hi Max,

To compare the response to treatment in A and B you would use an
interaction term:

design(dds) <- ~ condition + treatment + condition:treatment
DESeq(dds)
results(dds)
# this last line is all that is needed because the interaction term is last
in the design formula
# equivalently, you can check the name in resultsNames(dds) and then it
will be something like
results(dds, name="conditionB.treatmenttreat")

Small p-values for the interaction term indicate that the log fold change
due to treatment is significantly different for the two conditions.

Mike



On Thu, Mar 6, 2014 at 6:38 AM, Kauer Max <maximilian.kauer@ccri.at> wrote:

> Hi,
> I have a RNAseq dataset with this design:
>
>                condition       treatment
> sample1        A                 treat
> sample2        A                 treat
> sample3        A                 con
> sample4        A                 con
> sample5        B                 treat
> sample6        B                 treat
> sample7        B                 con
> sample8        B                 con
>
>
> so there are two conditions and within each condition treatment and
> control.
> So far I simply compared treat vs. con within each group, so I get logFCs
> and
> p values for A and B separately (for this I actually subsetted the dataset
> and used ~treatment as design)
>
> Now I would also like compare the two conditions to see genes that respond
> differently to treatment in A and in B.
> So my question: how do I set up the design for that?
>
> Thanks in advance!
> max
>
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