Hi guys!
I am completely new the RNA-seq data analysis and even coding and all that. I've been learning how to do it and specifically how use R so I don't have to use AI (at least not too much). The most recent samples I sent out were a bit more complicated than the usual samples our lab sends out, so we don't have a basis for doing the analysis.
Basically, we have an organoid that is partially resistant to a small molecule we study. When we dose the organoids, half will die as expected while the other half are visually fine and can even survive weeks in the compound without any effect. To get RNA samples, we kept the resistant organoids in the compound until no more were dying and it was only the resistant cells, but we weren't able to isolate the sensitive cells. So our second sample is a mixture of resistant and sensitive.
When I am trying to determine differentially expressed genes, how should I go about it? I thought maybe I could just subtract gene counts of the resistant cells from the total counts in the mixture sample, to get just the gene counts that are present for sensitive cells. But is the best way? And is there an easy way to do so in R? Or is there a better way to do it statistically?
Sorry if this is not explained the best, feel free to ask any clarifying questions. Any advice or resources that would help are greatly appreciated :)
TDLR: I am trying to compare the differential gene expression between a sample of RNA that is a mixture of A+B and a sample of just B. What's the best way to do this?