ShapoGraphy: A User-Friendly Web Application for Creating Bespoke and Intuitive Visualisation of Biomedical Data

Area of Science:

• Bioimage analysis
• Quantitative microscopy
• Data visualization

Background:

• Effective visualization of quantitative microscopy data is essential for pattern discovery in complex bioimage datasets.
• Traditional visualization methods like bar charts and scatter plots are insufficient for the complexity of microscopy data.

Purpose of the Study:

• To develop ShapoGraphy, a novel method and web-based application for creating customizable quantitative pictorial representations of image datasets.
• To facilitate a deeper understanding and analysis of complex bioimage data.

Main Methods:

• ShapoGraphy allows users to represent structures of interest as sets of shapes.
• Variables are encoded by mapping them to shape dimensions, colors, symbols, or outlines.
• The method is demonstrated using diverse image data, including high-dimensional multiplexed data.

Main Results:

• ShapoGraphy enables a more comprehensive understanding of cellular phenotypes.
• Improved insights into the relationships between different variables within the data were achieved.
• The visualization method proved effective across various image data types.

Conclusions:

• ShapoGraphy provides a powerful tool for scientific discovery and communication.
• It offers a rich vocabulary for creating engaging and intuitive representations of diverse data.
• This approach enhances the interpretation of complex quantitative microscopy data.