I think factor is not the right term to use here, and is even confusing.
In this case there are probably many regions (segments) either methylated or not. That is just one factor, but many tests. There for you'll have to use a multiple testing correction.
For omics data most people use FDR corrected p-values, Bonferroni is much too stringent. Don't use raw p-values with omics data.
I think you should learn about multiple testing correction. It is perfectly possible that after correction, you don't get any significant test. This just means that at the level of confidence you selected, you can't reject the null hypothesis (usually of no difference between samples). However, don't make the mistake of thinking that statistical significance means biological relevance.
Nice way to put it. It is important to understand how one performs the multiple testing. The line sentence speaks volumes about correlation of statistical testing with biological significance.