bio-single-cell-batch-integration
Integrate multiple scRNA-seq samples/batches using Harmony, scVI, Seurat anchors, and fastMNN. Remove technical variation while preserving biological differences. Use when integrating multiple scRNA-seq batches or datasets.
npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-single-cell-batch-integration --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: anndata 0.10+, scanpy 1.10+, scikit-learn 1.4+, scvi-tools 1.1+ Before using code patterns, verify installed versions match. If versions differ: - Python: `pip show <package>` then `help(module.function)` to check signatures - R: `packageVersion('<pkg>')` then `?function_name` to verify parameters If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying. # Batch Integration Integrate multiple scRNA-seq datasets to remove batch effects while preserving biological variation. ## Tool Comparison | Tool | Speed | Scalability | Best For | |------|-------|-------------|----------| | Harmony | Fast | Good | Quick integration, most use cases | | scVI | Moderate | Excellent | Large datasets, deep learning | | Seurat CCA/RPCA | Moderate | Good | Conserved biology across batches | | fastMNN | Fast | Good | MNN-based correction | ## Harmony (R/Python) **Goal:** Remove batch effects from merged scRNA-seq datasets using Harmony's iterative correction of PCA embeddings. **Approach:** Run PCA on merged data, iteratively adjust embeddings to mi
- Version Compatibility
- Tool Comparison
- Harmony (R/Python)
- R with Seurat
- Multiple Batch Variables
- Python with Scanpy
- scVI (Python)
- scVI with Covariates
- scANVI (with cell type labels)
- Seurat Integration (R)
- CCA-based Integration
- RPCA (Faster for Large Datasets)
- Seurat v5 Integration
- fastMNN (R)
What does the bio-single-cell-batch-integration skill do?
Integrate multiple scRNA-seq samples/batches using Harmony, scVI, Seurat anchors, and fastMNN. Remove technical variation while preserving biological differences. Use when integrating multiple scRNA-seq batches or datasets.
How do I install it?
Run `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-single-cell-batch-integration --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.