Current genome-wide ChIP-seq experiments on different epigenetic marks aim at 
unraveling the interplay between their regulation mechanisms. Published 
evaluation tools, however, allow testing for predefined hypotheses only. Here, 
we present a novel method for annotation-independent exploration of epigenetic 
data and their inter-correlation with other genome-wide features. Our method is 
based on a combinatorial genome segmentation solely using information on 
combinations of epigenetic marks. It does not require prior knowledge about the 
data (e.g. gene positions), but allows integrating the data in a straightforward 
manner. Thereby, it combines compression, clustering and visualization of the 
data in a single tool. Our method provides intuitive maps of epigenetic patterns 
across multiple levels of organization, e.g. of the co-occurrence of different 
epigenetic marks in different cell types. Thus, it facilitates the formulation 
of new hypotheses on the principles of epigenetic regulation. We apply our 
method to histone modification data on trimethylation of histone H3 at lysine 4, 
9 and 27 in multi-potent and lineage-primed mouse cells, analyzing their 
combinatorial modification pattern as well as differentiation-related changes of 
single modifications. We demonstrate that our method is capable of reproducing 
recent findings of gene centered approaches, e.g. correlations between 
CpG-density and the analyzed histone modifications. Moreover, combining the 
clustered epigenetic data with information on the expression status of 
associated genes we classify differences in epigenetic status of e.g. 
house-keeping genes versus differentiation-related genes. Visualizing the 
distribution of modification states on the chromosomes, we discover strong 
patterns for chromosome X. For example, exclusively H3K9me3 marked segments are 
enriched, while poised and active states are rare. Hence, our method also 
provides new insights into chromosome-specific epigenetic patterns, opening up 
new questions how "epigenetic computation" is distributed over the genome in 
space and time.