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histoCAT: analysis of cell phenotypes and interactions in multiplex image cytometry data
Open accessPublished version of a preprint
Abstract
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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Cites
Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq
Tirosh, I., Izar, B., Prakadan, S. M., Wadsworth, M. H., Treacy, D., Trombetta, J. J., Rotem, A., Rodman, C., Lian, C., Murphy, G., et al. (2016) · Science · doi:10.1126/science.aad0501 · Cited by 4,944
Tissue microarrays for high-throughput molecular profiling of tumor specimens
Kononen, J., Bubendorf, L., Kallionimeni, A., Bärlund, M., Schraml, P., Leighton, S., Torhorst, J., Mihatsch, M. J., Sauter, G., & Kallionimeni, O.-P. (1998) · Nature Medicine · doi:10.1038/nm0798-844 · Cited by 4,099
Spatially resolved, highly multiplexed RNA profiling in single cells
Chen, K. H., Boettiger, A. N., Moffitt, J. R., Wang, S., & Zhuang, X. (2015) · Science · doi:10.1126/science.aaa6090 · Cited by 2,969
Data-Driven Phenotypic Dissection of AML Reveals Progenitor-like Cells that Correlate with Prognosis
Levine, J. H., Simonds, E. F., Bendall, S. C., Davis, K. L., Amir, E.-A. D., Tadmor, M. D., Litvin, O., Fienberg, H. G., Jager, A., Zunder, E. R., et al. (2015) · Cell · doi:10.1016/j.cell.2015.05.047 · Cited by 2,303
Bendall, S. C., Simonds, E. F., Qiu, P., Amir, E.-A. D., Krutzik, P. O., Finck, R., Bruggner, R. V., Melamed, R., Trejo, A., Ornatsky, O. I., et al. (2011) · Science · doi:10.1126/science.1198704 · Cited by 2,279
Highly multiplexed imaging of tumor tissues with subcellular resolution by mass cytometry
Giesen, C., Wang, H. A. O., Schapiro, D., Zivanovic, N., Jacobs, A., Hattendorf, B., Schüffler, P. J., Grolimund, D., Buhmann, J. M., Brandt, S., et al. (2014) · Nature Methods · doi:10.1038/nmeth.2869 · Cited by 1,951
Self-citationAmir, E.-A. D., Davis, K. L., Tadmor, M. D., Simonds, E. F., Levine, J. H., Bendall, S. C., Shenfeld, D. K., Krishnaswamy, S., Nolan, G. P., & Pe'er, D. (2013) · Nature Biotechnology · doi:10.1038/nbt.2594 · Cited by 1,550
Ilastik: Interactive learning and segmentation toolkit
Sommer, C., Straehle, C., Kothe, U., & Hamprecht, F. A. (2011) · 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro · doi:10.1109/isbi.2011.5872394 · Cited by 1,125
Multiplexed ion beam imaging of human breast tumors
Angelo, M., Bendall, S. C., Finck, R., Hale, M. B., Hitzman, C., Borowsky, A. D., Levenson, R. M., Lowe, J. B., Liu, S. D., Zhao, S., et al. (2014) · Nature Medicine · doi:10.1038/nm.3488 · Cited by 1,108
Highly Multiplexed Subcellular RNA Sequencing in Situ
Lee, J. H., Daugharthy, E. R., Scheiman, J., Kalhor, R., Yang, J. L., Ferrante, T. C., Terry, R., Jeanty, S. S. F., Li, C., Amamoto, R., et al. (2014) · Science · doi:10.1126/science.1250212 · Cited by 973
Systematic Analysis of Breast Cancer Morphology Uncovers Stromal Features Associated with Survival
Beck, A. H., Sangoi, A. R., Leung, S., Marinelli, R. J., Nielsen, T. O., van de Vijver, M. J., West, R. B., van de Rijn, M., & Koller, D. (2011) · Science Translational Medicine · doi:10.1126/scitranslmed.3002564 · Cited by 763
Highly multiplexed single-cell analysis of formalin-fixed, paraffin-embedded cancer tissue
Gerdes, M. J., Sevinsky, C. J., Sood, A., Adak, S., Bello, M. O., Bordwell, A., Can, A., Corwin, A., Dinn, S., Filkins, R. J., et al. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1300136110 · Cited by 724
Macrophages and cancer: from mechanisms to therapeutic implications
Ostuni, R., Kratochvill, F., Murray, P. J., & Natoli, G. (2015) · Trends in Immunology · doi:10.1016/j.it.2015.02.004 · Cited by 683
Tumorigenesis: it takes a village
Tabassum, D. P., & Polyak, K. (2015) · Nature Reviews Cancer · doi:10.1038/nrc3971 · Cited by 564
Highly multiplexed imaging of single cells using a high-throughput cyclic immunofluorescence method
Lin, J.-R., Fallahi-Sichani, M., & Sorger, P. K. (2015) · Nature Communications · doi:10.1038/ncomms9390 · Cited by 562
Multiplexed mass cytometry profiling of cellular states perturbed by small-molecule regulators
Bodenmiller, B., Zunder, E. R., Finck, R., Chen, T. J., Savig, E. S., Bruggner, R. V., Simonds, E. F., Bendall, S. C., Sachs, K., Krutzik, P. O., et al. (2012) · Nature Biotechnology · doi:10.1038/nbt.2317 · Cited by 546
Self-citationCellProfiler Analyst: data exploration and analysis software for complex image-based screens
Jones, T. R., Kang, I. H., Wheeler, D. B., Lindquist, R. A., Papallo, A., Sabatini, D. M., Golland, P., & Carpenter, A. E. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-482 · Cited by 541
Analyzing proteome topology and function by automated multidimensional fluorescence microscopy
Schubert, W., Bonnekoh, B., Pommer, A. J., Philipsen, L., Böckelmann, R., Malykh, Y., Gollnick, H., Friedenberger, M., Bode, M., & Dress, A. W. M. (2006) · Nature Biotechnology · doi:10.1038/nbt1250 · Cited by 479
Social network architecture of human immune cells unveiled by quantitative proteomics
Rieckmann, J. C., Geiger, R., Hornburg, D., Wolf, T., Kveler, K., Jarrossay, D., Sallusto, F., Shen-Orr, S. S., Lanzavecchia, A., Mann, M., et al. (2017) · Nature Immunology · doi:10.1038/ni.3693 · Cited by 385
Comparison of clustering methods for high‐dimensional single‐cell flow and mass cytometry data
Weber, L. M., & Robinson, M. D. (2016) · Cytometry Part A · doi:10.1002/cyto.a.23030 · Cited by 378
Multiplexed Epitope-Based Tissue Imaging for Discovery and Healthcare Applications
Bodenmiller, B. (2016) · Cell Systems · doi:10.1016/j.cels.2016.03.008 · Cited by 230
Self-citationWang, H. A. O., Grolimund, D., Giesen, C., Borca, C. N., Stewart, J., Bodenmiller, B., & Günther, D. (2013) · Analytical Chemistry · doi:10.1021/ac400996x · Cited by 216
Self-citationAutomatic Classification of Cellular Expression by Nonlinear Stochastic Embedding (ACCENSE)
Shekhar, K., Brodin, P., Davis, M. M., & Chakraborty, A. K. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1321405111 · Cited by 215
AirLab: a cloud-based platform to manage and share antibody-based single-cell research
Catena, R., Özcan, A., Jacobs, A., Chevrier, S., & Bodenmiller, B. (2016) · Genome biology · doi:10.1186/s13059-016-1006-0 · Cited by 25
Self-citationGRAPHIE: graph based histology image explorer
Ding, H., Wang, C., Huang, K., & Machiraju, R. (2015) · BMC Bioinformatics · doi:10.1186/1471-2105-16-s11-s10 · Cited by 10
Research works printed but not linked: 1
- Schüffler, P.J. et al. Cytometry A 87, 936–942 (2015). · doi:10.1002/cyto.a.22702
Cited by
Data-efficient and weakly supervised computational pathology on whole-slide images
Lu, M. Y., Williamson, D. F. K., Chen, T. Y., Chen, R. J., Barbieri, M., & Mahmood, F. (2021) · Nature Biomedical Engineering · doi:10.1038/s41551-020-00682-w · Cited by 2,282
Eleven grand challenges in single-cell data science
Lähnemann, D., Köster, J., Szczurek, E., McCarthy, D. J., Hicks, S. C., Robinson, M. D., Vallejos, C. A., Campbell, K. R., Beerenwinkel, N., Mahfouz, A., et al. (2020) · Genome Biology · doi:10.1186/s13059-020-1926-6 · Cited by 1,327
Deciphering cell–cell interactions and communication from gene expression
Armingol, E., Officer, A., Harismendy, O., & Lewis, N. E. (2021) · Nature Reviews Genetics · doi:10.1038/s41576-020-00292-x · Cited by 1,267
Giotto: a toolbox for integrative analysis and visualization of spatial expression data
Dries, R., Zhu, Q., Dong, R., Eng, C.-H. L., Li, H., Liu, K., Fu, Y., Zhao, T., Sarkar, A., Bao, F., et al. (2021) · Genome Biology · doi:10.1186/s13059-021-02286-2 · Cited by 917
Pan-cancer integrative histology-genomic analysis via multimodal deep learning
Chen, R. J., Lu, M. Y., Williamson, D. F. K., Chen, T. Y., Lipkova, J., Noor, Z., Shaban, M., Shady, M., Williams, M., Joo, B., et al. (2022) · Cancer Cell · doi:10.1016/j.ccell.2022.07.004 · Cited by 660
Metadata
- Authors
- Schapiro, D., Jackson, H. W., Raghuraman, S., Fischer, J. R., Zanotelli, V. R. T., Schulz, D., Giesen, C., Catena, R., Varga, Z., & Bodenmiller, B.
- Venue
- Nature Methods
- Published
- 2017-08-07
- Volume
- 14
- Issue
- 9
- Pages
- 873-876
- ISSN
- 1548-7091 (ISSN-L)
- 1548-7105
- OpenAlex
- W2743344672
- Cited by
- 659
- References
- 25
- FWCI
- 11.55
- Type
- journal article
- Language
- en
- Open access
- green
- Licence
- www.springer.com/tdm (tdm)
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