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AnnData
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Data & Repro
BI
bio-spatial-transcriptomics-spatial-preprocessing
Maintainer FreedomIntelligence · Last updated April 1, 2026
Quality control, filtering, normalization, and feature selection for spatial transcriptomics data. Calculate QC metrics, filter spots/cells, normalize counts, and identify highly variable genes. Use when filtering and normalizing spatial transcriptomics data.
Original source
FreedomIntelligence/OpenClaw-Medical-Skills
https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-spatial-transcriptomics-spatial-preprocessing
- Maintainer
- FreedomIntelligence
- License
- MIT
- Last updated
- April 1, 2026
Skill Snapshot
Key Details From SKILL.md
Key Notes
- Python: scanpy.pp.calculate_qc_metrics() → filter_cells() → normalize_total() on spatial AnnData.
- Preprocess my spatial transcriptomics data" → Calculate spatial QC metrics (genes/spot, mitochondrial fraction), filter spots by expression and tissue coverage, normalize, and select variable genes. Python: scanpy.pp.calculate_qc_metrics() → filter_cells() → normalize_total() on spatial AnnData.
- QC, filtering, normalization, and feature selection for spatial data.
- sc.pp.calculate_qc_metrics(adata, inplace=True).
Source Doc
Excerpt From SKILL.md
Calculate QC Metrics
Goal: Compute per-spot and per-gene quality control statistics.
Approach: Use Scanpy's calculate_qc_metrics to generate total counts, gene counts, and other summary statistics.
## View QC columns
print(adata.obs[['total_counts', 'n_genes_by_counts']].describe())
print(adata.var[['total_counts', 'n_cells_by_counts']].describe())
Calculate Mitochondrial Content
Goal: Quantify mitochondrial gene expression as a quality indicator.
Approach: Flag MT-prefixed genes, then compute percentage of counts from mitochondrial genes per spot.
Use cases
- Use when filtering and normalizing spatial transcriptomics data.
Not for
- Do not rely on this catalog entry alone for installation or maintenance details.
Upstream Related Skills
- spatial-data-io - Load spatial data
- spatial-neighbors - Build spatial graphs
- single-cell/preprocessing - Non-spatial preprocessing
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