Corvo: Visualizing CellxGene Single-Cell Datasets in Virtual Reality

TL;DR

Corvo is an open-source tool that enhances the visualization and analysis of single-cell datasets by leveraging 3D virtual reality, offering a more intuitive understanding compared to traditional 2D methods.

Contribution

It introduces Corvo, a no-code, VR-based visualization tool for single-cell data that integrates with existing Python data science workflows.

Findings

Enables immersive 3D visualization of single-cell datasets.

Improves data exploration and pattern recognition in single-cell analysis.

Provides a user-friendly, open-source VR tool compatible with current data science tools.

Abstract

The CellxGene project has enabled access to single-cell data in the scientific community, providing tools for browsed-based no-code analysis of more than 500 annotated datasets. However, single-cell data requires dimensional reduction to visualize, and 2D embedding does not take full advantage of three-dimensional human spatial understanding and cognition. Compared to a 2D visualization that could potentially hide gene expression patterns, 3D Virtual Reality may enable researchers to make better use of the information contained within the datasets. For this purpose, we present \emph{Corvo}, a fully free and open-source software tool that takes the visualization and analysis of CellxGene single-cell datasets to 3D Virtual Reality. Similar to CellxGene, Corvo takes a no-code approach for the end user, but also offers multimodal user input to facilitate fast navigation and analysis, and is interoperable with the existing Python data science ecosystem. In this paper, we explain the design goals of Corvo, detail its approach to the Virtual Reality visualization and analysis of single-cell data, and briefly discuss limitations and future extensions.