Time-series experiment with patients from 2 conditions and 5 time-points from each patient

Hi everyone, I am trying to create a DEseq2 model matrix for my RNA-seq experiment. I have two conditions (treated vs untreated) and in each condition 10 patients (10 different patients in treated, 10 different patients in untreated group) and from each patient I have 5 time-points (baseline,10min, 3h, 6h, 24h). I would like to identify DE genes whose expression profiles across my time-points are different in the treated vs untreated group. I am now struggling with how to create my design for DESeq2. If my time-points were independent (not always 5 from the same patient), I would go for full model ~ condition + time + condition:time and reduced ~ condition + time. But when I ignore the non-independency of my time-points, in the PCA plot I can see that samples cluster more based on the patient they originated from rather than time-points or conditions. So I have a patient batch effect I need to remove. But I am not able to find out how (or if) that is possible to do with DESeq2, because if I add my patient effect into the model (like this ~ patient + condition + time + condition:time) I get an error that my model matrix is not full rank (which makes sense since I do not have the same patients in both groups).

My experimental design looks like this:

sample  condition   time        patient
01_A_SE treated     baseline    pat01
01_C_SE treated     10min       pat01
01_D_SE treated     3h          pat01
01_E_SE treated     6h          pat01
01_F_SE treated     24h         pat01
02_A_SE treated     baseline    pat02
02_C_SE treated     10min       pat02
02_D_SE treated     3h          pat02
02_E_SE treated     6h          pat02
02_F_SE treated     24h         pat02
.       .           .           .
.       .           .           .
.       .           .           .
18_A_SE untreated   baseline    pat18
19_C_SE untreated   10min       pat18
19_D_SE untreated   3h          pat18
19_E_SE untreated   6h          pat18
19_F_SE untreated   24h         pat18
20_A_SE untreated   baseline    pat20
20_C_SE untreated   10min       pat20
20_D_SE untreated   3h          pat20
20_E_SE untreated   6h          pat20
20_F_SE untreated   24h         pat20

Is there a way how do this in DESeq2, or do I have to look into limma or some other software?

Thank you very much!

Karolina

Take a look at the vignette section under Interactions, on group-specific condition effects, individuals nested within groups. This applies to your design with group = treatment and condition = time.