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Updated: Jun 19, 2026

DNA Methylation: Bisulphite Modification and Analysis

DNA Methylation: Bisulphite Modification and Analysis

Published on: October 21, 2011

Computational analysis of DNA methylation from long-read sequencing.

Yilei Fu¹, Winston Timp², Fritz J Sedlazeck^3,4,5

¹Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA.

Nature Reviews. Genetics

|March 29, 2025

Summary

This review covers computational methods for analyzing DNA methylation using long-read sequencing. It explores tools for calling methylation, comparing samples, and understanding its role in gene regulation and disease.

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Targeted DNA Methylation Analysis by Next-generation Sequencing

Targeted DNA Methylation Analysis by Next-generation Sequencing

Published on: February 24, 2015

Area of Science:

Epigenetics
Genomics
Computational Biology

Background:

DNA methylation is a key epigenetic mechanism influencing gene regulation, development, aging, and diseases like cancer.
Single-molecule long-read sequencing enables simultaneous measurement of DNA methylation and genomic variation.
Advancements in long-read data analysis are crucial for understanding methylation's role in chromatin structure and gene regulation.

Purpose of the Study:

To review computational methods for DNA methylation analysis using long-read sequencing.
To discuss tools for methylation calling, sample comparison, and cell-type diversity analysis.
To explore challenges and future directions in DNA methylation research tool development.

Main Methods:

Review of existing computational methods for DNA methylation analysis.
Focus on techniques applicable to single-molecule long-read sequencing data.
Discussion of algorithms for signal calling, differential analysis, and integration with genomic variation.

Main Results:

Identification and categorization of computational tools for DNA methylation analysis.
Comparison of methods based on their application to long-read sequencing data.
Highlighting the utility of these methods in understanding gene regulation and disease.

Conclusions:

Computational methods are essential for interpreting DNA methylation data from long-read sequencing.
Further development of advanced tools is needed to address current challenges.
Future research should focus on integrating methylation analysis with other genomic insights for a comprehensive understanding.