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 PKU-YuanGroup/OpenAI4S --skill bio-atac-seq-consensus-peaksetgit clone --depth 1 https://github.com/PKU-YuanGroup/OpenAI4SWrote 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/pku-yuangroup/openai4s/bio-atac-seq-consensus-peakset)<a href="https://agentmods.dev/skills/pku-yuangroup/openai4s/bio-atac-seq-consensus-peakset"><img src="https://agentmods.dev/badge/skills/pku-yuangroup/openai4s/bio-atac-seq-consensus-peakset/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/pku-yuangroup/openai4s/bio-atac-seq-consensus-peakset"><img src="https://agentmods.dev/badge/skills/pku-yuangroup/openai4s/bio-atac-seq-consensus-peakset.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 | $0.00097 | $0.05039 |
| Opus 5 | $0.00048 | $0.02520 |
| Sonnet 5 | $0.00019 | $0.01008 |
| Haiku 4.5 | $0.00010 | $0.00504 |
Grade A, and why
bio-atac-seq-consensus-peakset 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 11d 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.
This is a copy
98% identical to bio-atac-seq-consensus-peakset — 12 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 350 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Version Compatibility
Reference examples tested with: bedtools 2.31+, samtools 1.19+, BEDOPS 2.4.41+, GenomicRanges 1.54+, DiffBind 3.12+, Subread 2.0.2+ (featureCounts; --countReadPairs requires >= 2.0.2), pybedtools 0.10+.
Before using code patterns, verify installed versions match. If versions differ:
- Python:
pip show <package>thenhelp(module.function)to check signatures - R:
packageVersion('<pkg>')then?function_nameto verify parameters - CLI:
<tool> --versionthen<tool> --helpto confirm flags
If code throws unexpected errors, introspect the installed package and adapt rather than retrying.
Consensus Peakset Construction
"Build a single peakset to count reads against for all my samples" -> Combine per-replicate or per-condition peak calls into a non-redundant, fixed-width set of regions. The strategy chosen drives FDR calibration, peak-width fairness, and reproducibility downstream.
- CLI:
bedtools merge(simple union) andbedtools multiinter(per-sample membership columns emitted by default) - CLI: Corces 2018 iterative overlap removal (custom shell)
- R:
DiffBind::dba.count(summits=250)(built-in fixed-width) - Python:
pybedtoolsfor programmatic merging
The peakset choice is rarely default-correct. Wrong width or wrong overlap rule propagates to every downstream analysis (differential, motif, footprint, ML).
Why a Consensus Peakset Matters
ATAC peaks vary in width across replicates: same regulatory element might be called 200 bp in rep1 and 800 bp in rep2 because of stochastic Tn5 cuts at edges. Counting reads in different-width intervals confounds peak width with biological signal. A fixed-width consensus avoids this.
For ENCODE-style differential analysis: ALL samples must be counted against the SAME peak coordinates; otherwise the count matrix is non-rectangular and statistical models are misspecified.
Strategy Taxonomy
| Strategy | Implementation | Width | When to use | Fails when |
|---|---|---|---|---|
| Naive union | bedtools merge of all peaks |
Variable, tends wide | Quick exploratory; never for differential | Width inflation drives spurious differential |
| Naive intersection | bedtools multiinter requiring all samples |
Variable | High-stringency reproducibility | Loses real condition-specific peaks |
| Majority-rule overlap | multiinter requiring >= n/2 samples |
Variable | Balance; DiffBind default with minOverlap |
Width still varies; counts are width-biased |
| Iterative overlap removal (Corces 2018) | Sort by significance, greedily keep non-overlapping at fixed width | 501 bp fixed | ML features; cross-study comparison; modern ATAC standard | Loses sub-501bp resolution; overweights high-significance peaks |
| Summit-centered fixed width (DiffBind) | dba.count(summits=250) re-centers all peaks on summit +/- 250 bp |
501 bp fixed | Matches the Corces 501 bp convention (note: dba.count default is summits=200 -> 401 bp); integrates with replicate counts |
Requires summit info (MACS narrowPeak); broad peaks lose width info |
| IDR-filtered union | Union of IDR-passed peaks across rep pairs | Variable | ENCODE pipeline-compliant; reproducibility-aware | Requires running IDR per pair; computationally heavier |
| Per-condition union, then global union | Each group consensus separately, then merge | Variable | Different cell types / strong condition shift | Same width issues as naive union |
| Width-controlled extension | Extend each peak to median width centered on midpoint | User-set | Quick fixed-width without summit info | Midpoint != summit; can shift biology |
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.
- 11d ago First seen · 350 lines · 97 tokens per session scan A 8d529fbc133e
bio-atac-seq-consensus-peakset is a skill published in the GitHub repository PKU-YuanGroup/OpenAI4S (403 stars, last pushed today), licensed MIT. It adds 97 tokens to every session and 5,039 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 98% identical to bio-atac-seq-consensus-peakset, differing in 12 lines, and is treated as a copy.
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