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ABSTRACT: Summary
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 visualisation 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 visualisation of selected cells in corresponding images.Availability and implementation
The cytomapper package can be installed via https://www.bioconductor.org/packages/release/bioc/html/cytomapper.html. Code for analysis and further instructions can be found at https://github.com/BodenmillerGroup/cytomapper_publication.Supplementary information
Supplementary data are available at Bioinformatics online.
SUBMITTER: Eling N
PROVIDER: S-EPMC8023672 | biostudies-literature | 2020 Dec
REPOSITORIES: biostudies-literature
Eling Nils N Damond Nicolas N Hoch Tobias T Bodenmiller Bernd B
Bioinformatics (Oxford, England) 20210401 24
<h4>Summary</h4>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 ba ...[more]