single-cell-rna-qc
Performs quality control on single-cell RNA-seq data (.h5ad or .h5 files) using scverse best practices with MAD-based filtering and comprehensive visualizations. Use when users request QC analysis, filtering low-quality cells, assessing data quality, or following scverse/scanpy best practices for single-cell analysis.
npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill single-cell-rna-qc --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Single-Cell RNA-seq Quality Control Automated QC workflow for single-cell RNA-seq data following scverse best practices. ## When to Use This Skill Use when users: - Request quality control or QC on single-cell RNA-seq data - Want to filter low-quality cells or assess data quality - Need QC visualizations or metrics - Ask to follow scverse/scanpy best practices - Request MAD-based filtering or outlier detection **Supported input formats:** - `.h5ad` files (AnnData format from scanpy/Python workflows) - `.h5` files (10X Genomics Cell Ranger output) **Default recommendation**: Use Approach 1 (complete pipeline) unless the user has specific custom requirements or explicitly requests non-standard filtering logic. ## Approach 1: Complete QC Pipeline (Recommended for Standard Workflows) For standard QC following scverse best practices, use the convenience script `scripts/qc_analysis.py`: ```bash python3 scripts/qc_analysis.py input.h5ad # or for 10X Genomics .h5 files: python3 scripts/qc_analysis.py raw_feature_bc_matrix.h5 ``` The script automatically detects the file format and loads it appropriately. **When to use this approach:** - Standard QC workflow with adjustable thresholds (al
- When to Use This Skill
- Approach 1: Complete QC Pipeline (Recommended for Standard Workflows)
- Workflow Steps
- Approach 2: Modular Building Blocks (For Custom Workflows)
- Best Practices
- Reference Materials
- Next Steps After QC
python3 scripts/qc_analysis.py input.h5ad or for 10X Genomics .h5 files: python3 scripts/qc_analysis.py raw_feature_bc_matrix.h5
What does the single-cell-rna-qc skill do?
Performs quality control on single-cell RNA-seq data (.h5ad or .h5 files) using scverse best practices with MAD-based filtering and comprehensive visualizations. Use when users request QC analysis, filtering low-quality cells, assessing data quality, or following scverse/scanpy best practices for single-cell analysis.
How do I install it?
Run `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill single-cell-rna-qc --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From FreedomIntelligence/OpenClaw-Medical-Skills, a repository with 2,909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.