with a proper randomized design is out of the question.  Are there any studies describing how we might rerun a small subset of samples to recover the contrast of interest?  Or does anyone have any advice?  For example, can I run 10 samples from each time point in a new batch - could that be sufficient?  Clearly it could depend on the size of the batch effect, so I understand that there is probably no definitive answer...

Here's the sample breakdown with the relevant treatments/covariates - you can see that timepoints t1 and t2 are completely confounded with batch, while timepoints t2 and t3 are not. I also included another covariate that we want to account for, Ethnicity, and the number of samples in each group:
Batch  Timepoint   Ethnicity  Num_Samples
b1         t1         A         21
b1         t1         B         54
b2         t1         A         20
b2         t1         B         56
b3         t2         A         10
b3         t2         B         35
b3         t3         A         9
b3         t3         B         38
b4         t2         B         49
b4         t3         A         1
b4         t3         B         43
b5         t2         A         28
b5         t2         B         4
b5         t3         A         25
b5         t3         B         21
Here's the setup that I would like (note that I'm also including patientID in the design matrix since there are many patients that have a sample at multiple time points):

design <- model.matrix(~ -1 + Timepoint + Ethnicity + Batch + PatientID)
fit <- lmFit(eset, design)
contrast.matrix <- makeContrasts(Timepointt2 - Timepointt1, levels=design)
fit2 <- contrasts.fit(fit, contrast.matrix)
fit <- eBayes(fit)

If we do reprocess samples, do I need to ensure even representation of the two ethnicities in the new batch?

Thanks in advance for the guidance!

Ty


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