NanoMethViz

NanoMethViz is a Bioconductor package for visualising and summarising DNA methylation from Oxford Nanopore long-read sequencing.

It supports:

• tabular methylation calls (for example, Modkit, Megalodon, Nanopolish, and f5c)
• modBAM-based methylation calls

Installation

Install from Bioconductor:

if (!requireNamespace("BiocManager", quietly = TRUE)) {
    install.packages("BiocManager")
}
BiocManager::install("NanoMethViz")

Install the Bioconductor devel version:

if (!requireNamespace("BiocManager", quietly = TRUE)) {
    install.packages("BiocManager")
}
BiocManager::install(version = "devel")
BiocManager::install("NanoMethViz")

Quick Start

For tabix-backed methylation data, NanoMethResult needs three inputs:

• methy: path to a bgzip-compressed and tabix-indexed methylation file
• samples: a data.frame with at least a sample column
• exons: a data.frame with exon-level annotation

library(NanoMethViz)

# Example object bundled with the package
nmr <- load_example_nanomethresult()

# Region/gene visualisation
plot_gene(nmr, "Peg3")

# Group-level summaries
plot_agg_genes(nmr)

# Dimension reduction on methylation profiles
bss <- methy_to_bsseq(nmr)
gene_regions <- exons_to_genes(exons(nmr))
lmr <- bsseq_to_log_methy_ratio(bss, gene_regions)
plot_mds(lmr)
plot_pca(lmr)

Typical Workflow

1. Import methylation calls.
2. Convert to tabix format if needed (convert_methy_format(), create_tabix_file(), modbam_to_tabix()).
3. Prepare sample metadata and exon annotation (get_exons_hg38(), get_exons_mm10(), or custom annotation).
4. Build a result object (NanoMethResult() or ModBamResult()).
5. Query and visualise methylation (query_methy(), plot_gene(), plot_region(), plot_agg_genes(), plot_agg_regions(), plot_violin(), plot_region_heatmap()).
6. Export for downstream differential analysis (methy_to_bsseq(), bsseq_to_edger()).

Common Tasks

Choose the right object type:

• Use NanoMethResult for tabix-backed tabular methylation calls.
• Use ModBamResult for modBAM-based workflows.

If you want to...

• plot one gene: use plot_gene(x, gene)
• plot one genomic interval: use plot_region(x, chr, start, end)
• show per-read heatmap in a region: use plot_region_heatmap(x, chr, start, end)
• aggregate over genes/regions: use plot_agg_genes(x) / plot_agg_regions(x, regions)
• get methylation values for a region: use query_methy(x, chr, start, end)
• run dimension reduction: use plot_mds(log_methy_ratio_matrix) / plot_pca(log_methy_ratio_matrix)
• export for differential testing: use methy_to_bsseq(x), then bsseq_to_edger(...)

Core Data Requirements

• Chromosome naming must match across methylation calls and annotation (chr1 vs 1).
• Sample names in methylation data must match samples$sample.
• Exon annotation should include columns: gene_id, chr, strand, start, end, transcript_id, symbol

Key Global Options

• options(NanoMethViz.site_filter = 3L): minimum site coverage used by query/plot functions.
• options(NanoMethViz.highlight_col = "grey50"): default colour for highlighted annotation regions.

Documentation

• User Guide (Bioconductor vignette): https://www.bioconductor.org/packages/release/bioc/vignettes/NanoMethViz/inst/doc/UsersGuide.html
• User Guide (pkgdown site): https://shians.github.io/NanoMethViz/articles/UsersGuide.html
• Function reference index: https://shians.github.io/NanoMethViz/reference/index.html
• Issue tracker: https://github.com/Shians/NanoMethViz/issues

Example Plots

MDS plot

Feature aggregation

Region methylation plot

License

This project is licensed under Apache License, Version 2.0.