Hi all

• I use limma to do the differential expression analysis, I want to do the volcano plot, x-axis is logFC and y-axis is -1*log10(adjust p). But I found the the adjust p output by limma is so small and after -log10 transfor is up to 300, thats mean the p value gived by limma is 1*E-300 unit. But in other paper , the adjust p value is about 1*E-30 unit, and -log10 is about 30. Why the p value is so small in limma? How can I change p value to 1*E-30 unit.
• The logFC is small too. I try to calculate the mean expression for each genes in disease samples and mean value in normal value, then get the logFC, its larger than what limma output . And if I use log2(2) threshold , there is nearly no genes significant express. I have to use log2(1.5) even log2(1.2). Why there are so many genes are so signaficant (with very low p value) but also with a very small logFC at the same times? Can I still consider this genes are differentrial expression(depend on adjust p) even they with small logFC ?

Best

You haven't told us anything about your data or analysis, so it's impossible to say why you get the results that you do.

If your data has a huge number of replicates, then it would be natural to get small p-values even when the fold changes are relatively modest.

The limma volcanoplot function uses -log10(p-value) for the y-axis, not -log10(adjust p).