bio-spatial-transcriptomics-spatial-statistics
Compute spatial statistics for spatial transcriptomics data using Squidpy. Calculate Moran's I, Geary's C, spatial autocorrelation, co-occurrence analysis, and neighborhood enrichment. Use when computing spatial autocorrelation or co-occurrence statistics.
npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-spatial-transcriptomics-spatial-statistics --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: numpy 1.26+, pandas 2.2+, scanpy 1.10+, 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. # Spatial Statistics Compute spatial statistics and identify spatially variable features. ## Required Imports ```python import squidpy as sq import scanpy as sc import pandas as pd import numpy as np ``` ## Compute Spatial Autocorrelation (Moran's I) **Goal:** Identify genes whose expression is spatially autocorrelated across tissue. **Approach:** Build a spatial neighbor graph, then compute Moran's I statistic per gene to measure clustering of similar values. **"Find spatially variable genes"** -> Compute Moran's I autocorrelation on the spatial neighbor graph to rank genes by spatial patterning. ```python # Requires spatial neighbors sq.gr.spatial_neighbors(adata, coord_type='generic', n_neighs=6) # Compute Moran's I for all genes (can be slow)
- Version Compatibility
- Required Imports
- Compute Spatial Autocorrelation (Moran's I)
- Interpret Moran's I
- Compute Geary's C
- Co-occurrence Analysis
- Interpret Co-occurrence
- Neighborhood Enrichment
- Extract Enrichment Z-scores
- Ripley's Statistics
- Centrality Scores
- Interaction Matrix
- Custom Spatial Statistic
- Local Moran's I (LISA)
What does the bio-spatial-transcriptomics-spatial-statistics skill do?
Compute spatial statistics for spatial transcriptomics data using Squidpy. Calculate Moran's I, Geary's C, spatial autocorrelation, co-occurrence analysis, and neighborhood enrichment. Use when computing spatial autocorrelation or co-occurrence statistics.
How do I install it?
Run `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-spatial-transcriptomics-spatial-statistics --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.