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

Nils Eling1,2, Nicolas Damond1,2, Tobias Hoch1,2

  • 1Department of Quantitative Biomedicine, University of Zurich, 8057 Zurich, Switzerland.

Bioinformatics (Oxford, England)
|December 28, 2020
PubMed
Summary

Cytomapper is a new R tool for visualizing spatial profiling data from multiplexed imaging. It aids in analyzing cell marker expression in type 1 diabetes patients.

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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.