differential-methylation
This skill performs differential DNA methylation analysis (DMRs and DMCs) between experimental conditions using WGBS methylation tracks (BED/BedGraph). It standardizes input files into per-sample four-column Metilene tables, constructs a merged methylation matrix, runs Metilene for DMR detection, filters the results, and generates quick visualizations.
npx skills add majiayu000/claude-skill-registry --skill 21-differential-methylation-bisnake2001-chromskills-2 --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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_hi
- Overview
- Inputs & Outputs
- Inputs
- Outputs
- Decision Tree
- Step 1: Standardize BED file
- Step 2: Build the merged methylation matrix (fractions per sample)
- Step 3: Run metilene (DMR mode)
- Step 4: Run metilene (DMC mode)
- Step 5: Filter significant DMRs and export BED
- Step 6: Filter significant DMCs and export BED
- Step 6: Visualization (quick, optional)
- Troubleshooting
sample1.bed # raw methylation BED files, standardize it according to the following steps sample2.bed 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
What does the differential-methylation skill do?
This skill performs differential DNA methylation analysis (DMRs and DMCs) between experimental conditions using WGBS methylation tracks (BED/BedGraph). It standardizes input files into per-sample four-column Metilene tables, constructs a merged methylation matrix, runs Metilene for DMR detection, filters the results, and generates quick visualizations.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill 21-differential-methylation-bisnake2001-chromskills-2 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.