Hi!
I'm dealing with an RNA-Seq dataset where I would like to see if there are any differential expression differences in the expression of mitochondrial genes. However, one problem that I can't seem to overcome is: how do I normalize the number of mitochondria in the samples vs. the actual gene expression of a specific mitochondrial gene?
The package that I typically use for differential expression analysis quantification is RSEM. We are going to be getting the information on the number of mitochondria in the sample cells from an additional wet-lab experiment. What I plan on doing after is then writing a script to adjust the resulting values based on the data from the additional wet-lab experiment for DESEQ2 and edgeR.
Any suggestions?
Hmm not quite responding this, but is the difference in the mitochondria number importat for your question (i.e working with models that regards mitochondrial fusion/fission genes)? If it is, the difference in mitochondrial number should be expect and be reflected in your results. If it's not, I dont see ant direct reason to normalize for that.
If you will normalize, then I think you should look at some classical genes for mitochondria fission, like DNM1L, etc. Maybe some ratio of fission/fusion genes?
Oooo - that's an interesting idea!