cytomapper: an R/Bioconductor package for visualization of highly multiplexed imaging data

Area of Science:

• Computational biology
• Biomedical imaging
• Immunology

Background:

• Highly multiplexed imaging technologies allow in situ spatial profiling of numerous biomarkers.
• Imaging mass cytometry generates complex, high-dimensional datasets.

Purpose of the Study:

• To introduce cytomapper, an R package for visualizing and analyzing multiplexed imaging data.
• To demonstrate the utility of cytomapper using imaging mass cytometry data from type 1 diabetes patients.

Main Methods:

• Development of cytomapper, a computational tool in R.
• Utilizing cytomapper for pixel- and cell-level visualization of imaging mass cytometry data.
• Incorporating a Shiny application for hierarchical cell gating and image visualization.

Main Results:

• Cytomapper enables effective visualization of spatial biomarker information.
• Analysis of 100 imaging mass cytometry images from type 1 diabetes patients was performed.
• Hierarchical gating and visualization of specific cell populations were achieved.

Conclusions:

• Cytomapper is a valuable computational tool for spatial profiling using multiplexed imaging.
• The tool facilitates in-depth analysis of complex biological samples, such as those from type 1 diabetes cohorts.