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scvelo

Analyze RNA velocity in single-cell RNA-seq data with scVelo.

1|2|Updated Apr 29, 2026
Search Tags:#single-cell#anndata#scvelo#rna velocity#trajectory inference#latent time#velocity graph
One-click install
npx skills add https://github.com/fuzzy-dynamics/strings --skill scvelo-fuzzy-dynamics
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: scvelo
Source: https://github.com/fuzzy-dynamics/strings/tree/main/packages/skills/scvelo
Command: npx skills add https://github.com/fuzzy-dynamics/strings --skill scvelo-fuzzy-dynamics

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires scvelo, scanpy, numpy, matplotlib, and includes scripts (resource) and references (resource) components.

What problem does it solve?

RNA velocity analysis in single-cell transcriptomics enables inference of future cell states from spliced/unspliced mRNA dynamics.

Core Features & Use Cases

  • End-to-end velocity workflow: preprocessing, velocity estimation (stochastic or dynamical), velocity graph, and downstream analyses.
  • Latent time and driver gene analysis to identify transitional genes and trajectories.
  • Visualization and interpretation within Scanpy/AnnData ecosystem.

Quick Start

Load an AnnData object with spliced and unspliced layers and run the complete velocity workflow to generate velocity estimates and visualizations.

Frequently Asked Questions about scvelo

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

FAQPage Schema
How do I infer cell-state trajectories from RNA velocity data in single-cell RNA-seq?▼

RNA velocity analysis infers future cell states from spliced and unspliced mRNA dynamics. This Skill provides an end-to-end pipeline covering preprocessing, velocity estimation, velocity graphs, and latent time computation within the Scanpy ecosystem.

What do I need to run RNA velocity estimation with scVelo?▼

To run RNA velocity estimation, you need an AnnData object containing spliced and unspliced counts layers. The workflow operates within the Scanpy ecosystem and requires numpy and matplotlib for data handling and visualization.

Can I use stochastic and dynamical models for velocity estimation in the same workflow?▼

Yes, the velocity estimation workflow supports both stochastic and dynamical models. You can apply either model to compute velocity estimates and then generate velocity graphs and latent time analyses.

How does latent time analysis identify driver genes in trajectory inference?▼

Latent time analysis identifies driver genes by ranking transitional genes along the inferred trajectory. It leverages velocity estimates to determine the direction and speed of cell-state transitions in single-cell data.

What is the difference between velocity graphs and latent time in trajectory analysis?▼

Velocity graphs map the directional transitions between cell states based on spliced and unspliced dynamics, while latent time provides a pseudotemporal ordering of cells along the inferred trajectory to help rank driver genes.

Does this RNA velocity pipeline support visualization of trajectory inference results?▼

Yes, the pipeline includes visualization capabilities for trajectory inference results. It uses matplotlib to generate velocity graphs and latent time projections within the Scanpy and AnnData ecosystem.

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