WGBS Differential Methylation with metilene
Overview
- •Refer to the Inputs & Outputs section to check available inputs and design the output structure.
- •Always prompt user for which columns in the BED files are methylation fraction/percent. Never decide by yourself.
- •Convert heterogeneous inputs to a per‑sample 4‑column Metilene table (chrom, start, end, methylation_fraction). Sort the BED files after conversion.
- •Generate the merged bed file as the input of metilene.
- •Run metilene: call DMRs and DMCs with tunable parameters
- •Visualize: quick plots (Δmethylation vs –log10(q), length histograms).
Inputs & Outputs
Inputs
bash
sample1.bed # raw methylation BED files, standardize it according to the following steps sample2.bed
Assumptions: All samples share the same reference genome build and chromosome naming scheme.
Outputs
bash
DMR_DMC_detection/
stats/
dmr_results.txt # raw metilene output.
dmc_results.txt
significant_dmrs.txt # filtered significant DMRs (TSV).
significant_dmrs.bed # BED for genome browser.
significant_dmcs.txt
significant_dmcs.bed
dmr_summary.txt # counts and length statistics.
plots/
volcano.pdf
length_hist.pdf
temp/
sample1.sorted.bed
... # other sorted BED files
merged_input.bed
Decision Tree
Step 1: Standardize BED file
- •extract information from input BED files into per‑sample 4‑column Metilene table and sort
bash
for sample in samples;do
awk -F'\t' 'BEGIN {OFS="\t"} {print $1, $2, $3, $<n>/100}' sample.bed | sort -V -k1,1 -k2,2n # n is provide by user, devided by 100 if is percentage
done
Step 2: Build the merged methylation matrix (fractions per sample)
Call:
- •
mcp__methyl-tools__generate_metilene_input
with:
- •
group1_files: Comma-separated group 1 bedGraph/BED files (from Step 1, must be sorted) - •
group1_files: Comma-separated group 2 bedGraph/BED files (from Step 1, must be sorted) - •
output_path: Output file path for generated metilene input - •
group1_name: Identifier of group 1 - •
group2_name: Identifier of group 2
This tool will:
- •Generate a input file for metilene
Step 3: Run metilene (DMR mode)
Call:
- •
mcp__methyl-tools__run_metilene
with:
- •
merged_bed_path: file path for metilene input - •
group_a_name: name of group A (e.g."case") - •
group_b_name: name of group B (e.g."control") - •
mode: Mode for metilene CLI (e.g. 1: de-novo, 2: pre-defined regions, 3: DMCs), assign 1 for DMR analysis - •
threads: Always use 1 threads to avoid error - •
output_results_path: Output path for the DMR results
Step 4: Run metilene (DMC mode)
Call:
- •
mcp__methyl-tools__run_metilene
with:
- •
merged_bed_path: file path for metilene input - •
group_a_name: name of group A (e.g."case") - •
group_b_name: name of group B (e.g."control") - •
mode: Mode for metilene CLI (e.g. 1: de-novo, 2: pre-defined regions, 3: DMCs), assign 3 for DMR analysis - •
output_results_path: Output path for the DMC results
Step 5: Filter significant DMRs and export BED
Call:
- •
mcp__methyl-tools__filter_dmrswith: - •
metilene_results_path: DMR results from Step 3 - •
significant_tsv_path: Output path for the DMR results (e.g. significant_dmrs.tsv) - •
significant_bed_path: Output path for the DMR results (e.g. significant_dmrs.bed) - •
q_threshold,delta_thresholdas agreed.
Step 6: Filter significant DMCs and export BED
Call:
- •
mcp__methyl-tools__filter_dmrswith: - •
metilene_results_path: DMC results from Step 4 - •
significant_tsv_path: Output path for the DMC results (e.g. significant_dmcs.tsv) - •
significant_bed_path: Output path for the DMC results (e.g. significant_dmcs.bed) - •
q_threshold,delta_thresholdas agreed.
Step 6: Visualization (quick, optional)
Volcano-like plot (Δmethylation vs –log10(q))
- •Call:
- •
mcp__methyl-tools__plot_dmr_volcanowith: - •
metilene_results_path: DMR results from Step 3 - •
output_pdf_path - •
q_threshold,delta_thresholdas agreed. - •Optional tuning of
point_size,alphaas needed.
DMR length histogram Call:
- •
mcp__methyl-tools__plot_dmr_length_hist
with:
- •
significant_bed_path: Path for the signimicant DMRs (BED format from Step 5) - •
output_pdf_path
Troubleshooting
- •Chromosome naming mismatches: standardize to a single scheme (
chr1vs1) across all samples.