Agent skill · Data & Analytics

bio-copy-number-gatk-cnv

Call copy number variants using GATK best practices workflow. Supports both somatic (tumor-normal) and germline CNV detection from WGS or WES data. Use when following GATK best practices or integrating CNV calling with other GATK variant pipelines.

FreedomIntelligencegithub.com/FreedomIntelligenceGitHub ↗
claude-codeships scripts
Install
npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-copy-number-gatk-cnv --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: yes
Path: skills/bio-copy-number-gatk-cnv/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 2,909
Language: Python
Read our review of the source →

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: GATK 4.5+ Before using code patterns, verify installed versions match. If versions differ: - 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. # GATK CNV Workflow **"Call CNVs using GATK best practices"** → Collect read counts, build a panel of normals, denoise tumor coverage, model segments with allelic counts, and call copy ratio states. - CLI: `gatk CollectReadCounts` → `gatk DenoiseReadCounts` → `gatk ModelSegments` → `gatk CallCopyRatioSegments` ## Somatic CNV Workflow Overview ``` 1. PreprocessIntervals → intervals.interval_list 2. CollectReadCounts → sample.counts.hdf5 3. CreateReadCountPanelOfNormals → pon.hdf5 4. DenoiseReadCounts → sample.denoised.tsv 5. CollectAllelicCounts → sample.allelicCounts.tsv 6. ModelSegments → sample.modelFinal.seg 7. CallCopyRatioSegments → sample.called.seg ``` ## Step 1: Preprocess Intervals **Goal:** Prepare genomic intervals for read counting, handling both WES and WGS modes. **Approach:** Use PreprocessIntervals to

What's inside
Steps it walks through
  1. Version Compatibility
  2. Somatic CNV Workflow Overview
  3. Step 1: Preprocess Intervals
  4. Step 2: Collect Read Counts
  5. Step 3: Create Panel of Normals
  6. Step 4: Denoise Read Counts
  7. Step 5: Collect Allelic Counts
  8. Step 6: Model Segments
  9. Step 7: Call Copy Ratio Segments
  10. Plotting
  11. Germline CNV Workflow
  12. Complete Somatic Pipeline Script
  13. Key Output Files
  14. Related Skills
Ships with 2 files
  • examples/run_gatk_cnv.sh
  • usage-guide.md
Commands it runs
For WES/targeted
gatk PreprocessIntervals \
For WGS
For each sample
gatk CollectReadCounts \
Combine multiple normal samples
gatk CreateReadCountPanelOfNormals \
Using panel of normals
gatk DenoiseReadCounts \
From known SNP sites (for LOH detection)
More from OpenClaw-Medical-Skills
All skills →
About this skill
What does the bio-copy-number-gatk-cnv skill do?

Call copy number variants using GATK best practices workflow. Supports both somatic (tumor-normal) and germline CNV detection from WGS or WES data. Use when following GATK best practices or integrating CNV calling with other GATK variant pipelines.

How do I install it?

Run `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-copy-number-gatk-cnv --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 FreedomIntelligence/OpenClaw-Medical-Skills, a repository with 2,909 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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