please see my data here:
These are not raw data but normalized after edgeR. I list the first few genes with highest fold change, and found one sample is definitely a outlier (highlight in yellow), which cause high fold change (If I remove this outlier, the fold change is only 2 fold-ish.) I am so surprised that the p value and FDR are both extremely small even with an outlier.
Is it common issue when use edgeR for differential expression?
If it is a real issue, how could I find out outlier if I have a large set samples (eg, >100 samples) for data analysis?
We usually use DEseq2 for DE, DEseq2 can identify outlier and report NA for p value.