I'm currently working on RNA-seq analysis, and my goal is to get differentially expressed genes using DESeq2.
I have 2 groups, A and B, and each group contains 6 samples. After using DESeq2, I got 1405 DEGs in total. Code as following:
dds <- DESeq(dds) res = results(dds, cooksCutoff=TRUE, contrast=c("condition", "group A", "group B"), independentFiltering=TRUE)
However, when I tried to use one single sample from group A against group B (6 samples), the number of DEGs is very small:
sample 1 from group A vs group B: 11 DEGs sample 2 from group A vs group B: 245 DEGs sample 3 from group A vs group B: 35 DEGs sample 4 from group A vs group B: 21 DEGs sample 5 from group A vs group B: 7 DEGs sample 6 from group A vs group B: 20 DEGs
Although using one single sample from group A against group B (6 samples) will lead to different number of DEGs comparing to group A(6 samples) vs group B (6 samples), but the numbers I got is too few and I believe something went wrong.
The possible reason I guess is that using one single sample, the estimated size factor and dispersion are changed, this will lead to another different fitted regression model. But this still cannot explain why the number of DEGs is small.
Any help would be appreciated, thanks in advance!