Hi all, I'm working with my RNA-Seq raw count data right now. I'm in the process of determining differentially expressed genes among the file, and I used DESeq2 package for R to do that.
#run the DESeq pipeline
dds <- DESeq(dds)
#delete all the data that have total of 0 counts
#get differential expression results
If I use this code above, it gives me bunch of same numbers for the adjusted p-value, which I don't think is correct. And I think since this is a multiple comparison, I need to use adjusted p-values instead of just p-values. I'm trying to find the genes that have p-values<0.05.
My question is,
1) In this case, what cutoff value should I use instead of 0.05? Many articles used 0.1, but is there a specific reason to use that number?
2) As for the reason why the above code have me bunch of same numbers, is it because of the data size? I have more than 30,000 genes in the file. If this is so, then what is the alternative way to identify at differentially expressed genes?
Thanks a lot!