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alterlab-scvelo

Analyze RNA velocity to infer cell state transitions from spliced and unspliced counts.

58|9|Updated Mar 16, 2026
Search Tags:#scanpy#scvelo#single-cell-rna-seq#rna-velocity#trajectory-inference#latent-time#cell-state-transition
One-click install
npx skills add https://github.com/AlterLab-IEU/AlterLab-Academic-Skills --skill alterlab-scvelo
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: alterlab-scvelo
Source: https://github.com/AlterLab-IEU/AlterLab-Academic-Skills/tree/main/skills/bioinformatics/alterlab-scvelo
Command: npx skills add https://github.com/AlterLab-IEU/AlterLab-Academic-Skills --skill alterlab-scvelo

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 provides a framework to infer cell state transitions in single-cell RNA-seq by comparing unspliced and spliced mRNA to estimate transcriptional dynamics and trajectories.

Core Features & Use Cases

  • Trajectory inference from snapshot scRNA-seq data using splicing kinetics
  • Latent time estimation and downstream visualization on embeddings (UMAP)
  • Driver gene analysis via velocity-based metrics to identify regulators
  • Complement to Scanpy integration for rich, end-to-end analyses
  • Real-world example: map developmental trajectories across heterogeneous cell populations using scVelo

Quick Start

Run the scVelo workflow on your AnnData object to compute velocity and latent time.

Frequently Asked Questions about alterlab-scvelo

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

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

Infer cell state transitions by analyzing RNA velocity to compare unspliced and spliced mRNA counts, estimating transcriptional dynamics and trajectories from snapshot scRNA-seq data.

What is RNA velocity and how does it estimate latent time in single-cell datasets?▼

RNA velocity compares unspliced and spliced mRNA to estimate transcriptional dynamics, allowing latent time estimation and trajectory inference to map developmental progressions across heterogeneous cell populations.

Do I need spliced and unspliced count layers to run trajectory inference with scVelo?▼

Yes, trajectory inference with scVelo requires an AnnData object containing spliced and unspliced count layers to compute velocity and latent time.

How do I identify driver genes from single-cell RNA-seq velocity metrics?▼

Identify driver genes via velocity-based metrics to pinpoint regulators of cell state transitions, integrating scVelo computations with Scanpy for end-to-end analysis.

Can I visualize latent time estimations on UMAP embeddings using Scanpy?▼

Yes, latent time estimation and downstream visualization on embeddings like UMAP are supported by integrating scVelo results with Scanpy for rich end-to-end analysis.

What are the limitations of trajectory inference from splicing kinetics in scRNA-seq?▼

Trajectory inference from splicing kinetics depends on accurate unspliced and spliced mRNA quantification, limiting reliability when single-cell RNA-seq data lacks these distinct count layers.

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