Related Experiment Video
Updated: Mar 25, 2026
12:34
DNA Methylation: Bisulphite Modification and Analysis
Published on: October 21, 2011
106.7K
MethPat: a tool for the analysis and visualisation of complex methylation patterns obtained by massively parallel
Nicholas C Wong1,2,3,4, Bernard J Pope5,6, Ida L Candiloro7
1Translational Genomics and Epigenomics Laboratory, Olivia Newton-John Cancer Research Institute, Heidelberg, Victoria, 3084, Australia. nwon@unimelb.edu.au.
BMC Bioinformatics
|February 26, 2016
Summary
We developed Methpat, a software tool to visualize clonal DNA methylation patterns from sequencing data. Methpat accurately represents epiallelic diversity, overcoming limitations of average methylation values.
Area of Science:
- Epigenetics
- Genomics
- Bioinformatics
Background:
- DNA methylation regulates gene transcription, with complex, cell-type-specific patterns at gene promoters.
- Averaging methylation data obscures true allelic patterns, necessitating clonal analysis for accurate characterization.
- Deep sequencing offers detailed insights into clonal DNA methylation patterns and heterogeneity.
Purpose of the Study:
- To develop a novel analysis and visualization tool for clonal DNA methylation patterns.
- To accurately represent and interpret the heterogeneity of DNA methylation across different samples.
Main Methods:
- Developed 'Methpat', a software tool for extracting and displaying clonal DNA methylation patterns.
- Utilized Bismark for alignment of massively parallel sequencing data.
- Applied Methpat to analyze multiplex bisulfite amplicon sequencing data.
Main Results:
- Methpat successfully extracted and displayed clonal DNA methylation patterns from various human cell lines and tissues.
- The tool represented the clonal diversity of epialleles at specific gene promoter regions.
- Methpat was also used to describe epiallelic DNA methylation within the mitochondrial genome.
Conclusions:
- Methpat provides a compact and interpretable summary of epiallelic DNA methylation from sequencing data.
- The software effectively visualizes the diversity of epiallelic DNA methylation patterns, outperforming existing tools.
