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

Nils Eling | Zendy; Nicolas Damond | Zendy; Tobias Hoch | Zendy; Bernd Bodenmiller | Zendy

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

Author(s) -

Nils Eling,

Nicolas Damond,

Tobias Hoch,

Bernd Bodenmiller

Publication year - 2020

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btaa1061

Subject(s) - bioconductor , visualization , computer science , multiplexing , source code , r package , mass cytometry , pixel , profiling (computer programming) , computer graphics (images) , data mining , artificial intelligence , computational science , programming language , biology , telecommunications , biochemistry , gene , phenotype

Highly multiplexed imaging technologies enable spatial profiling of dozens of biomarkers in situ. Here, we describe cytomapper, a computational tool written in R, that enables visualization of pixel- and cell-level information obtained by multiplexed imaging. To illustrate its utility, we analysed 100 images obtained by imaging mass cytometry from a cohort of type 1 diabetes patients. In addition, cytomapper includes a Shiny application that allows hierarchical gating of cells based on marker expression and visualization of selected cells in corresponding images.

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