miCAT: A toolbox for analysis of cell phenotypes and interactions in multiplex image cytometry data
By D. Schapiro, H. Jackson, Swetha Raghuraman, Jana R Fischer, Vito R. T. Zanotelli, D. Schulz, Charlotte Giesen, R. Catena, Z. Varga, Bernd Bodenmiller. Nature Methods, 2017
413 citations recorded by the source corpus.
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.
Subfields: Biophysics, Molecular Biology, Oncology
View Paper: https://www.semanticscholar.org/paper/632ba989be404f1a3d76498585bccff9f3c3aa97
How researchers see this paper
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In Biophysics
In Molecular Biology
- Fabian J Theis
- Aviv Regev
- Giovanni Palla
- David S. Fischer
- Adam Officer
- Erick Armingol
- Olivier Harismendy
- Nathan E. Lewis
Citations in the corpus
- Coordinated Cellular Neighborhoods Orchestrate Antitumoral Immunity at the Colorectal Cancer Invasive Front (2019, neutral): “behavior or pairwise cell-cell contacts (Schapiro et al., 2017; Zhu et al., 2018).”
- Robust mapping of spatiotemporal trajectories and cell–cell interactions in healthy and diseased tissues (2023, positive): “(15): The LR score can be further adjusted to include cell type diversity, which is often positively correlated with increased likelihood of cell – cell interactions 13,23,74 .”
- Deciphering cell–cell interactions and communication from gene expression (2020, background): “As more approaches emerge for spatial-based transcriptomics 99–104 and proteomics 133,134 , future studies and algorithms should include this information.”
- Spatial components of molecular tissue biology (2022, positive): “Few methods have been proposed that aim to estimate cell-type neighborhood enrichments in spatial context 59,106,175 , and inferring cell interaction and signaling genes from spatial graph structure 33,41,58,59,106,172,176 .”