# Interactive analysis of single-cell trajectories in 3D space with Cell Journey

## TL;DR

Cell Journey is a 3D visualization tool for analyzing RNA velocity trajectories in single-cell data, enabling better understanding of complex cellular transitions.

## Contribution

Introduces Cell Journey, an interactive 3D platform for visualizing RNA velocity trajectories in single-cell datasets.

## Key findings

- Cell Journey supports both unimodal and multimodal data with multiple input formats and extensive customization.
- The platform uses Euler integration or Runge–Kutta methods to compute RNA velocity vector fields on 3D grids.
- Interactive visual elements like streamlines and volumetric plots allow dynamic exploration of cellular dynamics.

## Abstract

The integration of high-throughput single-cell profiling technologies with RNA velocity analysis has enabled the reconstruction of dynamic cellular differentiation trajectories at unprecedented resolution. Despite these advances, current visualization techniques for RNA velocity are predominantly confined to 2-dimensional representations, typically employing arrows or streamlines. While effective for depicting simple cellular trajectories, these approaches are insufficient for capturing the complex topologies of multipartite cellular transitions. This limitation highlights the need for advanced 3-dimensional visualization tools that can more accurately convey the structure and dynamics of velocity-inferred transitions in single-cell data. Here, we present Cell Journey, an interactive visualization platform specifically developed for 3-dimensional analysis and representation of RNA velocity trajectories derived from single-cell datasets. The platform features an intuitive graphical interface supporting both unimodal and multimodal data, accommodates multiple input formats, and provides extensive customization capabilities for trajectory visualization. Cell Journey computes RNA velocity vector fields on a user-defined 3-dimensional grid and constructs velocity trajectories using either Euler integration or the fourth-order Runge–Kutta method. The platform enables dynamic exploration of cellular dynamics through interactive visual elements, including streamlines, streamlets, cones, and volumetric plots. Furthermore, it allows users to investigate changes in feature activity along selected paths, facilitating deeper insights into cellular state transitions within complex multimodal single-cell datasets.