DNA, and m6A in RNA, with detection of other natural or synthetic epigenetic modifications possible through training basecalling algorithms. Differentially methylated regions (DMRs) Differentially methylated regions, which are genomic regions with different methylation statuses among multiple samples (tissues, cells, individuals or others), are regarded as possible functional regions involved in gene transcriptional regulation. The identification of DMRs among multiple tissues (T-DMRs) provides a comprehensive survey of epigenetic differences among human tissues. For example, these methylated regions that are unique to a particular tissue allow individuals to differentiate between tissue type, such as semen and vaginal fluid. Current research conducted by Lee et al., showed DACT1 and USP49 positively identified semen by examining T-DMRs. The use of T-DMRs has proven useful in the identification of various body fluids found at crime scenes. Researchers in the forensic field are currently seeking novel T-DMRs in genes to use as markers in forensic DNA analysis. DMRs between cancer and normal samples (C-DMRs) demonstrate the aberrant methylation in cancers. It is well known that DNA methylation is associated with cell differentiation and proliferation. Many DMRs have been found in the development stages (D-DMRs) and in the reprogrammed progress (R-DMRs). In addition, there are intra-individual DMRs (Intra-DMRs) with longitudinal changes in global DNA methylation along with the increase of age in a given individual. There are also inter-individual DMRs (Inter-DMRs) with different methylation patterns among multiple individuals. QDMR (Quantitative Differentially Methylated Regions) is a quantitative approach to quantify methylation difference and identify DMRs from genome-wide methylation profiles by adapting Shannon entropy. The platform-free and species-free nature of QDMR makes it potentially applicable to various methylation data. This approach provides an effective tool for the high-throughput identification of the functional regions involved in epigenetic regulation. QDMR can be used as an effective tool for the quantification of methylation difference and identification of DMRs across multiple samples. Gene-set analysis (a.k.a. pathway analysis; usually performed tools such as DAVID, GoSeq or GSEA) has been shown to be severely biased when applied to high-throughput methylation data (e.g. MeDIP-seq, MeDIP-ChIP, HELP-seq etc.), and a wide range of studies have thus mistakenly reported hyper-methylation of genes related to development and differentiation; it has been suggested that this can be corrected using sample label permutations or using a statistical model to control for differences in the numbers of CpG probes / CpG sites that target each gene. DNA methylation marks DNA methylation marks