Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add GPTomics/bioSkills --skill gatk-cnvgit clone --depth 1 https://github.com/GPTomics/bioSkillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/gptomics/bioskills/gatk-cnv)<a href="https://agentmods.dev/skills/gptomics/bioskills/gatk-cnv"><img src="https://agentmods.dev/badge/skills/gptomics/bioskills/gatk-cnv/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/gptomics/bioskills/gatk-cnv"><img src="https://agentmods.dev/badge/skills/gptomics/bioskills/gatk-cnv.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00175 | $0.04002 |
| Opus 5 | $0.00088 | $0.02001 |
| Sonnet 5 | $0.00035 | $0.00800 |
| Haiku 4.5 | $0.00017 | $0.00400 |
Grade A, and why
bio-copy-number-gatk-cnv scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- bio-copy-number-gatk-cnv — 95% identical, 12 lines differ
How it starts
The opening of the file, as written. The whole thing — 227 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Version Compatibility
Reference examples tested with: GATK 4.5+ (gatk4), Python 3.10+ (gcnv conda env), R 4.3+.
Before using code patterns, verify installed versions match. If versions differ:
- CLI:
gatk --versionthengatk <ToolName> --helpto confirm arguments - gCNV requires a working
gatkcondaenv(theano/tensorflow stack) —gatkwill report if the Python environment is missing
GATK 4.5+ gCNV inference defaults are tuned for whole-exome data; whole-genome runs generally need parameter changes. If a tool reports an unrecognized argument, check the help for that exact GATK version rather than retrying.
GATK CNV Workflows
"Call CNVs the GATK way" -> GATK has two separate CNV workflows that share almost no tools. Picking the wrong one is the most common mistake.
- Somatic CNV:
CollectReadCounts->DenoiseReadCounts->ModelSegments->CallCopyRatioSegments. Tumor copy-ratio segments, optionally allele-aware. - Germline gCNV:
DetermineGermlineContigPloidy->GermlineCNVCaller->PostprocessGermlineCNVCalls. Per-sample germline CN genotypes (VCF).
Critical: What GATK Somatic CNV Does NOT Provide
ModelSegments + CallCopyRatioSegments produce copy-ratio segments and a minor-allele fraction per segment, and the "call" is a simple t-test emitting + / - / 0. This is not integer allele-specific copy number, not tumor purity, and not ploidy. Practitioners routinely assume parity with ASCAT/FACETS and there is none. For integer allele-specific CN, purity, ploidy, LOH state, or whole-genome-doubling status, use allele-specific-copy-number (ASCAT, Sequenza, FACETS, or PureCN — PureCN can even reuse the GATK ModelSegments segmentation as input).
Somatic vs Germline — Choosing the Workflow
| Question | Somatic CNV | Germline gCNV |
|---|---|---|
| Input | One tumor (+ optional matched normal) | A cohort of constitutional samples |
| Output | Copy-ratio segments, +/-/0 call, minor-allele fraction | Integer germline CN genotype VCF per sample |
| Normalization | Tangent (projection onto PoN subspace) | PCA batching + Bayesian read-depth model |
| Cohort needed | PoN of normals for denoising | >= ~100 technically matched samples (cohort mode) |
| Use for | Tumor SCNAs, focal amplifications/deletions | Rare/de novo germline CNVs, NDD/Mendelian cohorts |
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago First seen · 227 lines · 175 tokens per session scan A de97437ffd0b
bio-copy-number-gatk-cnv is a skill published in the GitHub repository GPTomics/bioSkills (1,199 stars, last pushed 26d ago), licensed MIT. It adds 175 tokens to every session and 4,002 once invoked, about $0.0009 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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