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 peak-callinggit 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/peak-calling)<a href="https://agentmods.dev/skills/gptomics/bioskills/peak-calling"><img src="https://agentmods.dev/badge/skills/gptomics/bioskills/peak-calling/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/peak-calling"><img src="https://agentmods.dev/badge/skills/gptomics/bioskills/peak-calling.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 | $0.00138 | $0.05558 |
| Opus 5 | $0.00069 | $0.02779 |
| Sonnet 5 | $0.00028 | $0.01112 |
| Haiku 4.5 | $0.00014 | $0.00556 |
Grade A, and why
bio-chipseq-peak-calling 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 6d 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-chipseq-peak-calling — 100% identical, 12 lines differ
How it starts
The opening of the file, as written. The whole thing — 279 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Version Compatibility
Reference examples tested with: MACS3 3.0.4+, MACS2 2.2.9+, HOMER 4.11+, SPP 1.16+, samtools 1.19+, bedtools 2.31+, IDR 2.0.4+.
Before running, verify versions: <tool> --version and <tool> --help to confirm flags. If a flag is missing, check the changelog — MACS2->MACS3 is API-compatible for callpeak but predictd, bdgpeakcall, and hmmratac differ.
ChIP-seq Peak Calling
"Identify protein-DNA binding sites from ChIP-seq alignments" -> Detect statistically enriched genomic regions by comparing IP signal to input control (or genomic background), with peak shape (narrow/broad) determined by target biology (TF vs histone mark).
- CLI (ENCODE TF default):
macs2 callpeak -t chip.bam -c input.bam -f BAM -g hs -n sample --keep-dup all -p 1e-2 - CLI (ENCODE histone default): same with
--broad --broad-cutoff 0.1for H3K27me3, H3K9me3, H3K36me3 - CLI (alternative):
macs3 callpeak ...(API-identical, active development), HOMERfindPeaks tags/ -style histone -i input_tags/, SPP via phantompeakqualtools wrapper
ENCODE TF pipeline still uses SPP for peak ranking + IDR, with MACS2 producing the signal tracks. Histone pipeline uses MACS2 + naive overlap (IDR is too conservative for histone signal dynamic range). MACS3 is the actively maintained successor; MACS2 receives only bug fixes.
Critical Pre-Call Validation
Before any peak calling, three things must be true or the output is unreliable:
- Antibody validated — KO/KD orthogonal control, peptide-array specificity for histone modifications, or vendor-provided CRISPR-validated lot (Epicypher, CST). "ChIP-grade" marketing is not validation. See chipseq-qc.
- Fragment-size distribution is sane — TF ChIP should show sub-nucleosomal (~50-100 bp) enrichment; histone ChIP should show clean mono- (~150) and di-nucleosomal (~300) peaks. Flat distribution = over-sonication; rescue is impossible. Check via
samtools view -f 0x2 sample.bam | awk '{print $9}' | sort | uniq -c. - Input control matches — Sonicated input is biased toward open chromatin; MNase input toward nucleosomes. Input from a different library prep batch or fragmentation method introduces bias that subtraction cannot fix.
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.
- 6d ago First seen · 279 lines · 138 tokens per session scan A 9662768f54fc
bio-chipseq-peak-calling is a skill published in the GitHub repository GPTomics/bioSkills (1,199 stars, last pushed 25d ago), licensed MIT. It adds 138 tokens to every session and 5,558 once invoked, about $0.0007 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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