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Methods Mol Biol. 2012;856:431-67. doi: 10.1007/978-1-61779-585-5_18.

Analyzing epigenome data in context of genome evolution and human diseases.

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  • 1Max Planck Institute, Saarbrücken, Germany.


This chapter describes bioinformatic tools for analyzing epigenome differences between species and in diseased versus normal cells. We illustrate the interplay of several Web-based tools in a case study of CpG island evolution between human and mouse. Starting from a list of orthologous genes, we use the Galaxy Web service to obtain gene coordinates for both species. These data are further analyzed in EpiGRAPH, a Web-based tool that identifies statistically significant epigenetic differences between genome region sets. Finally, we outline how the use of the statistical programming language R enables deeper insights into the epigenetics of human diseases, which are difficult to obtain without writing custom scripts. In summary, our tutorial describes how Web-based tools provide an easy entry into epigenome data analysis while also highlighting the benefits of learning a scripting language in order to unlock the vast potential of public epigenome datasets.

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