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.Availability and implementationThe cytomapper package can be installed via . Code for analysis and further instructions can be found at .Supplementary informationare available at Bioinformatics online.
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Natl Res Council CNR, Inst Appl Math IAC Mauro Picone, I-00185 Rome, ItalyNatl Res Council CNR, Inst Appl Math IAC Mauro Picone, I-00185 Rome, Italy
Paparozzi, Veronica
Nardini, Christine
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Natl Res Council CNR, Inst Appl Math IAC Mauro Picone, I-00185 Rome, ItalyNatl Res Council CNR, Inst Appl Math IAC Mauro Picone, I-00185 Rome, Italy
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Tampere Univ Technol, Computat Med & Stat Learning Lab, Korkeakoulunkatu 1, FI-33720 Tampere, FinlandUniv Arkansas Med Sci, Dept Biomed Informat, Little Rock, AR 72205 USA
Emmert-Streib, Frank
Glazko, Galina
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Univ Arkansas Med Sci, Dept Biomed Informat, Little Rock, AR 72205 USAUniv Arkansas Med Sci, Dept Biomed Informat, Little Rock, AR 72205 USA