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scvelo

Analyze single-cell RNA-seq data with scvelo to infer cell state transitions and latent time.

13|3|Updated Jun 10, 2026
Search Tags:#single-cell RNA-seq#RNA velocity#trajectory inference#driver gene identification#cell state transition
One-click install
npx skills add https://github.com/tassiovale/claude-code-kit --skill scvelo-tassiovale
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: scvelo
Source: https://github.com/tassiovale/claude-code-kit/tree/main/skills/scvelo
Command: npx skills add https://github.com/tassiovale/claude-code-kit --skill scvelo-tassiovale

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires scvelo, scanpy, velocyto, alevin-fry, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides a comprehensive solution for RNA velocity analysis, enabling users to infer cell state transitions, trajectory directions, latent time, and identify driver genes from single-cell RNA-seq data.

Core Features & Use Cases

  • RNA Velocity Analysis: Estimate cell state transitions from unspliced/spliced mRNA dynamics.
  • Trajectory Inference: Infer trajectory directions and compute latent time.
  • Driver Gene Identification: Identify driver genes in single-cell RNA-seq data.
  • Use Case: For a study on hematopoiesis, use scVelo to analyze single-cell RNA-seq data and identify genes that drive cell differentiation.

Quick Start

Run the scvelo skill on your single-cell RNA-seq data to estimate RNA velocity and infer cell state transitions.

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 transitions from single-cell RNA-seq data?▼

You can infer cell state transitions by performing RNA velocity analysis on single-cell RNA-seq data to estimate unspliced and spliced mRNA dynamics. This Skill uses scVelo to calculate trajectory directions and latent time.

What is RNA velocity and how does it identify driver genes in scRNA-seq?▼

RNA velocity measures the ratio of unspliced to spliced mRNA to determine cell state transitions. By analyzing these transcriptional dynamics, you can identify driver genes that actively push cell differentiation forward.

Do I need to preprocess my scRNA-seq data before running RNA velocity analysis?▼

Yes, you must preprocess your scRNA-seq data using velocyto or alevin-fry to generate an AnnData object containing separate spliced and unspliced RNA layers required for the velocity calculation.

How do I calculate latent time and trajectory directions for cell differentiation?▼

You calculate latent time and trajectory directions by running scVelo on an AnnData object with spliced and unspliced layers. This models transcriptional dynamics to order cells along a continuous differentiation timeline.

Does this RNA velocity analysis work with scanpy AnnData objects?▼

Yes, the RNA velocity analysis works directly with scanpy AnnData objects. It leverages the scanpy and scvelo Python libraries to process the spliced and unspliced RNA layers stored within the AnnData format.

Why does my RNA velocity analysis require unspliced RNA counts?▼

RNA velocity analysis requires unspliced RNA counts because the method mathematically models the transition of unspliced mRNA into spliced mRNA to determine the direction and speed of cell state transitions.

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