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

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 visualization of pixel- and cell-level information obtained by multiplexed imaging. To illustrate its utility, we a...

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Detalles Bibliográficos
Autores principales: Eling, Nils, Damond, Nicolas, Hoch, Tobias, Bodenmiller, Bernd
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8023672/
https://www.ncbi.nlm.nih.gov/pubmed/33367748
http://dx.doi.org/10.1093/bioinformatics/btaa1061
Descripción
Sumario: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 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 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.