Agent skill · Data & Analytics

bio-workflows-cnv-pipeline

End-to-end copy number variant detection workflow from BAM files. Covers CNVkit analysis for exome/targeted sequencing with visualization and annotation. Use when detecting copy number alterations from sequencing data.

BioTender-maxgithub.com/BioTender-maxGitHub ↗
claude-codeships scriptsNOASSERTION
Install
npx skills add BioTender-max/awesome-bio-agent-skills --skill cnv-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: 9 KB
Bundled scripts: yes
Path: skills/bioskills/cnv-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: CNVkit 0.9+, 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. # CNV Pipeline **"Detect copy number variants from my sequencing data"** → Orchestrate CNVkit coverage analysis, segmentation, calling, visualization, and annotation for exome or targeted sequencing panels. Complete workflow for detecting copy number variants from exome or targeted sequencing data. ## Workflow Overview ``` BAM files (tumor/normal or germline) | v [1. Target Preparation] --> Create/access target BED | v [2. Coverage Calculation] --> Read depth per target | v [3. Reference Creation] --> Pool of normals | v [4. CNV Calling] --------> Log2 ratios, segmentation | v [5. Visualization] ------> Scatter plots, heatmaps | v [6. Annotation] ---------> Gene-level CNVs | v CNV calls with gene annotations ``` ## Primary Path: CNVkit ### Step 1: Prepare Target Regions ```bash # If using exome capture ki

What's inside
Steps it walks through
  1. Version Compatibility
  2. Workflow Overview
  3. Primary Path: CNVkit
  4. Step 1: Prepare Target Regions
  5. Step 2: Calculate Coverage
  6. Step 3: Create Reference (Pool of Normals)
  7. Step 4: Call CNVs
  8. Step 5: Visualization
  9. Step 6: Export and Annotation
  10. Batch Processing Script
  11. Germline CNV Calling
  12. Parameter Recommendations
  13. Troubleshooting
  14. Complete Pipeline Script
Ships with 2 files
  • examples/cnvkit_workflow.sh
  • usage-guide.md
Commands it runs
If using exome capture kit BED
cnvkit.py target capture_targets.bed \
Access regions (off-target for WGS-like sensitivity)
cnvkit.py access genome.fa \
cnvkit.py antitarget targets.bed \
For each sample
for bam in *.bam; do
cnvkit.py coverage $bam targets.bed \
cnvkit.py coverage $bam antitargets.bed \
done
More from awesome-bio-agent-skills
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About this skill
What does the bio-workflows-cnv-pipeline skill do?

End-to-end copy number variant detection workflow from BAM files. Covers CNVkit analysis for exome/targeted sequencing with visualization and annotation. Use when detecting copy number alterations from sequencing data.

How do I install it?

Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill cnv-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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