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rna-velocity-trajectory

Infer directional cellular trajectories from scRNA-seq using spliced and unspliced RNA ratios.

1|Updated Nov 20, 2025
Search Tags:#scRNA-seq#scvelo#rna-velocity#trajectory-inference#velocyto#cellrank#chronocell
One-click install
npx skills add https://github.com/tony-zhelonkin/SciAgent-toolkit --skill rna-velocity-trajectory
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: rna-velocity-trajectory
Source: https://github.com/tony-zhelonkin/SciAgent-toolkit/tree/main/skills/rna-velocity-trajectory
Command: npx skills add https://github.com/tony-zhelonkin/SciAgent-toolkit --skill rna-velocity-trajectory

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Infers directional cellular trajectories from scRNA-seq by modeling spliced/unspliced RNA to predict future cell states and map lineage relationships.

Core Features & Use Cases

  • RNA velocity modeling with scVelo (steady-state and dynamical) to infer developmental trajectories.
  • Uncertainty-aware inference via VeloVI and explicit topology modeling with Chronocell.
  • CellRank integration for fate probabilities and terminal states, enabling robust lineage analysis.
  • Supports upstream quantification of spliced/unspliced transcripts with velocyto, kb lamanno, or alevin-fry, and loading into AnnData layers.
  • Use cases include predicting differentiation endpoints, identifying driver genes, validating lineage relationships, and analyzing transient populations.

Quick Start

Run a complete RNA velocity workflow on your scRNA-seq data to infer future cell states.

Frequently Asked Questions about rna-velocity-trajectory

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

FAQPage Schema
How do I infer cellular trajectories from scRNA-seq data?▼

To infer cellular trajectories from scRNA-seq, you model the ratio of unspliced to spliced RNA to predict future cell states and map lineage relationships across developmental or disease contexts.

Do I need intron-aware quantification for RNA velocity analysis?▼

Yes, RNA velocity analysis requires intron-aware quantification using tools like velocyto, kb lamanno, or alevin-fry USA mode to generate compatible AnnData objects with spliced and unspliced layers.

Can I use CellRank to calculate fate probabilities from scVelo results?▼

Yes, you can integrate CellRank with scVelo results to calculate fate probabilities and identify terminal states, enabling robust lineage analysis and validating directional cellular trajectories.

What's the best way to model uncertainty in RNA velocity inference?▼

For uncertainty-aware RNA velocity inference, you can use VeloVI or model explicit cellular topology with Chronocell to map lineage relationships and predict differentiation endpoints.

Does this RNA velocity workflow support dynamical modeling?▼

Yes, this RNA velocity workflow supports dynamical modeling via scVelo, allowing you to infer developmental trajectories by moving beyond steady-state assumptions to predict future cell states.

Why are my spliced and unspliced RNA layers not working for trajectory inference?▼

RNA velocity trajectory inference fails if AnnData objects lack properly formatted spliced and unspliced layers generated from intron-aware quantification tools like velocyto or alevin-fry.

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