Hello,

I have been reading the vignette and online forum about the interaction terms and selection of coef as well as releveling to the reference. I thought I understood it but then it got me confused. My design involves 4 cell lines and 4 conditions so my code is like this:

dds <- DESeqDataSetFromMatrix(countData=cells2, colData = info2, design = cellline + condition + cellline:condition)

Assuming cell line 1 and condition A are my references. If I want to know the effect of condition C vs Condition A in cell line 2 (just cell line 2, not in comparison to cell line 1), I select in the list combining main effect of C and interaction term of cell line 2:

 results(dds, contrast =  list("condition_C_vs_A", "cellline2.conditionC"), independentFiltering = T, pAdjustMethod = "fdr")

Is this correct? Based on my understanding of linear regression, it makes sense to add the main effect plus the interaction term. But when I look at the results, it says that the logFC is based on condition_C_vs_A vs celline2.conditionC. If I follow this in the model matrix, it means that the numerator is all condition C (in all cell lines) and denominator are samples of cell 2 condition C. So the differential genes I am seeing is comparing the C in all cell lines vs C in cell line 2. Did I understand this correctly? But what I want is to compare Condition C to Condition A in cell line 2 only. How do I get this?

When I try to select just the interaction term, it says that the logFC is "cellline2.conditionC effect". What does this mean exactly? Is it the samples of the cell line 2 condition 2 compared to the reference Cell line 1 condition A? Apologies if my questions are very basic but I really want to understand how all the comparisons and contrasts work exactly so I know how to use it both for the results() as well as for the lfcShrink() which allows only one coef.

Thank you!

Please see the diagram in the vignette on interactions, but for further questions on setting up the design, I recommend to consult with a local statistician or someone familiar with linear models in R. I unfortunately have to limit my time on the support site to software-specific questions.