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

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

来源：Nature Methods, 2017, 14(9): 873-+.

DOI：10.1038/NMETH.4391

• MASS CYTOMETRY
• RESOLUTION
• IMMUNE
• CANCER

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.

• 出版日期2017-9