histoCAT: analysis of cell phenotypes and interactions in multiplex image cytometry data.

Schapiro, Denis; Jackson, Hartland W; Raghuraman, Swetha; Fischer, Jana R; Zanotelli, Vito R T; Schulz, Daniel; Giesen, Charlotte; Catena, Raúl et al. · Nat Methods · 2017

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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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