cytoviewer: an R/Bioconductor package for interactive visualization and exploration of highly multiplexed imaging...

Area of Science:

• Computational Biology
• Bioinformatics
• Data Visualization

Background:

• Highly multiplexed imaging allows for single-cell detection of multiple biological molecules within tissue context.
• Interactive visualization is essential for quality control and spatial exploration of single-cell features in complex imaging datasets.
• Existing tools for interactive visualization of multiplexed imaging data are lacking in the R statistical programming environment.

Purpose of the Study:

• To introduce cytoviewer, an R/Bioconductor package designed for interactive visualization and exploration of multi-channel images and segmentation masks.
• To provide R users with a tool that facilitates quality control, spatial exploration, and validation of hypotheses in highly multiplexed imaging data analysis.

Main Methods:

• Development of the cytoviewer R/Bioconductor package.
• Implementation of features for flexible generation of image composites and side-by-side visualization of single channels.
• Integration with standard Bioconductor data classes for seamless compatibility with existing single-cell and image analysis workflows.

Main Results:

• cytoviewer enables interactive visualization and exploration of multi-channel images and segmentation masks.
• The package supports flexible image compositing, single-channel visualization, and spatial visualization of single-cell data.
• cytoviewer enhances quality control for images and segmentation, aids in cell phenotyping visualization, and supports hypothesis validation.

Conclusions:

• The cytoviewer package provides comprehensive features for visualizing highly multiplexed imaging data in R.
• It integrates smoothly into existing image and single-cell data analysis workflows.
• cytoviewer is available via Bioconductor and GitHub, with instructions for installation and use.