mHapTk: a comprehensive toolkit for the analysis of DNA methylation haplotypes

• Published in: Bioinformatics (Oxford, England) Vol. 38; no. 22; pp. 5141 - 5143
• Main Authors: Ding, Yi, Cai, Kangwen, Liu, Leiqin, Zhang, Zhiqiang, Zheng, Xiaoqi, Shi, Jiantao
• Format: Journal Article
• Language: English
• Published: England 15.11.2022
• Subjects: CpG Islands; DNA Methylation; Haplotypes; High-Throughput Nucleotide Sequencing - methods; Sequence Analysis, DNA - methods; Software
• ISSN: 1367-4803; 1367-4811
• DOI: 10.1093/bioinformatics/btac650

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. https://jiantaoshi.github.io/mhaptk/index.html. Supplementary data are available at Bioinformatics online.