Arboreto
Infer gene regulatory networks from expression data with GRNBoost2/GENIE3, scaled via Dask.
Test report
- Verdict
- Tested · Works
- Score
- Tested
- Jul 14, 2026
- Environment
- Claude Code 2.x (agent harness)
- Upstream re-checked
- Aug 10, 2026 · b837e2d
The Quick Start marks the `if __name__ == '__main__':` Dask guard as 'Critical' and repeats it in Troubleshooting; a baseline script assembled from general arboreto knowledge dropped that guard, which is a genuine hang/crash bug on macOS and Windows spawn-based multiprocessing.
Scored on four weighted criteria — install, triggering, output vs. baseline, docs. How scoring works
- Installs cleanly 5/5
- Triggers reliably 5/5
- Output vs. baseline 7/10
- Docs & honesty 5/5
What Arboreto does
Guides GRN inference from bulk or single-cell RNA-seq expression data using arboreto's GRNBoost2 and GENIE3 algorithms, including TF filtering, local/cluster Dask scaling, and pySCENIC integration. Triggers when analyzing transcriptomics data to find transcription-factor-to-target-gene regulatory relationships.
How to install Arboreto
git clone https://github.com/K-Dense-AI/scientific-agent-skills
cd scientific-agent-skills
mkdir -p ~/.claude/skills
cp -r skills/arboreto ~/.claude/skills/arboreto
Skills live in ~/.claude/skills/ (global) or .claude/skills/
(per-project). Restart Claude Code after installing.
Commands — how to trigger Arboreto
-
/arboretoInfer gene regulatory networks from expression data with GRNBoost2/GENIE3, scaled via Dask.
It also activates on plain-language prompts like these:
-
Infer a gene regulatory network with GRNBoost2 -
Run GENIE3 GRN inference on my expression matrix -
Build a GRN from single-cell data using arboreto
Frequently asked questions
- Is the Arboreto skill free?
- Yes. The skill itself is free from K-Dense-AI/scientific-agent-skills. SkillProof publishes the install command and an independent test verdict at no cost.
- Does Arboreto work with Claude Code?
- We tested it with Claude Code 2.x (agent harness) on Jul 14, 2026. Verdict: Tested · Works. The Quick Start marks the `if __name__ == '__main__':` Dask guard as 'Critical' and repeats it in Troubleshooting; a baseline script assembled from general arboreto knowledge dropped that guard, which is a genuine hang/crash bug on macOS and Windows spawn-based multiprocessing.
- What is the Arboreto SkillProof Score?
- 8.8/10 — installs cleanly 5/5, triggers reliably 5/5, output vs. baseline 7/10, docs & honesty 5/5.
- How do I install Arboreto?
- Copy the install command from this page, run it in your terminal, and restart Claude Code. Skills live in ~/.claude/skills/ (global) or .claude/skills/ inside a project.
- Can I use Arboreto with Cursor, Copilot, Gemini CLI, Codex or other AI tools?
- The SKILL.md format is native to Claude (Claude Code, Desktop, claude.ai). The instructions inside adapt to other assistants: Cursor rules, GitHub Copilot instructions, Windsurf rules, Custom GPTs, AGENTS.md for OpenAI Codex, and GEMINI.md for Google Gemini CLI — our conversion guides cover each, and the free converter on the tools page does the wrapping for you.