I want to visualize the difference in chip-signal at specific locations by making average profiles using deeptools. For this I have generated RPKM normalized bigwig files for my treatment and control conditions and plotting them gives me good results. However, these files are not input normalized and I am concerned that this therefore may not be the best way to do the analysis.
I am now using deeptools bigwigCompare to normalize each file against its input. This gives a normalized bigwig file that shows log fold change over input. However, when I look at this file in IGV, I see a lot of regions with negative values which implies that these regions had more signal in the input than in the chip sample. I am not sure what to do with these regions or if they mean that my experiment was not reliable? Should I just remove all negative values from the bigwig files (is there a tool to do this?) and compare the positive values between treatment and control using plotprofile?
Also since I am comparing conditions, is it ok if I don’t input normalize and stick to the first approach? Would appreciate any feedback.