I'm having an odd problem while trying to set up a design matrix to do downstream pairwise differential expression analysis on RNAseq data. For the design matrix, I have both the donor information and each condition:
group<-factor(y$samples$group) #44 samples, 6 different conditions
sample<-factor(y$samples$samples) #44 samples, 11 different donors.
design<- model.matrix(~0+sample+group)
head(design)
Donor11.CD8 Donor12.CD8 Donor14.CD8 Donor15.CD8 Donor16.CD8
1 1 0 0 0 0
2 1 0 0 0 0
3 1 0 0 0 0
4 1 0 0 0 0
5 1 0 0 0 0
6 1 0 0 0 0
Donor17.CD8 Donor18.CD8 Donor19.CD8 Donor20.CD8 Donor3.CD8
1 0 0 0 0 0
2 0 0 0 0 0
3 0 0 0 0 0
4 0 0 0 0 0
5 0 0 0 0 0
6 0 0 0 0 0
Donor4.CD8 Treatment2 Treatment3 Treatment4 Treatment5
1 0 0 0 0 0
2 0 0 0 0 1
3 0 0 0 1 0
4 0 0 0 0 0
5 0 0 1 0 0
6 0 1 0 0 0
Treatment6
1 1
2 0
3 0
4 0
5 0
6 0
>
The issue is that I seem to be losing a condition (treatment 1) when I form the design matrix, and I'm not sure why.
Many thanks, in advance, for your help!
That's not a problem. Treatment 1 is indicated by all 0 for the columns in the design matrix. Look at row 4 - zero for Treatments 2 through 6. That means it is Treatment 1. This is called a "treatment contrast" because the coefficients in the model contrast the named treatment against the "base" level, in this case the base level is Treatment1.
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