Hello, I am new to DESeq2/RNAseq and would like a little help. I have performed a RIPSeq experiment with conditions described below (mouse neural tissue harvested after drug injections). I am aware that there are alternatives such as RipSeeker, however I am treating my samples as RNAseq for the time being. I have imported my raw counts into R and analyzed them with DESeq2. However, I am unsure how to take my knockouts into account. In this case, the knockouts essentially represent background bead binding. Since RIPSeq tends to be noisy, I need to "subtract" out any RNAs that might bind at a background level. I have read online that I cannot subtract counts but then I am not quite sure how to compare my DESeq2 results data frames between WT and KO.<caption>Experimental design</caption>
|KO||Solvent 2 KO||3|
|KO||Drug 1 KO||1|
|Experimental||Drug 1 + Drug 2||3|
|KO||Drug 1 + Drug 2 KO||3|
It is also important to mention that since drug 1 and drug 2 have different solvents, I have controls for each separate solvent. The hope is that the two solvents alone will not show a huge difference in what I immunoprecipitated.
Here is my analysis strategy:
- Collapse technical replicates (there are two technicals for each biological replicate)
- Slice up DESeq2 object into subsets that include the condition as well as the total RNA
- Run results on each of these comparing the condition against the total RNA to find enrichment
- Compare each condition and its knockout pair to see if any top differentially expressed genes showed up in both experimental and KO
- If so, remove gene from experimental condition list
So my question is whether or not this is valid and if there is a better way to do this kind of comparison to deal with the knockouts given my experimental conditions.