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Updated: Aug 27, 2025
Methodology for Accurate Detection of Mitochondrial DNA Methylation
Published on: May 20, 2018
mHapTk: a comprehensive toolkit for the analysis of DNA methylation haplotypes
Yi Ding1, Kangwen Cai2, Leiqin Liu1
1State Key Laboratory of Molecular Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, Shanghai 200031, China.
Summary:
Bisulfite sequencing remains the gold standard technique to detect DNA methylation profiles at single-nucleotide resolution. The DNA methylation status of CpG sites on the same fragment represents a discrete methylation haplotype (mHap). The mHap-level metrics were demonstrated to be promising cancer biomarkers and explain more gene expression variation than average methylation. However, most existing tools focus on average methylation and neglect mHap patterns. Here, we present mHapTk, a comprehensive python toolkit for the analysis of DNA mHap. It calculates eight mHap-level summary statistics in predefined regions or across individual CpG in a genome-wide manner. It identifies methylation haplotype blocks, in which methylations of pairwise CpGs are tightly correlated. Furthermore, mHap patterns can be visualized with the built-in functions in mHapTk or external tools such as IGV and deepTools.
Availability And Implementation:
https://jiantaoshi.github.io/mhaptk/index.html.
Supplementary Information:
Supplementary data are available at Bioinformatics online.
