Abstract

Epigenomic studies aim to define the location and nature of the genomic sequences that are epigenetically modified. Much progress has been made towards whole-genome epigenetic profiling using molecular techniques, but the analysis of such large and complex data sets is far from trivial given the correlated nature of sequence and functional characteristics within the genome. We describe the statistical solutions that help to overcome the problems with data-set complexity, in anticipation of the imminent wealth of data that will be generated by new genome-wide epigenetic profiling and DNA sequence analysis techniques. So far, epigenomic studies have succeeded in identifying CpG islands, but recent evidence points towards a role for transposable elements in epigenetic regulation, causing the fields of study of epigenetics and transposable element biology to converge.

Author affiliations

1. Departments of Epidemiology and Social Medicine, Albert Einstein College of Medicine, Bronx, New York 10461, USA.
2. Departments of Medicine (Hematology) and Molecular Genetics, Albert Einstein College of Medicine, Bronx, New York 10461, USA.

Correspondence to: Melissa J. Fazzari¹ Email: mfazzari@aecom.yu.edu

Correspondence to: John M. Greally² Email: jgreally@aecom.yu.edu

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