[this question has also been posted on Biostars; some additional clarification from there has been copied into this question]
I've been asked to analyse a set of samples in which their control sample has been done in duplicate (biological replicate) but the other samples have just one sample each.
The analysis purpose is just hypothesis generation for further experiment design. So, is it possible to have duplicate samples for one or two of the groups and use one sample for other groups? Could we estimate a constant dispersion from these replicates and apply it to all of the samples for differential gene expression analysis.
EdgeR/Limma for my differential gene expression analysis. When there are no replicates the
eBayes function gives me an error. However, if I add a replicate to just one of the samples, it won't give any errors. Does this mean that it uses the calculated dispersion from the duplicate condition for all of the other one sample conditions? Or is it a bug that it doesn't give an
Should I consider this method of using duplicates for some samples instead of just using no replicates in such large experiments that are being done for hypothesis generation?
I have read the EdgeR recommendations (page 23-24) on what to do without (enough) replicates, but the explanation is not complete. Like it doesn't say how to find these housekeeping genes. About its first case of using a common fixed dispersion. I guess what I'm asking here is I'd like a more reliable measure of this common fixed dispersion. I say instead of using a theoretical dispersion why not try to estimate dispersion from the few duplicate samples and then use it for all the samples. I'm asking if someone has already done this thing and I'd like to know about their experience and how reloable could thing method be.