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.

BioTender-maxgithub.com/BioTender-maxGitHub ↗
claude-codeNOASSERTION
Install
npx skills add BioTender-max/awesome-bio-agent-skills --skill methylation-pipeline --agent claude-code

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

Facts
Files in the skill folder: 3
SKILL.md size: 8 KB
Bundled scripts: none
Path: skills/bioskills/methylation-pipeline/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 135
Language: Python

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

From the SKILL.md

## Version Compatibility Reference examples tested with: Bismark 0.24+, Bowtie2 2.5.3+, FastQC 0.12+, Trim Galore 0.6.10+, fastp 0.23+, methylKit 1.28+ Before using code patterns, verify installed versions match. If versions differ: - R: `packageVersion('<pkg>')` then `?function_name` to verify parameters - 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 Pipeline **"Analyze my bisulfite sequencing data from FASTQ to DMRs"** → Orchestrate Bismark alignment, methylation calling, methylKit analysis, DMR detection, annotation with genomic features, and visualization of methylation patterns. 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. Per-CpG Analysis] ---> methylKit (R) or scipy (Python) | v [6. DMR Detection] ------> me

What's inside
Steps it walks through
  1. Version Compatibility
  2. Workflow Overview
  3. Primary Path: Bismark + methylKit
  4. Step 1: Quality Control
  5. Step 2: Bismark Alignment
  6. Step 3: Deduplication
  7. Step 4: Methylation Calling
  8. Step 5: Analysis with methylKit
  9. Step 5b: Python Alternative for Per-CpG Testing
  10. Step 6: DMR Detection
  11. Parameter Recommendations
  12. Troubleshooting
  13. Complete Pipeline Script
  14. Related Skills
Ships with 2 files
  • examples/methylkit_analysis.R
  • usage-guide.md
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 \
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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 BioTender-max/awesome-bio-agent-skills --skill methylation-pipeline --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 BioTender-max/awesome-bio-agent-skills, a repository with 135 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.

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