Moved to an answer as this is, from my perspective at least, the one and only way to answer a question on this topic. In addition, mlai2567, you should clarify whether you are using log (base 2) fold changes - most likely you are. Keep in mind that, if using log (base 2), then a cut-off of 1.5 still equates to an un-logged difference of 2.83 fold change (2^1.5)
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Kevin Blighe
I never apply a fold-change threshold for differential expression.
Can you elaborate on that?
I think that some just recommend to order genes by fold-change, as opposed to just setting a hard filter threshold. Any good and honest analyst will understand the limitations of setting a hard threshold, and also the limitations of not setting a threshold.
That's for sure. I was just bit surprised to hear that one should never apply FC threshold.
Nobody implied that nobody should ever apply such a threshold. russhh just stated that he never uses it.
The elaboration being that I only ever apply p-value / FDR thresholds for differential expression; what matters is reproducibility not the estimated change. For biomarker discovery, I might apply an FC threshold.
Hi mlai2567, can I ask you how did you perform the differential gene expression analysis? I have two dataset, control and stimolate, and I would like to know what is the fold change of all genes of a specific population (in my case the subpopulation is macrophages Adgre1+)