pydeseq2 SKILL.md skillA
pydeseq2 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/pydeseq2@v1.7Pins v1.7 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/pydeseq2/SKILL.md- Versions recorded
- 8
- Latest version
- v1.7, committed Oct 1, 2026
- First version recorded
- Jun 11, 2026
- Size
- 10,507 bytes
- Repository stars
- 56,497
- License
- MIT
Performs bulk RNA-seq differential expression analysis with PyDESeq2, including count validation, formula designs, explicit contrasts, Wald tests, FDR correction, coefficient-matched LFC shrinkage, and result visualization. Use for PyDESeq2 or Python DESeq2 workflows with biological replicates.
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
# PyDESeq2 Use this skill for bulk RNA-seq negative-binomial GLMs, with explicit biological replicates, covariates, and comparisons. Cells, sequencing lanes, and repeated measurements from the same donor are not independent biological replicates. Donor-level pseudobulk can be appropriate when its aggregation and design match the scientific question; this is not a single-cell per-cell testing workflow. Current [PyDESeq2 0.5.4](https://github.com/scverse/PyDESeq2/releases/tag/v0.5.4) provides Wald tests and apeGLM-style coefficient shrinkage. Do not assume every feature or numerical result of current R DESeq2 is implemented identically. See [API and tested versions](references/api_reference.md) for supported calls, AnnData storage, and source/runtime verification limits. ## Analysis contract 1. Establish the experimental unit, count provenance, sample exclusions, reference levels, and intended comparison before fitting. Use nonnegative integer counts in **samples × genes** order, with unique sample/gene IDs. TPM, FPKM, log data, VST data, and library-normalized counts are not model inputs. Integer checks …
Read the whole file at its exact version.
How to install
mdr add k-dense-ai/scientific-agent-skills/pydeseq2@sha256:f06a9f5ece540c05The line at the top of this page pins the label v1.7, 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_kj5jcvs5s76gsny5)
5 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 8 versions of this file, between Jun 11, 2026 and Oct 1, 2026, about one every 16 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| v1.7 latest | 2026-10-01 | a92663a | 10,507 B | A | view · diff |
| v1.6 | 2026-09-30 | a0aea74 | 13,141 B | A | view · diff |
| v1.5 | 2026-09-30 | ce9e6e9 | 13,141 B | A | view · diff |
| v1.4 | 2026-09-02 | 1e5eeff | 12,773 B | A | view · diff |
| v1.3 | 2026-07-28 | 4fb7e0b | 11,815 B | A | view · diff |
| v1.2 | 2026-07-26 | 2f2022d | 11,815 B | A | view · diff |
| v1.1 | 2026-07-26 | b085e11 | 17,513 B | A | view · diff |
| git:20260611.1b8fae3 | 2026-06-11 | 1b8fae3 | 17,518 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 (10507 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_kj5jcvs5s76gsny5 GET https://markdownregistry.com/api/v1/resolve?ref=k-dense-ai/scientific-agent-skills/pydeseq2 GET https://markdownregistry.com/api/v1/blob/f06a9f5ece540c05bd8a8208bb3970d000b13cb1032abc9488cfbfe6106cd843
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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