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.
We would like to thank the Bodenmiller lab for support and fruitful discussions. Thank you to open-source softwares like “cyt”, “CellProfiler,” and many others. This work was supported by the Swiss National Science Foundation (SNSF) R'Equip grant 316030-139220, an SNSF Assistant Professorship grant PP00P3-144874, a Swiss Cancer League grant, the PhosphonetPPM and MetastasiX SystemsX grants, and funding from the European Research Council (ERC) under the European Union′s Seventh Framework Programme (FP/2007-2013)/ERC Grant Agreement no. 336921. D. Schapiro was supported by the Forschungskredit of the University of Zurich, grant FK-74419-01-01, and the BioEntrepreneur-Fellowship of the University of Zurich, reference no. BIOEF-17-001. H.W.J. and D. Schulz are supported by European Molecular Biology Organization (EMBO) Long Term Fellowships cofunded by the European Commission (LTFCOFUND2013 and 2014), grants ALTF-711 2015 and ALTF-970 2014, respectively. H.W.J. was also supported by a Transition Postdoc Fellowship from the Swiss SystemsX.ch initiative ref. 2015/344, evaluated by the Swiss National Science Foundation.