histoCAT: analysis of cell phenotypes and interactions in multiplex image cytometry data.
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.
Keywords
Spatial Omics
IMC
MeSH terms
Algorithms
Cell Communication
Flow Cytometry
Image Interpretation, Computer-Assisted
Molecular Imaging
Proteome
Software
Tissue Array Analysis
User-Computer Interface
Authors
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