spatial-velocity

Compute RNA velocity vectors from spatial transcriptomics AnnData objects.

155|26|Updated Mar 14, 2026
One-click install
npx skills add https://github.com/TianGzlab/OmicsClaw --skill spatial-velocity
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: spatial-velocity
Source: https://github.com/TianGzlab/OmicsClaw/tree/main/skills/spatial/spatial-velocity
Command: npx skills add https://github.com/TianGzlab/OmicsClaw --skill spatial-velocity

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires scvelo, scvi-tools, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the complex process of inferring cellular dynamics and directional movement from spatial transcriptomics data, which traditionally requires manual configuration of sophisticated bioinformatics pipelines.

Core Features & Use Cases

  • RNA Velocity Analysis: Computes RNA velocity vectors to predict future cell states.
  • Spatial Integration: Overlays velocity vectors onto spatial expression maps or UMAP embeddings.
  • Kinetic Modeling: Supports stochastic, deterministic, and dynamical models for RNA kinetics.
  • Use Case: Analyze how cells are differentiating or migrating within a tissue by visualizing the predicted direction of gene expression changes over time.

Quick Start

Compute RNA velocity and map the arrows onto my tissue using the default stochastic model.

Frequently Asked Questions about spatial-velocity

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I compute RNA velocity on spatial transcriptomics data?

To compute RNA velocity on spatial transcriptomics data, this Skill analyzes AnnData objects containing spliced and unspliced RNA count layers to infer cellular dynamics and predict future cell states.

What is the difference between stochastic, deterministic, and dynamical models for RNA velocity?

RNA velocity kinetic modeling differs by approach: stochastic models handle transcriptional variability, deterministic models assume fixed rates, and dynamical models infer transient cell states to map cellular dynamics.

Do I need spliced and unspliced RNA counts to infer cellular dynamics?

Yes, inferring cellular dynamics requires AnnData objects with spliced and unspliced RNA count layers, as these counts form the mathematical basis for calculating RNA velocity vectors.

Can I use VELOVI for variational inference of gene expression changes?

Yes, you can use VELOVI for variational inference alongside scVelo stochastic, deterministic, and dynamical models to analyze gene expression changes and predict future cell states.

How do I visualize RNA velocity vectors on a UMAP embedding?

You can visualize RNA velocity vectors by overlaying the computed arrows onto UMAP embeddings or spatial expression maps to analyze how cells are differentiating or migrating within a tissue.

Does this RNA velocity pipeline work with scvi-tools?

Yes, the RNA velocity pipeline integrates with scvi-tools and scvelo to automate the complex process of inferring directional movement from spatial transcriptomics data.