AnnData
AnnData is a Python package for handling annotated data matrices, storing experimental measurements (X) alongside observ…
维护者 FreedomIntelligence · 最近更新 2026年4月1日
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.
原始来源
https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-spatial-transcriptomics-spatial-preprocessing
技能摘要
原始文档
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())
Goal: Quantify mitochondrial gene expression as a quality indicator.
Approach: Flag MT-prefixed genes, then compute percentage of counts from mitochondrial genes per spot.
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