When you have only one variable with two categories (e.g. disease vs control) to compare for RNA-seq, you assume the expression level follows negative binomial distribution and you can use DESeq, edgeR, etc. software to do differential gene expression analysis. How if your variable is not binary but continues such as treated by a compound with different concentrations (e.g. 0.1nM, 0.2 nM, 0.5nM). Or even more complicated, besides different compound concentrations, you have time points. If you have more than just one binary variable to consider, what do you do for differential gene expression analysis?
What I have in mind is to use:
-log(expression) = case/control + [compound concentration] + time_of_treatment
And check for the p-value for the thetas (slopes) of each variable for significance.