Analyzing epigenome data in context of genome evolution and human diseases

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

Abstract

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Chromosomes, Human / genetics
  • CpG Islands / genetics
  • DNA Methylation / genetics
  • Data Interpretation, Statistical
  • Databases, Genetic
  • Disease / genetics*
  • Epigenomics / methods*
  • Evolution, Molecular*
  • Female
  • Genome, Human / genetics*
  • Humans
  • Mice
  • Ovarian Neoplasms / genetics
  • Promoter Regions, Genetic / genetics
  • Software