NanoMethViz: An R/Bioconductor package for visualizing long-read methylation data.

Area of Science:

• Genomics
• Bioinformatics
• Molecular Biology

Background:

• Long-read nanopore sequencing offers unique advantages for detecting modified DNA bases, including 5-methylcytosine.
• Existing R/Bioconductor tools lack comprehensive visualization capabilities for nanopore methylation data across diverse experimental groups.

Purpose of the Study:

• To develop an R package, NanoMethViz, for effective visualization and analysis of nanopore sequencing methylation profiles.
• To provide a user-friendly tool for handling large methylation datasets and exploring patterns at multiple resolutions.

Main Methods:

• Developed the NanoMethViz R package compatible with various methylation callers.
• Implemented dimensionality reduction for sample-level methylation profile comparison.
• Enabled visualization of aggregated methylation profiles for genomic features (genes, CpG islands) and individual read-level patterns (spaghetti plots, heatmaps).

Main Results:

• NanoMethViz efficiently handles large nanopore methylation datasets using a compressed format.
• The package facilitates exploration of methylation patterns from sample-level relationships to single-read resolution.
• Seamless integration with existing Bioconductor methylation analysis tools is achieved.

Conclusions:

• NanoMethViz enhances the convenience of handling methylation signals from nanopore sequencing.
• The package expands visualization options for nanopore methylation data, aiding biological interpretation.
• NanoMethViz supports comprehensive analysis of DNA methylation patterns within the R/Bioconductor ecosystem.