bio-single-cell-markers-annotation
Find marker genes and annotate cell types in single-cell RNA-seq using Seurat (R) and Scanpy (Python). Use for differential expression between clusters, identifying cluster-specific markers, scoring gene sets, and assigning cell type labels. Use when finding marker genes and annotating clusters.
npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-single-cell-markers-annotation --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: DESeq2 1.42+, pandas 2.2+, scanpy 1.10+ 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. # Marker Genes and Cell Type Annotation Find differentially expressed genes between clusters and annotate cell types. ## Scanpy (Python) **Goal:** Identify cluster-specific marker genes, score gene sets, and annotate cell types using Scanpy. **Approach:** Perform differential expression testing between clusters with Wilcoxon rank-sum, visualize markers with dot plots and heatmaps, and assign cell type labels manually. **"Find marker genes for each cluster"** → Test each cluster against all others for differentially expressed genes and rank by statistical significance and fold change. ### Required Imports ```python import scanpy as sc import pandas as pd ``` ### Find Markers for All Clusters ```python
- Version Compatibility
- Scanpy (Python)
- Required Imports
- Find Markers for All Clusters
- Marker Detection Methods
- Filter Markers
- Compare Specific Clusters
- Visualize Marker Expression
- Gene Set Scoring
- Cell Cycle Scoring
- Manual Cell Type Annotation
- Export Markers
- Seurat (R)
- Required Libraries
What does the bio-single-cell-markers-annotation skill do?
Find marker genes and annotate cell types in single-cell RNA-seq using Seurat (R) and Scanpy (Python). Use for differential expression between clusters, identifying cluster-specific markers, scoring gene sets, and assigning cell type labels. Use when finding marker genes and annotating clusters.
How do I install it?
Run `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-single-cell-markers-annotation --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.