Dear all I have 6 microarray data set and I want to select a cut off base on adj. p.value and fold change to find DEGs. About adj. p.value, I know a cut off less than .05 or .01 are the best but what is the best fold chang cutoff if we want to compare different datasets? all datasets are affymatrix and normalized base on R package.
While there is no ideal cutoff for p-value (which has to be corrected for multiple testing) and fold change, you can have a look at a similar or reference studies and choose cutoffs based on them to be able to make fare comparisons with already published results.
I assume that all of your datasets are the same array type / version? How have you processed and normalised them - all together?
There are no correct cut-offs. The cut-offs change in each and every study. So, not even P 0.05 or 0.01 should be regarded as the best cut-of for statistical significance. Also, you should be using FDR-adjusted P values, i.e., Q values.
For fold-changes, there is neither any correct cut-off. Some use absolute log (base 2) fold change 1.0, whilst others use 2.0. Others don't set any fold-change cut-offs and instead just rank the statistically-significant genes based on fold-change.
You are the analyst and you are in control.