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-chip-seq-super-enhancersgit 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-chip-seq-super-enhancers)<a href="https://agentmods.dev/skills/pku-yuangroup/openai4s/bio-chip-seq-super-enhancers"><img src="https://agentmods.dev/badge/skills/pku-yuangroup/openai4s/bio-chip-seq-super-enhancers/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-chip-seq-super-enhancers"><img src="https://agentmods.dev/badge/skills/pku-yuangroup/openai4s/bio-chip-seq-super-enhancers.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 | $0.00146 | $0.04435 |
| Opus 5 | $0.00073 | $0.02218 |
| Sonnet 5 | $0.00029 | $0.00887 |
| Haiku 4.5 | $0.00015 | $0.00443 |
Grade A, and why
bio-chipseq-super-enhancers scanned grade A with 1 finding 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 9d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
wget https://downloads.wenglab.org/Registry-V4/GRCh38-cCREs.bed This is a copy
97% identical to bio-chipseq-super-enhancers — 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 — 272 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Version Compatibility
Reference examples tested with: ROSE (stjude/ROSE, 2018+), ROSE2 (linlabbcm/rose2, 2021+), LILY (BoevaLab/LILY, 2020+), HOMER 4.11+, samtools 1.19+, bedtools 2.31+, GenomicRanges 1.54+.
The original Young-lab ROSE is Python 2; ROSE2 (linlabbcm/rose2) and the stjude/ROSE fork are the Python-3 implementations with the same algorithm. For hg38 data use stjude/ROSE (python ROSE_main.py, whose genomeDict includes HG38); rose2's released genomeDict covers only HG18/HG19/MM8/MM9/MM10/RN4/RN6, so rose2 -g HG38 fails. LILY (Boeva 2017) is a refactored implementation with input-control background subtraction for low-quality H3K27ac data.
Super-Enhancer Calling
"Identify super-enhancers driving cell identity / cancer biology" -> Stitch nearby active enhancer peaks (H3K27ac, MED1, or BRD4) within a stitching window, exclude proximal-promoter signal, rank by total signal, find the hockey-stick inflection point where signal sharply increases, and classify all stitched regions above the inflection as super-enhancers.
- CLI (stjude/ROSE, Python 3):
python ROSE_main.py -g HG38 -i peaks.gff -r h3k27ac.bam -c input.bam -s 12500 -t 2500 -o rose_out/ - CLI (HOMER):
findPeaks tag_dir/ -style super -i input_tag_dir/ - CLI (LILY): variant with input-control background subtraction
- R (custom hockey-stick): rank enhancers by signal, find tangent-line inflection
The SE concept (Whyte 2013) is a thresholding heuristic on a continuous signal distribution (Pott & Lieb 2015 Nat Genet), not a categorical biological category. Genetic dissection of super-enhancers (Hay 2016; Moorthy 2017) shows constituent elements contribute unequally and many are individually dispensable/redundant; the "SE" label is a useful operational definition for BET-inhibitor responsiveness and cell-identity gene regulation, not an absolute biological property.
Marker Choice: H3K27ac vs MED1 vs BRD4
| Marker | Captures | When to prefer |
|---|---|---|
| H3K27ac | Active regulatory elements broadly | Most widely available; standard for SE definition since Whyte 2013 |
| MED1 | Mediator complex accumulation (the defining biology) | Direct readout of SE; less common antibody; lower signal-to-noise |
| BRD4 | BET cofactor accumulation | Most predictive of BET-inhibitor responsiveness; clinical relevance |
| H3K27ac + MED1 intersection | High-confidence SE | Gold standard if both available |
| dELS from ENCODE cCREs | Cell-type-agnostic distal enhancer registry | Cross-reference; not SE-specific by itself |
What ships with it
3 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.
- 9d ago First seen · 272 lines · 146 tokens per session scan A acf240637c98
bio-chipseq-super-enhancers is a skill published in the GitHub repository PKU-YuanGroup/OpenAI4S (407 stars, last pushed yesterday), licensed MIT. It adds 146 tokens to every session and 4,435 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 97% identical to bio-chipseq-super-enhancers, differing in 12 lines, and is treated as a copy.
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