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Recently, great interest has been aroused in decoding DNA methylation patterning to understand the generation of cell diversity. In addition to tracing the cell lineage (Shibata, 2012; Tsai et al., 2012), DNA methylation patterns can be used as a measure of the epigenetic heterogeneity in cell populations (Xie et al., 2011). In particular, with the emergence of next-generation sequencing techniques, rapidly accumulating deep bisulfite sequencing data allow the securitization of DNA methylation patterns on genome-wide scale. However, existing DNA methylation analysis tools mainly focus on the bisulfite sequencing data mapping and the comparison at DNA methylation level. No software has been developed to assess DNA methylation variations embedded in bisulfite sequencing data.
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(Tsai et al., 2012) Heterogeneity and randomness of DNA methylation patterns in human embryonic stem cells. DNA Cell Biol.
(Xie et al., 2011) Genome-wide quantitative assessment of variation in DNA methylation patterns. Nucleic Acids Res.
(He et al., 2013) DMEAS: DNA methylation entropy analysis software. Bioinformatics.