Agent skill · Data & Analytics

bio-workflows-methylation-pipeline

End-to-end bisulfite sequencing workflow from FASTQ to differentially methylated regions. Covers Bismark alignment, methylation calling, and DMR detection with methylKit. Use when analyzing bisulfite sequencing data.

majiayu000github.com/majiayu000GitHub ↗
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill methylation-pipeline-gptomics-bioskills-2 --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 7 KB
Bundled scripts: none
Path: skills/analysis/methylation-pipeline-gptomics-bioskills-2/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Methylation Pipeline Complete workflow from bisulfite sequencing FASTQ to differentially methylated regions. ## Workflow Overview ``` FASTQ files | v [1. QC & Trimming] -----> fastp/Trim Galore | v [2. Alignment] ---------> Bismark | v [3. Deduplication] -----> deduplicate_bismark | v [4. Methylation Calling] -> bismark_methylation_extractor | v [5. Analysis] -----------> methylKit (R) | v [6. DMR Detection] ------> methylKit/DSS | v Differentially methylated regions ``` ## Primary Path: Bismark + methylKit ### Step 1: Quality Control ```bash # Trim Galore recommended for bisulfite data (handles adapter bias) trim_galore --paired --fastqc \ -o trimmed/ \ sample_R1.fastq.gz sample_R2.fastq.gz # Or fastp with conservative settings fastp -i sample_R1.fastq.gz -I sample_R2.fastq.gz \ -o trimmed/sample_R1.fq.gz -O trimmed/sample_R2.fq.gz \ --detect_adapter_for_pe \ --qualified_quality_phred 20 \ --length_required 35 \ --html qc/sample_fastp.html ``` ### Step 2: Bismark Alignment ```bash # Prepare genome (once) bismark_genome_preparation --bowtie2 genome/ # Align bismark --genome genome/ \ -1 trimmed/sample_R1_val_1.fq.gz \ -2 trimmed/sample_R2_val_2.fq.gz \ -o aligned/ \ --parallel 4

What's inside
Steps it walks through
  1. Workflow Overview
  2. Primary Path: Bismark + methylKit
  3. Step 1: Quality Control
  4. Step 2: Bismark Alignment
  5. Step 3: Deduplication
  6. Step 4: Methylation Calling
  7. Step 5: Analysis with methylKit
  8. Step 6: DMR Detection
  9. Parameter Recommendations
  10. Troubleshooting
  11. Complete Pipeline Script
  12. Related Skills
Ships with 1 file
  • metadata.json
Commands it runs
Trim Galore recommended for bisulfite data (handles adapter bias)
trim_galore --paired --fastqc \
sample_R1.fastq.gz sample_R2.fastq.gz
Or fastp with conservative settings
fastp -i sample_R1.fastq.gz -I sample_R2.fastq.gz \
Prepare genome (once)
bismark_genome_preparation --bowtie2 genome/
Align
bismark --genome genome/ \
deduplicate_bismark \
More from claude-skill-registry
All skills →
About this skill
What does the bio-workflows-methylation-pipeline skill do?

End-to-end bisulfite sequencing workflow from FASTQ to differentially methylated regions. Covers Bismark alignment, methylation calling, and DMR detection with methylKit. Use when analyzing bisulfite sequencing data.

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill methylation-pipeline-gptomics-bioskills-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.

Keep going