| name | single-cell-rna-qc |
| description | Performs quality control on single-cell RNA-seq data (.h5ad or .h5 files) using scverse best practices with MAD-based filtering and comprehensive visualizations. |
| type | reference |
| version | 1.0.0 |
| category | science |
| last_updated | "2026-02-03T00:00:00.000Z" |
| source | https://github.com/anthropics/knowledge-work-plugins |
| related_skills | ["scvi-tools","nextflow-pipelines","clinical-trial-protocol","instrument-data-allotrope","scientific-problem-selection"] |
| capabilities | [] |
| requires | [] |
| see_also | [] |
| tags | [] |
| scripts_exempt | true |
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:
python3 scripts/qc_analysis.py input.h5ad
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 (all cells filtered the same way)
- Batch processing multiple datasets
- Quick exploratory analysis
- User wants the "just works" solution
Requirements: anndata, scanpy, scipy, matplotlib, seaborn, numpy
Parameters:
Customize filtering thresholds and gene patterns using command-line parameters:
--output-dir - Output directory--mad-counts, --mad-genes, --mad-mt - MAD thresholds for counts/genes/MT%--mt-threshold - Hard mitochondrial % cutoff--min-cells - Gene filtering threshold--mt-pattern, --ribo-pattern, --hb-pattern - Gene name patterns for different species
Use --help to see current default values.
Outputs:
All files are saved to directory by default (or to the directory specified by ):
