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 de-resultsgit 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/de-results)<a href="https://agentmods.dev/skills/gptomics/bioskills/de-results"><img src="https://agentmods.dev/badge/skills/gptomics/bioskills/de-results/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/de-results"><img src="https://agentmods.dev/badge/skills/gptomics/bioskills/de-results.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 | $0.00169 | $0.06173 |
| Opus 5 | $0.00084 | $0.03086 |
| Sonnet 5 | $0.00034 | $0.01235 |
| Haiku 4.5 | $0.00017 | $0.00617 |
Grade A, and why
bio-differential-expression-de-results 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 8d 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-differential-expression-de-results — 92% identical, 12 lines differ
How it starts
The opening of the file, as written. The whole thing — 376 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Version Compatibility
Reference examples tested with: DESeq2 1.42+, edgeR 4.0+, IHW 1.34+, qvalue 2.34+, ashr 2.2+, AnnotationDbi 1.66+, org.Hs.eg.db 3.18+, biomaRt 2.58+, mygene 1.38+ (Python), dplyr 1.1+, openxlsx 4.2+
Before using code patterns, verify installed versions match. If versions differ:
- R:
packageVersion('<pkg>')then?function_nameto verify parameters - Python:
pip show <package>thenhelp(module.function)to check signatures
If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.
DE Results
"What are my significant genes?" -> Extract DE estimates and p-values from the fitted model, handle missing padj correctly, apply FDR control appropriate to the design, and produce the table or ranked list the downstream tool actually needs.
The Single Most Important Modern Insight -- padj = NA has three distinct meanings
A NA in the padj column is not a missing value; it is a flag indicating which filter excluded the gene. The three causes -- independent filtering, Cook's distance outlier, and all-zero in a group -- have completely different remediations. Dropping all NA rows blindly silently discards real signal, most often from low-count master regulators (transcription factors expressed at ~10 counts) that pass biology but fail the data-driven baseMean threshold.
padj = NA cause |
DESeq2 detection | What it means | Fix if undesired |
|---|---|---|---|
| Independent filtering | finite pvalue, NA padj, baseMean below auto threshold |
Removed before BH adjustment to maximize rejections at alpha |
results(dds, independentFiltering = FALSE) OR filterFun = ihw |
| Cook's distance outlier | NA pvalue, NA padj, baseMean > 0, group has >=3 reps |
One sample has Cook's > qf(0.99, p, m-p) |
results(dds, cooksCutoff = FALSE) |
| All-zero or near-zero in a group | NA pvalue AND baseMean very low |
Insufficient information to test | Filter at preprocess time; or accept |
What ships with it
4 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.
- 8d ago First seen · 376 lines · 169 tokens per session scan A 8b615cc06452
bio-differential-expression-de-results is a skill published in the GitHub repository GPTomics/bioSkills (1,201 stars, last pushed 27d ago), licensed MIT. It adds 169 tokens to every session and 6,173 once invoked, about $0.0008 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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