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?
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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!