Literature DB >> 22399470

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

Lars Feuerbach1, Konstantin Halachev, Yassen Assenov, Fabian Müller, Christoph Bock, Thomas Lengauer.   

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.

Entities:  

Mesh:

Year:  2012        PMID: 22399470     DOI: 10.1007/978-1-61779-585-5_18

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  1 in total

1.  Comparative analysis using K-mer and K-flank patterns provides evidence for CpG island sequence evolution in mammalian genomes.

Authors:  Heejoon Chae; Jinwoo Park; Seong-Whan Lee; Kenneth P Nephew; Sun Kim
Journal:  Nucleic Acids Res       Date:  2013-03-21       Impact factor: 16.971

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.