The State of Single-Cell Atlas Data Visualization in the Biological Literature.

Area of Science:

• Single-cell biology
• Bioinformatics
• Data visualization

Background:

• Recent advancements allow single-cell profiling of tissue samples.
• Analysis of single-cell data aids disease understanding and therapeutic development.
• Large-scale 'atlas' projects are cataloging cellular archetypes, biomarkers, and spatial locations.

Purpose of the Study:

• To survey the current usage of visualization techniques for interpreting single-cell atlas datasets.
• To identify challenges and opportunities in visualizing large-scale, high-resolution, and heterogeneous single-cell data.
• To provide a foundational resource for the visualization community addressing emerging atlas-scale datasets.

Main Methods:

• Assessed over 1,800 figure panels from 45 biological publications.
• Analyzed the application of visualization methods in the context of single-cell atlas data interpretation.

Main Results:

• Identified common and novel visualization strategies employed in single-cell atlas research.
• Highlighted the impact of data size, resolution, and heterogeneity on visualization choices.
• Provided insights into how visualization aids the discovery of biological function in health and disease.

Conclusions:

• Visualization is crucial for interpreting complex single-cell atlas data.
• Understanding current visualization practices is essential as atlas-scale datasets rapidly emerge.
• This survey serves as a resource to guide future visualization development for single-cell biology.