OpenClaw-Medical-Skills 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.

install

source · Clone the upstream repo

git clone https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/bio-long-read-sequencing-nanopore-methylation" ~/.claude/skills/freedomintelligence-openclaw-medical-skills-bio-long-read-sequencing-nanopore-me && rm -rf "$T"

OpenClaw · Install into ~/.openclaw/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills "$T" && mkdir -p ~/.openclaw/skills && cp -r "$T/skills/bio-long-read-sequencing-nanopore-methylation" ~/.openclaw/skills/freedomintelligence-openclaw-medical-skills-bio-long-read-sequencing-nanopore-me && rm -rf "$T"

manifest: skills/bio-long-read-sequencing-nanopore-methylation/SKILL.md

Version Compatibility

Reference examples tested with: methylKit 1.28+, minimap2 2.26+, samtools 1.19+

Before using code patterns, verify installed versions match. If versions differ:

CLI:
```
<tool> --version
```
then
```
<tool> --help
```
to confirm flags

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.

Nanopore Methylation Calling

"Call methylation from my Nanopore reads" → Extract 5mC/6mA modification probabilities from basecalled reads and summarize per-site methylation frequencies.

CLI:

modkit pileup aligned.bam methylation.bed --ref ref.fa

Modern Workflow (modkit)

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

Extract Methylation from BAM

# 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

# 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

# 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

# Get modification summary statistics
modkit summary aligned.bam

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

Differential Methylation

# 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