4.8 Article

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

期刊

NATURE METHODS
卷 14, 期 9, 页码 873-+

出版社

NATURE PUBLISHING GROUP
DOI: 10.1038/NMETH.4391

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资金

  1. Bodenmiller lab
  2. Swiss National Science Foundation (SNSF) R'Equip grant [316030-139220]
  3. SNSF Assistant Professorship grant [PP00P3-144874]
  4. Swiss Cancer League grant
  5. PhosphonetPPM grant
  6. MetastasiX SystemsX grant
  7. European Research Council (ERC) under the European Union [336921]
  8. Forschungskredit of the University of Zurich [FK-74419-01-01]
  9. University of Zurich [BIOEF-17-001]
  10. European Molecular Biology Organization (EMBO) Long Term Fellowships - European Commission [ALTF-711 2015, ALTF-970 2014]
  11. Transition Postdoc Fellowship from the Swiss SystemsX.ch initiative ref. [2015/344]
  12. Swiss National Science Foundation (SNF) [316030_139220, PP00P3_144874] Funding Source: Swiss National Science Foundation (SNF)
  13. European Research Council (ERC) [336921] Funding Source: European Research Council (ERC)

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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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