Schapiro Denis, Jackson Hartland W, Raghuraman Swetha, Fischer Jana R, Zanotelli Vito R T, Schulz Daniel, Giesen Charlotte, Catena Raúl, Varga Zsuzsanna, Bodenmiller Bernd
Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland.
Life Science Zurich Graduate School, ETH Zurich and University of Zurich, Zurich, Switzerland.
Nat Methods. 2017 Sep;14(9):873-876. doi: 10.1038/nmeth.4391. Epub 2017 Aug 7.
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.
组织的单细胞、空间分辨组学分析有望改变生物医学研究和临床实践。我们开发了一个开源的计算组织学地形细胞术分析工具箱(histoCAT),以实现对完整组织内单个细胞表型、细胞间相互作用、微环境和形态结构的交互式、定量和全面探索。我们通过分析人类乳腺癌组织的高度多重质谱流式细胞术图像,突出了histoCAT的独特能力。