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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; Varga, Zsuzsanna; Bodenmiller, Bernd (2017). histoCAT: analysis of cell phenotypes and interactions in multiplex image cytometry data. Nature Methods:8.

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.

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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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Institute of Pathology and Molecular Pathology
Dewey Decimal Classification:610 Medicine & health
Language:English
Date:7 August 2017
Deposited On:30 Aug 2017 12:39
Last Modified:30 Aug 2017 12:41
Publisher:Nature Publishing Group
ISSN:1548-7091
Publisher DOI:https://doi.org/10.1038/nmeth.4391
PubMed ID:28783155

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