arboreto-grn-inference SKILL.md skillB
arboreto-grn-inference from jaechang-hits/sciagent-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add jaechang-hits/sciagent-skills/arboreto-grn-inference@git:20260929.7a7d60fPins git:20260929.7a7d60f in mdr.lock. Pin the fingerprint instead.
- Audit grade
- B, 16 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- jaechang-hits/sciagent-skills
- Path
skills/genomics-bioinformatics/arboreto-grn-inference/SKILL.md- Versions recorded
- 4
- Latest version
- git:20260929.7a7d60f, committed Sep 29, 2026
- First version recorded
- Feb 18, 2026
- Size
- 21,130 bytes
- Repository stars
- 381
- License
- a license file GitHub does not identify
GRN inference from expression via GRNBoost2 (gradient boosting) or GENIE3 (Random Forest). Load matrix, filter by TFs, infer TF-target-importance links, save network. Dask-parallelized to single-cell scale. Core SCENIC component.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# Arboreto GRN Inference ## Overview Arboreto infers gene regulatory networks (GRNs) from gene expression data using parallelized tree-based regression. For each target gene, it trains a regression model with all other genes (or a specified TF list) as features and emits TF-target-importance triplets. It provides two interchangeable algorithms -- GRNBoost2 (gradient boosting, fast) and GENIE3 (Random Forest, classic) -- sharing identical input/output formats. Computation is Dask-parallelized, scaling from laptop cores to HPC clusters. ## When to Use - Inferring transcription factor-to-target gene regulatory relationships from bulk RNA-seq expression data - Building gene regulatory networks from single-cell RNA-seq count matrices (cells as rows, genes as columns) - Generating the adjacency matrix (Step 1) of the pySCENIC regulatory analysis pipeline - Comparing regulatory network structure across experimental conditions (e.g., control vs treatment) - Producing consensus regulatory networks by running inference across multiple random seeds - Validating GRN results by comparing GRNBoost2 and GENIE3 outputs on the same dataset …
Read the whole file at its exact version.
How to install
mdr add jaechang-hits/sciagent-skills/arboreto-grn-inference@sha256:27d23babdbe32003The line at the top of this page pins the label git:20260929.7a7d60f, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_ht2w4u4fqviduiji)
4 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 4 versions of this file, between Feb 18, 2026 and Sep 29, 2026, about one every 74 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260929.7a7d60f latest | 2026-09-29 | 7a7d60f | 21,130 B | B | view · diff |
| git:20260929.35fe6e3 | 2026-09-29 | 35fe6e3 | 21,179 B | B | view · diff |
| git:20260428.81ea2d2 | 2026-04-28 | 81ea2d2 | 19,473 B | B | view · diff |
| git:20260218.8df1694 | 2026-02-18 | 8df1694 | 19,568 B | B | view |
Audit of the latest version
- fail: No link to a raw IP address (matched: http://127.0.0.1:8787)
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (21130 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No script tag
Starting a new one? Use a template for SKILL.md on mdpantry, which passes every one of these checks and says what to change in it.
Source
jaechang-hits/sciagent-skills · 381 stars · license a license file GitHub does not identify · pushed 2026-10-16 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_ht2w4u4fqviduiji GET https://markdownregistry.com/api/v1/resolve?ref=jaechang-hits/sciagent-skills/arboreto-grn-inference GET https://markdownregistry.com/api/v1/blob/27d23babdbe32003b382af63d4746a9e41898c367dc42ff57e889f6139c0b50e
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.
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