The promise of epigenome-wide association studies (EWAS) and cancer specific somatic changes in improving our understanding of cancer coupled with the decreasing cost and increasing coverage of DNA methylation microarrays, has brought about a surge in the use of these technologies. Here, we aim to provide both a review of issues encountered in the processing and analysis of array-based DNA methylation data, as well as to summarize advantages of recent approaches proposed for handling those issues; focusing on approaches publicly available in open-source environments such as R and Bioconductor. The processing tools and analysis flowchart described we hope will facilitate researchers to effectively use these powerful DNA methylation array-based platforms, thereby advancing our understanding of human health and disease.Keywords: Processing, Microarray, Analysis, DNA methylation, Bioconductor and R package
