AnnData
AnnData is a Python package for handling annotated data matrices, storing experimental measurements (X) alongside observation metadata (obs)…
Maintainer FreedomIntelligence · Last updated April 1, 2026
Process and analyze tissue images from spatial transcriptomics data using Squidpy. Extract image features, segment cells/nuclei, and compute morphological features from H&E or IF images. Use when processing tissue images for spatial transcriptomics.
Original source
https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-spatial-transcriptomics-image-analysis
Skill Snapshot
Source Doc
hires = img_dict['hires'] lowres = img_dict['lowres']
print(f'Hires shape: {hires.shape}') print(f'Lowres shape: {lowres.shape}')
scalef = adata.uns['spatial'][library_id]['scalefactors'] spot_diameter = scalef['spot_diameter_fullres'] hires_scale = scalef['tissue_hires_scalef']
## Create ImageContainer
**Goal:** Wrap tissue images in Squidpy's ImageContainer for structured access and feature extraction.
**Approach:** Initialize an ImageContainer from the AnnData image data or a TIFF file.
```python
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