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histoCAT: analysis of cell phenotypes and interactions in multiplex image cytometry data
Denis Schapiro1,2, Hartland W Jackson1, Swetha Raghuraman1
1Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland.
Abstract:
Single-cell, spatially resolved omics analysis of tissues is poised to transform biomedical research and clinical practice. We have developed an open-source, computational histology topography cytometry analysis toolbox (histoCAT) to enable interactive, quantitative, and comprehensive exploration of individual cell phenotypes, cell-cell interactions, microenvironments, and morphological structures within intact tissues. We highlight the unique abilities of histoCAT through analysis of highly multiplexed mass cytometry images of human breast cancer tissues.
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