bio-single-cell-trajectory-inference
Infer developmental trajectories and pseudotime from single-cell RNA-seq data using Monocle3, Slingshot, and scVelo for RNA velocity analysis. Use when inferring developmental trajectories or pseudotime.
npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-single-cell-trajectory-inference --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: Cell Ranger 8.0+, 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 - CLI: `<tool> --version` then `<tool> --help` to confirm flags If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying. # Trajectory Inference ## Monocle3 (R) **Goal:** Infer developmental trajectories and pseudotime ordering using Monocle3's principal graph approach. **Approach:** Learn a principal graph through the data manifold, order cells along the graph from a root state, and extract pseudotime values. **"Find the developmental trajectory in my data"** → Construct a tree-like graph through the cell embedding, assign pseudotime from a root population, and identify branch points. ```r library(monocle3) # Create cell_data_set from Seurat cds <- as.cell_data_set(seurat_obj) # Preprocess (if not already done) cds <- preprocess_cds(cds, num_dim = 50) cds <- reduce
- Version Compatibility
- Monocle3 (R)
- Set Root Programmatically
- Slingshot (R)
- Slingshot with Start/End Clusters
- scVelo RNA Velocity (Python)
- scVelo Dynamical Model
- Gene Dynamics Along Trajectory
- Branch Point Analysis
- Velocyto Preprocessing
- PAGA Trajectory (Scanpy)
- Related Skills
Generate loom file with spliced/unspliced counts velocyto run10x -m repeat_mask.gtf /path/to/cellranger_output annotation.gtf For SmartSeq2 velocyto run_smartseq2 -o output -m repeat_mask.gtf -e sample bam_files/*.bam annotation.gtf
What does the bio-single-cell-trajectory-inference skill do?
Infer developmental trajectories and pseudotime from single-cell RNA-seq data using Monocle3, Slingshot, and scVelo for RNA velocity analysis. Use when inferring developmental trajectories or pseudotime.
How do I install it?
Run `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-single-cell-trajectory-inference --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.