Exponentially increasing numbers of NGS-based epigenomic datasets in public repositories like GEO constitute an enormous source of information that is invaluable for integrative and comparative studies of gene regulatory mechanisms. One of todays challenges for such studies is to identify functionally informative local and global patterns of chromatin states in order to describe the regulatory impact of the epigenome in normal cell physiology and in case of pathological aberrations. Critically, the most preferred Chromatin ImmunoPrecipitation-Sequencing (ChIP-Seq) is inherently prone to significant variability between assays, which poses significant challenge on comparative studies. One challenge concerns data normalization to adjust sequencing depth variation.