@article {Schapiro109207, author = {Denis Schapiro and Hartland Warren Jackson and Swetha Raghuraman and Vito R T Zanotelli and Jana R Fischer and Daniel Schulz and Charlotte Giesen and Raul Catena and Zsuzsanna Varga and Bernd Bodenmiller}, title = {Systematic analysis of cell phenotypes and cellular social networks in tissues using the multiplexed image cytometry analysis toolbox (miCAT)}, elocation-id = {109207}, year = {2017}, doi = {10.1101/109207}, publisher = {Cold Spring Harbor Laboratory}, abstract = {Single-cell, spatially resolved {\textquoteleft}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.}, URL = {https://www.biorxiv.org/content/early/2017/02/17/109207}, eprint = {https://www.biorxiv.org/content/early/2017/02/17/109207.full.pdf}, journal = {bioRxiv} }