Dear all,
I have a time course RNA-seq analysis with the following design: 5 time points, 15 patients, 2 types of patients.
the questions I would like to answer:
a) expression differences across time points irrespective of patient type (t1 vs t2, t1 vs t3, ...)
b) expression differences between the two types of patients for every time point or in general for any time point
should I follow limma's user guide section 9.6.1 or 9.6.2 ?
should I add duplicatecorrelation function to account for repeated measures (same patients each time point)?
should I combine the factors time_point + type_of_patient in one single factor?
thanks for the clarifications.
This is the information I have: patient (p1 to p15), time (t1 to t5), group (A,B)
sample | patient | time | group |
---|---|---|---|
1 | p1 | t1 |
A |
2 | p1 | t2 | A |
3 | p1 | t3 | A |
4 | p1 | t4 | A |
5 | p1 | t5 | A |
6 | p2 | t1 | A |
7 | p2 | t2 | A |
8 | p2 | t3 | A |
9 | p2 | t4 | A |
10 | p2 | t5 | A |
11 | p3 | t1 | B |
12 | p3 | t2 | B |
13 | p3 | t3 | B |
14 | p3 | t4 | B |
15 | p3 | t5 | B |
16 | p4 | t1 | B |
17 | p4 | t2 | B |
18 | p4 | t3 | B |
19 | p4 | t4 | B |
... | .... | ... | ... |
optional design formulas:
1) ~patient+timegroup
2) ~0+timegroup and then duplicatecorrelation to block for patient
3) ~patient+time+group
A design matrix would be helpful. Or at least some code describing the available sample annotation.
sure, I will edit my post.
How many samples do you have in total? If I understand the question it seems that you have three patients for each time points which would be then divided into the 2 types of patients you have. Or it is something helse
I have 5 time points per patient, in total 15 patients. These 15 patients can be further divided in two groups for question b)
For question a) Do you want the answer irrespective of the group or not? (for me the only one that makes sense is the 3rd option. because then you can make the contrasts to answer any question you might have.
Yes, irrespective of the group.