scVelo (Claude Skill)

Claude skill that drives scVelo for RNA-velocity analysis — estimating directed cell-state transitions from unspliced/spliced mRNA dynamics in single-cell RNA-seq data.


Type	Claude Skill
Supplier	K-Dense Inc. (community OSS)
Availability	GA — actively maintained 2025–2026
Pricing	Free / OSS skill (MIT collection); scVelo itself is BSD-3
Capabilities	Read/Write — Claude executes scVelo via Python/Bash

How to install

Claude Code / Claude.ai — Skills CLI (recommended):
```
npx skills add K-Dense-AI/scientific-agent-skills
```
Installs the K-Dense collection; enable the scvelo skill when prompted (also works in Cursor/Codex via the Agent Skills spec; requires Node ≥ 18).

Claude Code / Claude Desktop — manual clone:

git clone https://github.com/K-Dense-AI/scientific-agent-skills
cp -r scientific-agent-skills/skills/scvelo ~/.claude/skills/
pip install scvelo

Project-scoped alternative: copy into .claude/skills/ instead of ~/.claude/skills/.

What it does

SKILL.md with recipes for:

Preprocessing unspliced/spliced counts from loom / velocyto / STARsolo / Kallisto-bustools outputs
Steady-state, stochastic, and dynamical velocity models
Velocity-embedding projections onto UMAP / t-SNE
Latent-time inference and driver-gene identification
Velocity confidence and coherence scoring
Trajectory and lineage analysis paired with PAGA

Primary use cases: Mapping differentiation trajectories, identifying lineage-decision genes, dynamics analysis in development and disease, ordering cells by inferred latent time.

Notes

Pairs with the catalog’s scanpy, anndata, cellxgene-census, and scvi-tools skills for end-to-end single-cell trajectory workflows. RNA-velocity requires upstream alignment that emits spliced + unspliced count matrices (velocyto, kallisto-bustools, or STARsolo Velocyto mode) — scVelo cannot recover velocities from a counts-only AnnData. Skill is documentation plus Python recipes — Claude calls scVelo locally via Bash/Python.

Sources

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