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 agentmods add skills/tiangzlab/omicsclaw/chip-atlas-diff-analysisnpx skills add TianGzlab/OmicsClaw --skill chip-atlas-diff-analysisgit clone --depth 1 https://github.com/TianGzlab/OmicsClawWrote 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/tiangzlab/omicsclaw/chip-atlas-diff-analysis)<a href="https://agentmods.dev/skills/tiangzlab/omicsclaw/chip-atlas-diff-analysis"><img src="https://agentmods.dev/badge/skills/tiangzlab/omicsclaw/chip-atlas-diff-analysis.svg" alt="Measured on agentmods" 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 | $0.00006 | $0.04203 |
| Opus 5 | $0.00003 | $0.02101 |
| Sonnet 5 | $0.00001 | $0.00841 |
| Haiku 4.5 | $0.00001 | $0.00420 |
Grade A, and why
ChIP-Atlas Diff Analysis 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 5d 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:
- chip-atlas-diff-analysis — 92% identical, 610 lines differ
How it starts
The opening of the file, as written. The whole thing — 228 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ChIP-Atlas Diff Analysis
Compare two groups of experiments to identify differential peak regions (DPR) or differentially methylated regions (DMR) using the ChIP-Atlas Diff Analysis API.
When to Use This Skill
Use ChIP-Atlas diff analysis when you need to:
- Find differential peaks between two conditions (treated vs control, tissue A vs B)
- Identify differentially methylated regions between sample groups (Bisulfite-seq)
- Compare chromatin accessibility between cell types using ATAC-seq/DNase-seq data
- Leverage edgeR-based statistical framework on ChIP-Atlas public experiment data
- Avoid raw data downloads — works directly with experiment accession IDs
Don't use for:
- Single experiment analysis or peak calling (use MACS2/MACS3 workflows)
- Enrichment of factors near a gene list (use chip-atlas-peak-enrichment)
- Offline analysis (requires internet for API calls)
Key Concept: Submits two groups of experiment IDs to ChIP-Atlas. Server performs edgeR differential analysis (for DPR) or metilene (for DMR), returning BED files with genomic coordinates, logFC, p-values, q-values (FDR), and per-experiment normalized counts.
Installation
| Software | Version | License | Commercial Use | Installation |
|---|---|---|---|---|
| pandas | >=1.3 | BSD-3-Clause | Permitted | pip install pandas |
| requests | >=2.25 | Apache-2.0 | Permitted | pip install requests |
| numpy | >=1.20 | BSD-3-Clause | Permitted | pip install numpy |
| plotnine | >=0.10 | MIT | Permitted | pip install plotnine |
| plotnine-prism | >=0.2 | MIT | Permitted | pip install plotnine-prism |
pip install pandas requests numpy plotnine plotnine-prism
System requirements: Internet connection (API calls to ChIP-Atlas)
Inputs
Experiment IDs (two groups, minimum 2 per group):
- SRA accessions: SRX, ERX, DRX (e.g., SRX18419259)
- GEO accessions: GSM (e.g., GSM6765200)
- Formats: Python list, plain text (one per line), CSV with ID column
What ships with it
14 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.
- references/chipatlas_diff_api_format.md 3.1 KB
- references/diff_analysis_methods.md 3.1 KB
- references/output_format.md 3.0 KB
- scripts/__init__.py 44 B runs code
- scripts/annotate_genes.py 4.2 KB runs code
- scripts/export_all.py 23 KB runs code
- scripts/filter_regions.py 5.7 KB runs code
- scripts/generate_all_plots.py 10 KB runs code
- scripts/load_example_data.py 6.0 KB runs code
- scripts/load_user_data.py 6.6 KB runs code
- scripts/parse_bed_results.py 7.8 KB runs code
- scripts/qc_checks.py 23 KB runs code
- scripts/query_chipatlas_api.py 10 KB runs code
- scripts/run_diff_workflow.py 8.7 KB runs code
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.
- 5d ago First seen · 228 lines · 6 tokens per session scan A 374c3c6c4b66
ChIP-Atlas Diff Analysis is a skill published in the GitHub repository TianGzlab/OmicsClaw (160 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 6 tokens to every session and 4,203 once invoked, about $0.0000 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 2026-08-30.
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