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Scrna qc

Skill FridrichMethod/awesome-skills/skills/scrna-qc

Execute the MAD-based single-cell RNA-seq QC workflow (scripts + Python API) to filter low-quality cells and emit reports plus filtered AnnData files.From its SKILL.md

Install
npx -y skills add FridrichMethod/awesome-skills --skill scrna-qc

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

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  • no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
  • 13 stars13 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

1.7 KB, 373 tokens by cl100k_base, as published. Nobody here has run it

<!-- # COPYRIGHT NOTICE # This file is part of the "Universal Biomedical Skills" project. # Copyright (c) 2026 MD BABU MIA, PhD <[email protected]> # All Rights Reserved. # # This code is proprietary and confidential. # Unauthorized copying of this file, via any medium is strictly prohibited. # # Provenance: Authenticated by MD BABU MIA -->

At-a-Glance

  • description (10-20 chars): QC autopilot
  • keywords: scRNAseq, MAD, h5ad, QC, plots

Workflow

  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).

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.

References

  • See README.md, qc_core.py, qc_analysis.py, and qc_plotting.py for API usage and schema details.
<!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE -->

What ships with it: 5 files

36.2 KB alongside SKILL.md, 3 of them executable

Keep looking

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