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

Schapiro, Denis; Jackson, Hartland W; Raghuraman, Swetha; Fischer, Jana R; Zanotelli, Vito R T; Schulz, Daniel; Giesen, Charlotte; Catena, Raúl; Varga, Zsuzsanna; Bodenmiller, Bernd.

Afiliación

Schapiro D; Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland.
Jackson HW; Life Science Zurich Graduate School, ETH Zurich and University of Zurich, Zurich, Switzerland.
Raghuraman S; Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland.
Fischer JR; Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland.
Zanotelli VRT; Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland.
Schulz D; Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland.
Giesen C; Life Science Zurich Graduate School, ETH Zurich and University of Zurich, Zurich, Switzerland.
Catena R; Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland.
Varga Z; Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland.
Bodenmiller B; Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland.

Nat Methods ; 14(9): 873-876, 2017 Sep.

Article en En | MEDLINE | ID: mdl-28783155

ABSTRACT

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.

Asunto(s)

Comunicación Celular/fisiología; Citometría de Flujo/métodos; Imagen Molecular/métodos; Proteoma/metabolismo; Programas Informáticos; Análisis de Matrices Tisulares/métodos; Algoritmos; Interpretación de Imagen Asistida por Computador/métodos; Interfaz Usuario-Computador

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Programas Informáticos / Comunicación Celular / Proteoma / Análisis de Matrices Tisulares / Imagen Molecular / Citometría de Flujo Idioma: En Revista: Nat Methods Asunto de la revista: TECNICAS E PROCEDIMENTOS DE LABORATORIO Año: 2017 Tipo del documento: Article País de afiliación: Suiza

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