I have 35 lung cancer samples and 4 normal tissues. I'm trying to do differential analysis. With the available read counts data using edgeR for differential analysis.
For the filtering steps I'm using this which is mentioned in edgeR tutorial
keep <- rowSums(cpm(y) > 0.5) >= 2
This is where we keep genes with cpm values greater than 0.5 in at least two cases. But with this among 19k genes after filtering it kept 17k genes and when I do differential analysis between lung cancer samples and Normal cases I got only 1000 DEG's with log2 FC 1.2 and FDR <= 0.05
I expected more differential expressed genes. As only 1000 genes were Differentially expressed Is this because of less number of normal samples or do I need to change anything in the filtering step?
Any help is appreciated.