AN
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AnnData
AnnData is a Python package for handling annotated data matrices, storing experimental measurements (X) alongside observation metadata (obs)…
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Data & Repro
SC
scrna-qc
Maintainer FreedomIntelligence · Last updated April 1, 2026
Single-cell RNA-seq quality control: doublet removal, ambient RNA, filtering thresholds.
Original source
FreedomIntelligence/OpenClaw-Medical-Skills
https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/scrna-qc
- Maintainer
- FreedomIntelligence
- License
- MIT
- Last updated
- April 1, 2026
Skill Snapshot
Key Details From SKILL.md
Key Notes
- description (10-20 chars): QC autopilot.
- keywords: scRNAseq, MAD, h5ad, QC, plots.
- description (10-20 chars): QC autopilot keywords: scRNAseq, MAD, h5ad, QC, plots.
- 1. Accept.h5ad, 10x.h5, or 10x directory inputs; set mitochondrial/ribosomal patterns as needed. 2. Run qc_analysis.py (CLI) or call qc_core helpers to compute metrics, apply MAD thresholds, and filter cells/genes. 3. Generate standard plots (metrics before/after, threshold overlays) plus filtered data artifacts. 4. Document parameters (mad_counts/genes/mt, mt_threshold, min_cells, log1p flag) inside the summary JSON. 5. Provide guidance on next steps (doublet detection, downstream analysis).
Source Doc
Excerpt From SKILL.md
Guardrails
- Adjust MT% expectations for tissue context; avoid over-filtering rare populations.
- This workflow is QC only—doublet handling and batch correction stay separate.
- Keep reproducibility by storing command invocations and environment info.
Use cases
- Use scrna-qc for single-cell or spatial omics analysis.
- Apply scrna-qc to clustering, integration, or trajectory workflows.
Not for
- Do not rely on this catalog entry alone for installation or maintenance details.
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