Agent skill

bio-long-read-sequencing-nanopore-methylation

Calls DNA methylation from Oxford Nanopore sequencing data using signal-level analysis. Use when detecting 5mC or 6mA modifications directly from nanopore reads without bisulfite conversion.

View SKILL.md on GitHub Repository
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Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/data/nanopore-methylation

SKILL.md

Nanopore Methylation Calling

Modern Workflow (modkit)

ONT's modkit is the recommended tool for methylation analysis from basecalled data.

Extract Methylation from BAM

bash
# Assumes BAM has MM/ML tags from dorado basecalling
modkit pileup input.bam methylation.bed \
    --ref reference.fa \
    --cpg \
    --combine-strands

Output Format

# bedMethyl format
chr1  1000  1001  .  10  +  1000  1001  0,0,0  10  80.5
# Columns: chrom, start, end, name, score, strand, thickStart, thickEnd,
#          itemRgb, coverage, percent_modified

Basecalling with Methylation

bash
# Dorado basecalling with 5mC model
dorado basecaller dna_r10.4.1_e8.2_400bps_sup@v4.2.0 \
    pod5_dir/ \
    --modified-bases 5mCG \
    > calls.bam

# Index and align
samtools fastq calls.bam | \
    minimap2 -ax map-ont -y reference.fa - | \
    samtools sort -o aligned.bam
samtools index aligned.bam

Region-Specific Analysis

bash
# CpG islands only
modkit pileup aligned.bam cpg_islands.bed \
    --ref reference.fa \
    --cpg \
    --include-bed cpg_islands.bed

# Promoter regions
modkit pileup aligned.bam promoters.bed \
    --ref reference.fa \
    --cpg \
    --include-bed promoters.bed

Sample Summary

bash
# Get modification summary statistics
modkit summary aligned.bam

# Output includes:
# - Total reads with modifications
# - Modification types detected
# - Fraction modified per type

Differential Methylation

bash
# Create BED files for each sample
modkit pileup sample1.bam sample1.bed --ref ref.fa --cpg
modkit pileup sample2.bam sample2.bed --ref ref.fa --cpg

# Compare with methylKit or DSS in R

Quality Considerations

  • Minimum coverage: 10x for reliable calls
  • Modified base probability threshold: 0.5 default, adjust as needed
  • Combine strands for CpG (symmetric methylation)

Related Skills

  • long-read-sequencing/basecalling - Dorado basecalling
  • methylation-analysis/methylation-calling - General methylation concepts
  • methylation-analysis/dmr-detection - Differential methylation

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