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freedomintelligence/openclaw-medical-skills/bio-methylation-calling

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PublishedMay 19, 2026 at 12:23 AM

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version: "1.0.1" name: bio-methylation-calling description: Extract methylation calls from Bismark BAM files using bismark_methylation_extractor. Generates per-cytosine reports for CpG, CHG, and CHH contexts. Use when extracting methylation levels from aligned bisulfite sequencing data for downstream analysis. tool_type: cli primary_tool: bismark

Version Compatibility

Reference examples tested with: pandas 2.2+

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

Python: pip show <package> then help(module.function) to check signatures
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.

Methylation Calling

"Extract methylation calls from my Bismark BAM" → Generate per-cytosine methylation reports (CpG, CHG, CHH contexts) from aligned bisulfite sequencing data.

CLI: bismark_methylation_extractor --bedGraph --cytosine_report sample.bam

Basic Extraction

bash

# Extract methylation calls from Bismark BAM
bismark_methylation_extractor --gzip --bedGraph \
    sample_bismark_bt2.bam

Paired-End Extraction

bash

bismark_methylation_extractor --paired-end --gzip --bedGraph \
    sample_bismark_bt2_pe.bam

Common Options

bash

bismark_methylation_extractor \
    --paired-end \                 # For paired-end data
    --gzip \                       # Compress output
    --bedGraph \                   # Generate bedGraph file
    --cytosine_report \            # Genome-wide cytosine report
    --genome_folder /path/to/genome/ \  # Required for cytosine_report
    --buffer_size 10G \            # Memory buffer
    --parallel 4 \                 # Parallel extraction
    -o output_dir/ \
    sample.bam

CpG Context Only

bash

# Most common - extract only CpG methylation
bismark_methylation_extractor \
    --paired-end \
    --no_overlap \                 # Avoid double counting overlapping reads
    --gzip \
    --bedGraph \
    --CX \                         # Also extract CHG/CHH (optional)
    sample.bam

Genome-Wide Cytosine Report

bash

# Comprehensive report with all CpGs in genome
bismark_methylation_extractor \
    --paired-end \
    --gzip \
    --bedGraph \
    --cytosine_report \
    --genome_folder /path/to/genome/ \
    sample.bam

Strand-Specific Output

bash

# Default: strand-specific output
# CpG_OT_sample.txt - Original Top strand
# CpG_OB_sample.txt - Original Bottom strand
# CpG_CTOT_sample.txt - Complementary to OT
# CpG_CTOB_sample.txt - Complementary to OB
 
# Merge strands (CpG methylation is usually symmetric)
bismark_methylation_extractor --merge_non_CpG --gzip sample.bam

Avoid Double-Counting Overlapping Reads

bash

# For paired-end data with overlapping reads
bismark_methylation_extractor \
    --paired-end \
    --no_overlap \                 # Ignore overlapping portion of read 2
    --gzip \
    sample_pe.bam

Generate Coverage File

bash

# bismark2bedGraph creates coverage file
bismark_methylation_extractor --bedGraph --gzip sample.bam
 
# Or run separately
bismark2bedGraph -o sample CpG_context_sample.txt.gz
 
# Coverage format: chr start end methylation_percentage count_meth count_unmeth

Convert to BigWig for Visualization

bash

# bedGraph to BigWig (requires UCSC tools)
bedGraphToBigWig sample.bedGraph.gz chrom.sizes sample.bw

M-Bias Plot

bash

# Check for methylation bias across read positions
bismark_methylation_extractor --paired-end \
    --mbias_only \                 # Only generate M-bias plot
    sample.bam
 
# Generates sample.M-bias.txt and sample.M-bias_R1.png, sample.M-bias_R2.png

Ignore End Bias

bash

# Ignore positions with systematic bias (found from M-bias plot)
bismark_methylation_extractor \
    --paired-end \
    --ignore 2 \                   # Ignore first 2 bp of read 1
    --ignore_r2 2 \                # Ignore first 2 bp of read 2
    --ignore_3prime 2 \            # Ignore last 2 bp of read 1
    --ignore_3prime_r2 2 \         # Ignore last 2 bp of read 2
    sample.bam

Output Files

bash

# Main output files:
# CpG_context_sample.txt.gz      - Per-read CpG methylation
# sample.bismark.cov.gz          - Coverage file
# sample.bedGraph.gz             - bedGraph for visualization
# sample.CpG_report.txt.gz       - Genome-wide CpG report (with --cytosine_report)
 
# Coverage file format:
# chr  start  end  methylation%  count_methylated  count_unmethylated

Parse Output in Python

python

import pandas as pd
cov = pd.read_csv('sample.bismark.cov.gz', sep='\t', header=None,
                   names=['chr', 'start', 'end', 'meth_pct', 'count_meth', 'count_unmeth'])
cov['coverage'] = cov['count_meth'] + cov['count_unmeth']
cov_filtered = cov[cov['coverage'] >= 10]

Key Parameters

Parameter	Description
--paired-end	Paired-end mode
--gzip	Compress output
--bedGraph	Generate bedGraph
--cytosine_report	Full genome cytosine report
--genome_folder	Path to genome (for cytosine_report)
--CX	Report CHG/CHH contexts
--no_overlap	Avoid counting overlapping reads twice
--parallel	Parallel extraction threads
--mbias_only	Only M-bias analysis
--ignore N	Ignore first N bp of read 1
--ignore_r2 N	Ignore first N bp of read 2

Output Formats

Format	Description	Use Case
CpG_context	Per-read methylation calls	Detailed analysis
.bismark.cov	Per-CpG coverage summary	methylKit input
.bedGraph	Methylation track	Genome browser
.CpG_report	All genome CpGs	Comprehensive analysis

Related Skills

bismark-alignment - Generate input BAM files
methylkit-analysis - Import coverage files to R
dmr-detection - Find differentially methylated regions

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