Analysing and interpreting DNA methylation data

Abstract

Recent technological advances make it possible to map DNA methylation in essentially any cell type, tissue or organism. Computational methods and software tools are essential for processing, analysing and interpreting large-scale DNA methylation data sets. Tailored software tools are now available for processing data obtained with all common methods for genome-wide DNA methylation mapping (including bisulphite sequencing and the Infinium assay). Bioinformatic methods for visualization of DNA methylation data facilitate quality assessment and help to pinpoint global trends in the data. By combining stringent statistical methods with computational and experimental validation, researchers can establish accurate lists of differentially methylated regions for a phenotype of interest. Biological interpretation of differential DNA methylation is aided by computational tools for data exploration and enrichment analysis. Large community projects are currently generating reference epigenome maps for many different cell types; the interpretation of these maps will require a comprehensive effort in functional epigenomics.