I am analysing our RNA-seq data to find DEG responding our drug combinations and have a few questions.
I have 4 conditions and per each condition I have 3 replicates
group 1. Control (3 replicates) group 2. Disease model (3 replicates) group 3. Disease model + 1 drugs ( 3 replicates) group 4. Disease model + 1 drugs + 1 adjuvants ( 3 replicates)
My hypothesis is that the drug is effective, and hopefully with adjuvants, it is much more effective....
In order to test this hypothesis I would like to compare several things.
comparison 1. group 1 vs group 2 ( the genes affected by disease) comparison 2. group 2 vs group 3 (the genes affected by drug ) comparison 3. group 3 vs group 4 (the genes affected by adjurvants) comparison(maybe) 4. group 1 vs group 3 (expect that there are not so many DEG if drug is effective) comparison (maybe) 5. group 1 vs group 4 (expect that there are not so many DEG if drug+adjurvants is effective)
First of all, I made a dataset with these 4 groups of data to find DEGs responding one of above comparions. (by adjusting other factors)
However, it seems that it brings too many variances due to the group 2 (which is a disease model ) Note that other three groups indicate the cure model ( recovered from disease)
Could you please someone recommend that whether I just need to compare only each of two groups? ( For example, for comparison 1 , I can just use two data set from group 1 and group2 etc.. )