Edger Dealing With Paired Experiment

Question

[liran0921]

Hi all,

I am using EdgeR for DE analysis. I would appreciate if somebody could help me check my experiment design.

I have 6 cows (2,63,66,67,73,74) for a treatment, each with 3 time points(m14,p7,p28). I want to compare between p28 vs m14, p7 vs m14 and p28 vs p7.

cow <- factor(c(2,2,2,63,63,63,66,66,66,67,67,67,73,73,73,74,74,74))
timep <- factor(c("m14","p7","p28","m14","p7","p28","m14","p7","p28","m14","p7","p28","m14","p7","p28","m14","p7","p28"))
data.frame(Sample=colnames(y),cow,timep)
design<-model.matrix(~cow+timep)

This follows the EdgerR user guide (31 March 2013 revised), case study 4.4 on page 53.

And here I have 18 libraries. So I would like to ask what if one library is missing? In this way, how to make the design? If I still use the way mentioned above, Edger cannot handle it.

Thanks.

Answer 1

[Charles Warden]

what if you try:

model.mat <- data.frame(Sample=colnames(y),cow,timep)
design <- model.matrix(~cow+timep, data=model.mat)

Addiitonally, you can try only using the paired samples (and ignoring the unpaired samples).

[liran0921]

Hi, thanks for your reply. The method you proposed get the same design as mine. So I suppose the matrix is right? Here it is:

 (Intercept) cow63 cow66 cow67 cow73 cow74 timepp28 timepp7
           1     0     0     0     0     0        0       0
           1     0     0     0     0     0        0       1
           1     0     0     0     0     0        1       0
           1     1     0     0     0     0        0       0
           1     1     0     0     0     0        0       1
           1     1     0     0     0     0        1       0
           1     0     1     0     0     0        0       0
           1     0     1     0     0     0        0       1
           1     0     1     0     0     0        1       0
           1     0     0     1     0     0        0       0
           1     0     0     1     0     0        0       1
           1     0     0     1     0     0        1       0
           1     0     0     0     1     0        0       0
           1     0     0     0     1     0        0       1
           1     0     0     0     1     0        1       0
           1     0     0     0     0     1        0       0
           1     0     0     0     0     1        0       1
           1     0     0     0     0     1        1       0