PT  - JOURNAL ARTICLE
AU  - Denis Schapiro
AU  - Hartland Warren Jackson
AU  - Swetha Raghuraman
AU  - Vito R T Zanotelli
AU  - Jana R Fischer
AU  - Daniel Schulz
AU  - Charlotte Giesen
AU  - Raul Catena
AU  - Zsuzsanna Varga
AU  - Bernd Bodenmiller
TI  - Systematic analysis of cell phenotypes and cellular social networks in tissues using the multiplexed image cytometry analysis toolbox (miCAT)
AID  - 10.1101/109207
DP  - 2017 Jan 01
TA  - bioRxiv
PG  - 109207
4099  - http://biorxiv.org/content/early/2017/02/17/109207.short
4100  - http://biorxiv.org/content/early/2017/02/17/109207.full
AB  - Single-cell, spatially resolved ‘omics analysis of tissues is poised to transform biomedical research and clinical practice. We have developed a computational multiplexed image cytometry analysis toolbox (miCAT) to enable the interactive, quantitative, and comprehensive exploration of phenotypes of individual cells, cell-to-cell interactions, microenvironments, and morphological structures within intact tissues. miCAT will be useful in all areas of tissue-based research. We highlight the unique abilities of miCAT by analysis of highly multiplexed mass cytometry images of human breast cancer tissues.