投稿前单细胞 DE 影子审阅

SkillDev tools

Review completed multi-donor single-cell differential expression before submission. Accept existing DE tables, sample sheets, AnnData, scripts and claims; produce located findings, evidence gaps, repairs and human review. Record pilot observations without claiming validated benefit.

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the 投稿前单细胞 DE 影子审阅 skill

What this skill tells your AI

The instructions your AI receives, as published by herry423/bionexus in skills/single-cell-de-audit/SKILL.md and read by ahel’s review.

Use for completed multi-donor single-cell DE results before submission, a lab meeting or handoff. Keep the user's existing analysis workflow. The first product promise is a bounded evidence review; error reduction and saved time remain hypotheses until measured in laboratories.

First review

Inspect supplied files and column names. A DE table plus sample sheet is a useful starting point. Request missing donor/condition mappings only when needed. Do not require a full analysis rerun or fabricate execution records to get a pass.

bionexus audit-de --de-table de_results.csv --sample-sheet samples.csv --claim "Exact proposed manuscript claim" --bundle review-case-001

Use a new bundle directory. Add --script analysis.ipynb or --execution execution.json when those artifacts already exist. AnnData uses --h5ad results.h5ad and requires goldchain; table review works with the core package.

For a teaching example with no user data:

bionexus audit-de --demo --bundle review-demo

The synthetic example deliberately lacks evidence; exit code 1 is expected. It cannot count toward pilot benefit. If the installed CLI lacks these options, report the version mismatch rather than claiming a source-tree feature ran in the installed plugin.

Deliver the review

Open REVIEW.md first: priority findings, their locations, minimal next steps, missing evidence and claim limits. Link audit-full.md for every finding and recorded fact. Do not turn a generic check into a specific donor/contrast attribution without evidence. Code snippets are suggestions, not verified execution.

The original audit status is binding. Missing evidence and parse failures remain explicit; a result-table schema, a script mentioning pseudobulk or a receipt hash is not proof of donor-level execution. Distinguish artifact validity from the warrant for the supplied claim. Keep valid negative results and unresolved interpretations visible. Leave scientific adjudication with the responsible human.

Pilot observations, only when requested

Use reference-review.json with original inputs for a human reference review before revealing BioNexus findings. Copy the finished reference fields into review.json, then ask a human to judge each finding and record time/cost and reuse intent. Never invent reviewers, independent labels or saved minutes.

bionexus audit-de-summary review-case-001/review.json --out pilot-observations.md

Pending reviews and synthetic demos are excluded. Duplicate cases, changed audit hashes, incomplete judgments and invalid times are rejected. Summaries are self-reported descriptive evidence; they do not activate calibration or certify net benefit. See docs/de-pilot-guide.zh-CN.md in the source checkout for the pilot procedure. No outreach, scheduling, LIMS write or autonomous planning is part of this skill.

Signals

GitHub stars
31
Forks
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Last commit
Sep 2026
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Item type
skill
Key
single-cell-de-audit
Source
github.com/herry423/bionexus