Abstract
DNA methylation is one of the most commonly studied epigenetic marks, due to its role in disease and development. Illumina methylation arrays have been extensively used to measure methylation across the human genome. Methylation array analysis has primarily focused on preprocessing, normalization, and identification of differentially methylated CpGs and regions. GOmeth and GOregion are new methods for performing unbiased gene set testing following differential methylation analysis. Benchmarking analyses demonstrate GOmeth outperforms other approaches, and GOregion is the first method for gene set testing of differentially methylated regions. Both methods are publicly available in the missMethyl Bioconductor R package.
Highlights
DNA methylation is essential to human development, with roughly 3–6% of all cytosines methylated in normal human DNA [1]
In order to perform gene set enrichment analysis based on the results from a probe-wise differential methylation analysis, we need to annotate each probe on the array to a gene
One approach for gene set testing is to call a gene differentially methylated if at least one CpG site associated with that gene is significantly differentially methylated, and this has been used in many previous analyses (e.g., Zhang et al [27], Phipson and Oshlack [28])
Summary
DNA methylation is essential to human development, with roughly 3–6% of all cytosines methylated in normal human DNA [1]. Aberrant methylation patterning is associated with many diseases, which has led to several large studies profiling DNA methylation, such as The Cancer Genome Atlas, Encyclopedia of DNA Elements, and numerous epigenome-wide association studies. Both array- and sequencing-based technologies are available for profiling DNA methylation at a genome-wide scale. A major focus when analyzing DNA methylation data has been the identification of significantly differentially methylated CpG sites between groups of samples in a designed experiment. It is well established that methylation of CpG sites is spatially correlated along the genome [12] and that long tracks of differential methylation are often more biologically meaningful
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