I want to study the effect of TGF-beta between two genotypes WT and KO. To compare the two genotypes, we have knocked out (KO) the gene using the parental as WT control. Then we have stimulated the cells with TGF-beta at 1 hour and 24 hours.
I created a design matrix for comparing the groups that looks like this:
my.design <- model.matrix(~ 0 + design, data=matrix)
KO1hControl KO1hTGF KO24hControl KO24hTGF WT1hControl WT1hTGF WT24hControl WT24hTGF
1 0 0 0 0 0 1 0 0
2 0 0 0 0 0 0 0 1
3 0 0 0 0 1 0 0 0
4 0 0 0 0 0 0 1 0
5 0 1 0 0 0 0 0 0
6 0 0 0 1 0 0 0 0
7 1 0 0 0 0 0 0 0
8 0 0 1 0 0 0 0 0
9 0 0 0 0 0 1 0 0
10 0 0 0 0 0 0 0 1
11 0 0 0 0 1 0 0 0
12 0 0 0 0 0 0 1 0
13 0 1 0 0 0 0 0 0
14 0 0 0 1 0 0 0 0
15 1 0 0 0 0 0 0 0
16 0 0 1 0 0 0 0 0
17 0 0 0 0 0 1 0 0
18 0 0 0 0 0 0 0 1
19 0 0 0 0 1 0 0 0
20 0 0 0 0 0 0 1 0
21 0 1 0 0 0 0 0 0
22 0 0 0 1 0 0 0 0
23 1 0 0 0 0 0 0 0
24 0 0 1 0 0 0 0 0
25 0 0 0 0 0 1 0 0
26 0 0 0 0 0 0 0 1
27 0 0 0 0 1 0 0 0
28 0 0 0 0 0 0 1 0
29 0 1 0 0 0 0 0 0
30 0 0 0 1 0 0 0 0
31 1 0 0 0 0 0 0 0
32 0 0 1 0 0 0 0 0
I have compared the samples to see the effect of TGF-beta stimulation: WT1hTGF - WT1hControl, KO1hTGF - KO1hControl .. And so on. Now I would like to compare the samples which genes differ between WT and KO when stimulated with TGF-beta.
Does anyone have a suggestion how such a matrix would look like?
I am sorry, but I am still not sure how I would construct the contrast. For example If I would like to show which genes are up regulated in KOTGF treated compared to WTTGF.