I always selected top differentially expressed genes based on p-values (DESeq2 for differential-expr analysis). Just recently, someone suggested me to use both p-value and fold change to select top genes. I am little confused as p-values already take fold-change into consideration. Can someone shed some more light on what I am missing here?
Fold change is a measure of the ratio of means of two populations (say control and treatment).
p value measures how much confidence you have in that ratio. The p value usually will take into account the difference in means and variances (or standard deviation) of the populations being compared, but not directly the fold-change. Of course, if the fold change is high => difference in mean is high => the gene has more chance to becomes significant. However, even if the difference in mean is small, and the variances in two groups are also small => you are confident that this difference is real and not coming just by chance => the gene could become significant. That is to say, p-value is not directly determined by fold change