多路复用
质量细胞仪
细胞仪
流式细胞术
表型
计算生物学
细胞
生物
生物信息学
分子生物学
遗传学
基因
作者
Denis Schapiro,Hartland W. Jackson,Swetha Raghuraman,Jana Fischer,Vito Riccardo Tomaso Zanotelli,Daniel Schulz,Charlotte Giesen,Raúl Catena,Zsuzsanna Varga,Bernd Bodenmiller
出处
期刊:Nature Methods
[Nature Portfolio]
日期:2017-08-07
卷期号:14 (9): 873-876
被引量:577
摘要
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.
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