Single-trajectory analysis

What problem does it solves? Inferring and visualizing developmental trajectories from single-cell data is crucial for understanding cell differentiation, but it involves complex algorithms like PAGA, Palantir, and RNA velocity. This Skill provides a comprehensive guide to these trajectory analysis workflows, simplifying the process of uncovering cellular fate.

Core Features & Use Cases

• Graph-Based Trajectory Inference: Infer cell lineage trajectories using PAGA, Palantir, and VIA.
• RNA Velocity Coupling: Integrate RNA velocity to refine lineage directionality and pseudotime.
• Fate Scoring: Quantify differentiation potential, branch probabilities, and fate bias.
• Downstream Analysis: Integrate CytoTRACE differentiation potential and aggregate metacell trajectories for robustness.
• Use Case: Analyze a single-cell dataset of T-cell development, infer trajectories using VIA, integrate RNA velocity for directional insights, and then quantify the differentiation potential of different T-cell subsets.

Quick Start

Perform trajectory analysis on my single-cell data using VIA, integrate RNA velocity, and visualize the pseudotime and lineage paths.