Your browser doesn't support javascript.
loading
mHapTk: a comprehensive toolkit for the analysis of DNA methylation haplotypes.
Ding, Yi; Cai, Kangwen; Liu, Leiqin; Zhang, Zhiqiang; Zheng, Xiaoqi; Shi, Jiantao.
Affiliation
  • Ding Y; State 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.
  • Cai K; Department of Mathematics, Shanghai Normal University, Shanghai 200234, China.
  • Liu L; State 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.
  • Zhang Z; State 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.
  • Zheng X; Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
  • Shi J; State 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.
Bioinformatics ; 38(22): 5141-5143, 2022 11 15.
Article in En | MEDLINE | ID: mdl-36179079
ABSTRACT

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.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: DNA Methylation / High-Throughput Nucleotide Sequencing Language: En Journal: Bioinformatics Journal subject: INFORMATICA MEDICA Year: 2022 Document type: Article Affiliation country: China

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: DNA Methylation / High-Throughput Nucleotide Sequencing Language: En Journal: Bioinformatics Journal subject: INFORMATICA MEDICA Year: 2022 Document type: Article Affiliation country: China