bulk-rnaseq SKILL.md skillA
bulk-rnaseq from k-dense-ai/scientific-agent-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add k-dense-ai/scientific-agent-skills/bulk-rnaseq@v2.0Pins v2.0 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- k-dense-ai/scientific-agent-skills
- Path
skills/bulk-rnaseq/SKILL.md- Versions recorded
- 5
- Latest version
- v2.0, committed Oct 1, 2026
- First version recorded
- Jun 11, 2026
- Size
- 16,890 bytes
- Repository stars
- 56,497
- License
- MIT
Prepares bulk RNA-seq FASTQ, Salmon, STAR or featureCounts output for gene-level differential expression. Covers nf-core/rnaseq and standalone quantification, biological replication, strandedness, reference provenance, validated count assembly and a PyDESeq2 handoff. Use for FASTQ-to-counts analysis, nf-core/rnaseq configuration, STAR/Salmon quantification, or building a counts matrix for DESeq2. For single-cell data use scanpy; for statistical fitting alone use pydeseq2.
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
# Bulk RNA-seq ## Overview This skill prepares bulk RNA-seq reads and quantification output for a reproducible gene-level comparison. It owns sample validation, reads-to-counts recipes, and the count/metadata handoff; downstream statistical fitting and enrichment remain in their specialist skills. "Defensible" means three things, applied throughout: - **Reproducible** — pinned pipeline/tool versions, containers where possible, recorded parameters, fixed random seeds. - **Quality-gated** — QC is inspected and acted on before, during, and after quantification, not skipped. - **Statistically sound** — adequate replication, a design that matches the biology, counts handled correctly, and FDR-controlled testing. The pipeline is: **FastQC/trim → align/quant (STAR/Salmon) → counts → DE (pydeseq2) → enrichment (pathway-enrichment) → figures**. ## When to Use This Skill Use this skill when the user wants to: - Go from FASTQ files (or a sequencing run) to differentially expressed genes and pathways. - Run or configure `nf-core/rnaseq`, or align/quantify with STAR, Salmon, or featureCounts. - Turn Salmon/STAR/featureCounts output into a counts matrix ready for DESeq2/PyDESeq2. …
Read the whole file at its exact version.
How to install
mdr add k-dense-ai/scientific-agent-skills/bulk-rnaseq@sha256:e945e97026850536The line at the top of this page pins the label v2.0, 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_33fwgkxksdmovg3z)
4 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 5 versions of this file, between Jun 11, 2026 and Oct 1, 2026, about one every 28 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| v2.0 latest | 2026-10-01 | a92663a | 16,890 B | A | view · diff |
| v1.2 | 2026-09-30 | ce9e6e9 | 15,988 B | A | view · diff |
| v1.1 | 2026-09-02 | 1e5eeff | 15,621 B | A | view · diff |
| v1.0 | 2026-07-26 | b085e11 | 14,663 B | A | view · diff |
| git:20260611.1b8fae3 | 2026-06-11 | 1b8fae3 | 14,668 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (16890 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 link to a raw IP address
- pass: No script tag
Source
k-dense-ai/scientific-agent-skills · 56,497 stars · license MIT · pushed 2026-11-02 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_33fwgkxksdmovg3z GET https://markdownregistry.com/api/v1/resolve?ref=k-dense-ai/scientific-agent-skills/bulk-rnaseq GET https://markdownregistry.com/api/v1/blob/e945e970268505368e20d9ddc0c135de469e86626d67565ae9047fb05f70cdbf
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.