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bio-copy-number-germline-cnv-interpretation

Classify constitutional (germline) copy number variants for clinical reporting using the 2019 ACMG/ClinGen technical standards points-based framework, with ClassifyCNV and AnnotSV for semi-automated scoring. Covers the separate copy-number-loss and copy-number-gain rubrics, the five-tier classification, ClinGen haploinsufficiency/triplosensitivity and dosage-sensitive regions, de novo and segregation evidence, and population-frequency benign evidence. Use when assigning pathogenic/likely-pathogenic/VUS/likely-benign/benign to a constitutional CNV, scoring a CNV against ACMG/ClinGen criteria, o

BioTender-maxgithub.com/BioTender-maxGitHub ↗
claude-codeships scriptsNOASSERTION
Install
npx skills add BioTender-max/awesome-bio-agent-skills --skill germline-cnv-interpretation --agent claude-code

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

Facts
Files in the skill folder: 3
SKILL.md size: 12 KB
Bundled scripts: yes
Path: skills/bioskills/germline-cnv-interpretation/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: ClassifyCNV 1.1+, AnnotSV 3.4+, Python 3.10+ with pandas 2.2+; bedtools 2.31+. Before using code patterns, verify installed versions match. If versions differ: - CLI: `python ClassifyCNV.py --help`, `AnnotSV --version` - Update the bundled ClinGen/dosage databases — ClassifyCNV ships an `update_clingen.sh`; dosage curation changes, and a stale database silently mis-scores. This skill is for **constitutional/germline** CNVs only. Somatic tumor CNVs use a different framework (AMP/ASCO/CAP and OncoKB tiers) — do not apply ACMG/ClinGen constitutional scoring to a tumor. # Germline CNV Interpretation **"Is this constitutional CNV pathogenic"** -> Apply the 2019 ACMG/ClinGen technical standards: a semiquantitative, points-based rubric that sums evidence into one of five clinical categories. There are two separate rubrics — one for copy-number **loss**, one for copy-number **gain** — because the evidence for deletion and duplication pathogenicity is different. The total score maps to a five-tier classification. - CLI: `ClassifyCNV` (automates the observed-evidence sections), `AnnotSV` (ACMG-aligned rank) - Manual: case-specific evid

What's inside
Steps it walks through
  1. Version Compatibility
  2. The Points Framework
  3. Classification Workflow
  4. Semi-Automated Scoring with ClassifyCNV
  5. Comprehensive Annotation Cross-Check with AnnotSV
  6. Failure Modes
  7. Applying constitutional scoring to a somatic CNV
  8. Treating a tool's VUS as a final answer
  9. Stale ClinGen dosage database
  10. Genome-build mismatch
  11. Partial-gene overlap scored as whole-gene loss
  12. Reconciliation
  13. Quantitative Thresholds
  14. Common Errors
Ships with 2 files
  • examples/classify_germline_cnv.py
  • usage-guide.md
Commands it runs
Input BED: chrom, start, end, type  (type = DEL or DUP)
python ClassifyCNV.py \
Output Scoresheet.txt: per-CNV total score, classification, and per-criterion points.
AnnotSV -SVinputFile constitutional_cnvs.vcf -genomeBuild GRCh38 \
AnnotSV emits an ACMG-aligned rank (1 benign - 5 pathogenic) per SV; use it to
cross-check ClassifyCNV, not as a standalone clinical classification.
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About this skill
What does the bio-copy-number-germline-cnv-interpretation skill do?

Classify constitutional (germline) copy number variants for clinical reporting using the 2019 ACMG/ClinGen technical standards points-based framework, with ClassifyCNV and AnnotSV for semi-automated scoring. Covers the separate copy-number-loss and copy-number-gain rubrics, the five-tier classification, ClinGen haploinsufficiency/triplosensitivity and dosage-sensitive regions, de novo and segregation evidence, and population-frequency benign evidence. Use when assigning pathogenic/likely-pathogenic/VUS/likely-benign/benign to a constitutional CNV, scoring a CNV against ACMG/ClinGen criteria, o

How do I install it?

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