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Related Experiment Video

Updated: Sep 4, 2025

Multimodal Optical Imaging Platform for Studying Cellular Metabolism

Multimodal Optical Imaging Platform for Studying Cellular Metabolism

Published on: June 6, 2025

Mistic: An open-source multiplexed image t-SNE viewer.

Sandhya Prabhakaran¹, Chandler Gatenbee¹, Mark Robertson-Tessi¹

¹Department of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA.

Patterns (New York, N.Y.)

|July 18, 2022

Summary

This summary is machine-generated.

Mistic is a new open-source tool for visualizing multiplexed images in cancer research. It aids in understanding tumor microenvironment complexity and identifying specific cellular phenotypes for further analysis.

Keywords:

CODEX CyCIF Mistic NSCLC PerkinElmer Vectra UMAP viewer cancer data analysis data exploration endometrial cancer immune landscape immunotherapy lung cancer multiplexed images t-CyCIF t-SNE viewer visualization

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Area of Science:

Computational biology
Cancer research
Bioinformatics

Background:

Tumor microenvironment complexity is crucial for translational research, particularly in immuno-oncology.
Analyzing multiplexed images from patient samples is vital for understanding tumor ecology.
Existing tools lack the capability for generating image t-SNEs.

Purpose of the Study:

To introduce Mistic, an open-source multiplexed image t-SNE viewer.
To enable simultaneous viewing and analysis of multiple 2D images from patient samples.
To facilitate exploratory analysis of biomarker expression and cellular phenotypes.

Main Methods:

Development of Mistic, an open-source software tool.
Implementation of t-SNE (t-distributed Stochastic Neighbor Embedding) and UMAP (Uniform Manifold Approximation and Projection) for image positioning.
Provision of multiple layout options for visual preview of multiplexed image datasets.

Main Results:

Mistic allows simultaneous viewing of multiple 2D images with flexible layout options.
Image positions can be mapped using t-SNE or UMAP coordinates.
The tool facilitates identification of images with specific phenotypes and biomarker expression patterns.

Conclusions:

Mistic provides a novel, freely available solution for generating image t-SNEs.
The viewer aids in the exploratory analysis of complex multiplexed imaging data.
This tool supports the selection of relevant images for downstream analysis in cancer research.