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omicverse-single-cell-sctour-trajectory

Run OmicVerse scTour trajectory inference on raw-count AnnData to produce pseudotime, latent space, and vector-field outputs.

13|2|Updated Apr 5, 2026
Search Tags:#trajectory#pseudotime#omicverse#anndata#sctour#vector-field
One-click install
npx skills add https://github.com/omicverse/omicverse-skills --skill omicverse-single-cell-sctour-trajectory-omicverse
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: omicverse-single-cell-sctour-trajectory
Source: https://github.com/omicverse/omicverse-skills/tree/main/src/omicverse_skills/skills/single-cell-sctour-trajectory
Command: npx skills add https://github.com/omicverse/omicverse-skills --skill omicverse-single-cell-sctour-trajectory-omicverse

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) and assets (resource) components.

What problem does it solve?

This Skill turns the OmicVerse scTour trajectory branch into a reusable workflow for single-cell analysis, so you can generate pseudotime, latent embeddings, and vector-field results without manually reconstructing the notebook logic.

Core Features & Use Cases

  • scTour Branch Execution: Runs the specialized sctour path of OmicVerse trajectory inference on AnnData inputs.
  • Raw-Count Preservation: Validates that raw UMI counts remain in .X so the negative-binomial training path stays consistent.
  • Result Capture and Plotting: Records sctour_pseudotime, X_TNODE, and X_VF, then supports trajectory and branch-style visualizations.
  • Notebook-to-Skill Conversion: Useful when converting an OmicVerse trajectory notebook into a repeatable skill for latent dynamics analysis.
  • Dependency-Aware Guidance: Separates this branch from diffusion_map, slingshot, and palantir when the requested output is scTour-specific.

Quick Start

Ask the agent to run the OmicVerse scTour trajectory branch on your raw-count AnnData and return the pseudotime, latent space, and vector-field outputs.

Frequently Asked Questions about omicverse-single-cell-sctour-trajectory

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

FAQPage Schema
How do I run scTour trajectory inference on raw-count AnnData?▼

Run scTour trajectory inference by passing a raw-count AnnData object with UMI counts stored in the .X layer, which ensures the negative-binomial training path remains consistent for pseudotime and vector-field generation.

What is scTour pseudotime analysis used for in single-cell RNA-seq?▼

scTour pseudotime analysis reconstructs continuous single-cell developmental trajectories by computing latent dynamics and vector-fields from raw UMI counts, enabling branch-specific trajectory inference and latent space visualization.

Does scTour require raw UMI counts in the AnnData .X layer?▼

Yes, scTour requires raw UMI counts in the AnnData .X layer to maintain consistency in the negative-binomial training path used for trajectory inference and latent space generation.

When should I use scTour instead of diffusion map or slingshot for trajectory analysis?▼

Use scTour instead of diffusion map, slingshot, or palantir when your analysis specifically requires sctour_pseudotime, X_TNODE latent embeddings, and X_VF vector-field outputs for latent dynamics modeling.

How do I validate scTour trajectory outputs like sctour_pseudotime and X_VF?▼

Validate scTour trajectory outputs by checking the AnnData object for correctly populated sctour_pseudotime, X_TNODE, and X_VF fields after the model finishes training.

Do I need to install the external sctour package to run OmicVerse trajectory analysis?▼

Yes, the external sctour package is required, as this Skill separates the scTour branch from other trajectory methods and relies on that dependency to produce pseudotime and vector-field results.

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