Illustration of DNA wrapped around histone proteins. Source: Adapted from the website of the National Cancer Institute.
DNA methylation is an important mechanism regulating gene transcription, and its role in carcinogenesis has been extensively studied. Hyper and hypomethylation of genes is an alternative mechanism to deregulate gene expression in a wide range of diseases. At the same time high throughput DNA methylation assays have been developed generating vast amounts of genome wide DNA methylation measurements. Yet few tools exist that can formally identify hypo and hypermethylated genes that are predictive of transcription and thus functionally relevant for a particular disease. To accommodate this lack of tools, we developed MethylMix, an algorithm implemented in R to identify disease specific hyper and hypomethylated genes. MethylMix is based on a beta mixture model to identify methylation states and compares them with the normal DNA methylation state. MethylMix introduces a novel metric, the "Differential Methylation value" or DM-value defined as the difference of a methylation state with the normal methylation state. Finally, matched gene expression data is used to identify, besides differential, transcriptionally predictive methylation states by focusing on methylation changes that effect gene expression. (Publication Summary)