Dear all,

we performed RNAseq for a set of mouse samples. The samples come from different mouse strains, and from different knockout lines. Here is an excerpt of the sample metadata:

sample  condition      strain
1       WT             B6
2       WT             B6
3       WT             B6
4       Gene1KO        B6
5       Gene1KO        B6
6       Gene1KO        B6
7       Gene1KO        FOO
8       Gene1KO        FOO
9       Gene1KO        FOO
10      WT             BAR
11      WT             BAR
12      WT             BAR
13      Gene2KO        B6
14      Gene2KO        B6
15      Gene2KO        B6
16      WT             FOO
17      WT             FOO
18      WT             FOO

For the B6 strain, there are other knockouts than Gene1KO and Gene2KO which I omitted.

My design is:

design(dds) <- 0 + strain + condition

In general, the comparisons are straightforward to do because we want to compare the KOs to the WTs of the same strain. They are mostly in the B6 strain.

res1 <- results(dds, contrast = c("condition", "Gene1KO", "WT")
res2 <- results(dds, contrast = c("condition", "Gene2KO", "WT")

In a few particular cases, though, we are interested in comparing WT individuals of strain BAR to the overall effects of knockout Gene1KO, essentially treating strain as a batch variable. Phenotypically, we expect them to be similar overall with potentially pronounced effects in a few specific pathways. The Gene1KO samples come from several strains, but not from strain BAR. Incorporating the interaction condition:strain is not possible because we lack Gene1KO:BAR.

I believe this does what we want:

res3 <- results(dds, contrast = list("conditionGene1KO", "strainBAR")

Is this a valid approach to take? It runs fine, but results in ~22500 significant hits out of ~22800 genes after lfcShrink, which makes me a bit suspicious ...

Thanks in advance!

That last contrast doesn't make sense, comparing across coefficients from different design terms. I'd recommend consulting with a local statistician on your statistical analysis plan.