Dear all, dear Michael Love,

The DESeqDataSetFromHTSeqCount() function does not want to accept my design, which is (as suggested by the deseq2 manual):

**design = model.matrix(~group + group:subjectID + group:time)**

```
Group Time SubjectID
A 1 1
A 2 1
A 1 2
A 2 2
A 1 3
A 2 3
A 1 4
A 2 4
A 1 5
A 2 5
B 1 1
B 2 1
B 1 2
B 2 2
B 1 3
B 2 3
B 1 4
B 2 4
B 1 5
B 2 5
B 1 6
B 2 6
```

**As you can see, I have one subject more in group B than in group A. Therefore I deleted the collumn 'GroupA:subjectID6' from the designmatrix.**

But still, the following error occurs: **'The model matrix is not full rank. One or more variables or interaction terms in the design formula are linear combinations of the others and must be removed.'**

Who knows the answer to this problem? Has this something to do with the fact that subject 6 in group B is now a linear combination when comparing B16 to B26? But how to solve this, without losing subject 6?

Many thanks in advance,

Sara

Are you completely sure you want subject as a factor in your design? Is subject 1 from group A really the same as subject 1 in group B? I have no idea what you are trying to compare to what, but I think in general, a lot of people try to include subject or individual as a factor in their design where their experimental design does not warrant it.

It's group x subject, so a subject specific blocking term within each group. See the section of the vignette that describes this design.