I have a dataset where I want to see effect of a drug on my patients who responded and not responded towards treatment. I collected their blood at three different time point or visit. For each patient I have their age and sex information with me. Now to perform differential expression analysis I used DESeq2 to perform time series analysis as I have collected blood at three different visit. I want to control age and gender effect on my data so I can see interaction between responder group and different time point
Here is the sample table and my DESeq2 design formula:
sample Phenotype visit Age Gender
1 NonResponder 1 42 female
2 NonResponder 2 42 female
3 NonResponder 3 42 female
4 NonResponder 1 49 female
5 NonResponder 2 49 female
6 NonResponder 3 49 female
7 NonResponder 1 27 male
8 NonResponder 2 27 male
9 NonResponder 3 27 male
10 NonResponder 1 51 female
11 NonResponder 2 51 female
12 NonResponder 3 51 female
13 NonResponder 1 52 male
14 NonResponder 2 52 male
15 NonResponder 3 52 male
16 NonResponder 1 58 male
17 NonResponder 2 58 male
18 NonResponder 3 58 male
19 NonResponder 1 27 female
20 NonResponder 2 27 female
21 NonResponder 3 27 female
22 NonResponder 1 55 male
23 NonResponder 2 55 male
24 NonResponder 3 55 male
25 NonResponder 1 45 male
26 NonResponder 2 45 male
27 NonResponder 3 45 male
28 NonResponder 1 42 female
29 NonResponder 2 42 female
30 NonResponder 3 42 female
31 Responder 1 77 female
32 Responder 2 77 female
33 Responder 3 77 female
34 Responder 1 51 male
35 Responder 2 51 male
36 Responder 3 51 male
37 Responder 1 47 male
38 Responder 2 47 male
39 Responder 3 47 male
40 Responder 1 51 male
41 Responder 2 51 male
42 Responder 3 51 male
43 Responder 1 56 male
44 Responder 2 56 male
45 Responder 3 56 male
46 Responder 1 47 female
47 Responder 2 47 female
48 Responder 3 47 female
49 Responder 1 53 male
50 Responder 2 53 male
51 Responder 3 53 male
52 Responder 1 35 female
53 Responder 2 35 female
54 Responder 3 35 female
55 Responder 1 58 female
56 Responder 2 58 female
57 Responder 3 58 female
So which design should I use to control age and gender effect on my data
design 1:
dds=(design= ~age+gender+visit+phenotype+visit:phenotype+age:phenotype+gender:phenotype)
dds=DESeq(dds)
design 2:
dds=(design=~age+gender+visit+phenotype+visit:phenotype)
dds=DESeq(dds,test="LRT", reduced=~age+gender)
I will highly appreciate help with this
Best,
Lalit
