Spatial analysis for highly multiplexed imaging data to identify tissue microenvironments

Highly multiplexed in situ imaging cytometry assays have made it possible to study the spatial organization of numerous cell types simultaneously. We have addressed the challenge of quantifying complex multi‐cellular relationships by proposing a statistical method which clusters local indicators of...

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Bibliographic Details
Published inCytometry. Part A Vol. 103; no. 7; pp. 593 - 599
Main Authors Patrick, Ellis, Canete, Nicolas P., Iyengar, Sourish S., Harman, Andrew N., Sutherland, Greg T., Yang, Pengyi
Format Journal Article
LanguageEnglish
Published Hoboken, USA John Wiley & Sons, Inc 01.07.2023
Wiley Subscription Services, Inc
Subjects
Cytometry
Image Cytometry
imaging
Microenvironments
Multiplexing
Spatial Analysis
Statistical methods
statistics
R
spatial analysis
imaging
statistics
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Summary:Highly multiplexed in situ imaging cytometry assays have made it possible to study the spatial organization of numerous cell types simultaneously. We have addressed the challenge of quantifying complex multi‐cellular relationships by proposing a statistical method which clusters local indicators of spatial association. Our approach successfully identifies distinct tissue architectures in datasets generated from three state‐of‐the‐art high‐parameter assays demonstrating its value in summarizing the information‐rich data generated from these technologies.
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ISSN:1552-4922
1552-4930
1552-4930
DOI:10.1002/cyto.a.24729