bio-spatial-transcriptomics-image-analysis
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.
npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-spatial-transcriptomics-image-analysis --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
## Version Compatibility Reference examples tested with: Cellpose 3.0+, matplotlib 3.8+, numpy 1.26+, pandas 2.2+, scanpy 1.10+, scikit-learn 1.4+, scipy 1.12+, squidpy 1.3+ Before using code patterns, verify installed versions match. If versions differ: - Python: `pip show <package>` then `help(module.function)` to check signatures If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying. # Image Analysis for Spatial Transcriptomics **"Segment cells in my tissue image"** → Extract image features, segment nuclei/cells, and compute morphological features from H&E or immunofluorescence images paired with spatial data. - Python: `squidpy.im.process()`, `squidpy.im.segment()` with Cellpose backend Extract features and segment tissue images in spatial transcriptomics data. ## Required Imports ```python import squidpy as sq import scanpy as sc import numpy as np import matplotlib.pyplot as plt from skimage import io, filters, segmentation ``` ## Access Tissue Images ```python # Get image from Visium data library_id = list(adata.uns['spatial'].keys())[0] img_dict = adata.uns['spatial'][lib
- Version Compatibility
- Required Imports
- Access Tissue Images
- Create ImageContainer
- Extract Image Features per Spot
- Available Image Features
- Segment Cells/Nuclei
- Segment with Cellpose
- Extract Spot Image Crops
- Color Deconvolution (H&E)
- Compute Morphological Features
- Use Image Features for Clustering
- Smooth Expression with Image
- Related Skills
What does the bio-spatial-transcriptomics-image-analysis skill do?
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.
How do I install it?
Run `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-spatial-transcriptomics-image-analysis --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From FreedomIntelligence/OpenClaw-Medical-Skills, a repository with 2,909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.