
Single Cell Rna Qc
Runs the standard scverse QC pipeline on single-cell RNA-seq data with MAD-based filtering and generates before/after visualizations. Works with both h5ad files and 10X h5 outputs. The convenience script handles the full workflow automatically, but you can also use the modular functions if you need different thresholds for cell subsets or want to skip filtering entirely. Default thresholds are intentionally permissive to avoid losing rare populations. Outputs include filtered h5ad files ready for downstream analysis plus PNG plots showing count depth, gene detection, and mitochondrial content. This is the boring foundation work you need to do before anything interesting happens, packaged so you don't have to remember the scanpy incantations.
- skills.sh installs
- 2.5K
- GitHub stars
- 35.3K
- last updated
- Aug 21, 2026
Install
$ npx -y skills add anthropics/knowledge-work-plugins --skill single-cell-rna-qc --agent claude-codeInstalls into .claude/skills of the current project.
Files
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:
.h5adfiles (AnnData format from scanpy/Python workflows).h5files (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:
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.
Sponsors
Details
- Repository
- github.com/anthropics/knowledge-work-plugins
- Category
- Code Review & Quality
- First seen
- May 16, 2026
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