Entering edit mode
5.3 years ago
judhenaosa
▴
50
Hi.
I have a question about lima-voom design. I have an experiment just like I'm showing you in the next table:
| Sample | cell-type | treatment |
|---|---|---|
| C.A | A | C |
| S.A | A | S |
| C.B | B | C |
| S.B | B | S |
| N.A | A | N |
| H.A | A | H |
| N.B | B | N |
| H.B | B | H |
As you can see, I have four treatments, the controls (C and N) and treatments (S and H). I need to use limma-voom to find the differential expressed genes in cell type A in the treatment S and treatment H separately, and the same procedure in cell type B. I saw the user guide when defining this problem as the union in the matrix design, i.e the vector C.A, S.A, N.A, H.A, and so on. But this process doesn't find any differential expression gene in any of the possible comparisons. Then, How can I do a correct matrix design for this case?.
Kind regards,
Juan
If I understand correct, your groups are all n = 1. If you want to compare group
C.AversusS.Aboth groups are n = 1 (only one sample per group). You can correct this by adding more biological replicates, to make at least n = 2.Hi.
I forgot to say that, I have biological replicates n=3.
Regards,
Juan
Okay, you also forgot to add your code. It is not possible to help you properly without any code or error reports (if any).
Furthermore, try to make MDS plots and add them to your post as well. If the only problem is that you don't get DE genes, it might be that the groups are really not different (which can be seen in MDS plot).
Could you post the code you used to define both your design matrix and your contrasts, please