The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
FlowSOM: Using self‐organizing maps for visualization and interpretation of cytometry data
Abstract
The number of markers measured in both flow and mass cytometry keeps increasing steadily. Although this provides a wealth of information, it becomes infeasible to analyze these datasets manually. When using 2D scatter plots, the number of possible plots increases exponentially with the number of markers and therefore, relevant information that is present in the data might be missed. In this article, we introduce a new visualization technique, called FlowSOM, which analyzes Flow or mass cytometry data using a Self‐Organizing Map. Using a two‐level clustering and star charts, our algorithm helps to obtain a clear overview of how all markers are behaving on all cells, and to detect subsets that might be missed otherwise. R code is available at https://github.com/SofieVG/FlowSOM and will be made available at Bioconductor. © 2015 International Society for Advancement of Cytometry
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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
Amir, 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
Extracting a cellular hierarchy from high-dimensional cytometry data with SPADE
Qiu, P., Simonds, E. F., Bendall, S. C., Gibbs, K. D., Bruggner, R. V., Linderman, M. D., Sachs, K., Nolan, G. P., & Plevritis, S. K. (2011) · Nature Biotechnology · doi:10.1038/nbt.1991 · Cited by 956
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“REAGENT or RESOURCE SOURCE IDENTIFIER Recombinant DNA pLentiguide Rubin et al., 2019 Addgene: 117986 pLex_Cas9 Rubin et al., 2019 Addgene: 117987 Software and Algorithms Cell Ranger versions 2.1/3.0 10X Genomics https://www.10xgenomics.com/; RRID:SCR_017344 ST Pipeline version 1.7.2 Navarro et al., 2017 https://github…”
BackgroundMethodInfluentialKeren, L., Bosse, M., Marquez, D., Angoshtari, R., Jain, S., Varma, S., Yang, S.-R., Kurian, A., Van Valen, D., West, R., et al. (2018) · Cell · doi:10.1016/j.cell.2018.08.039 · Cited by 1,183
Mrdjen, D., Pavlovic, A., Hartmann, F. J., Schreiner, B., Utz, S. G., Leung, B. P., Lelios, I., Heppner, F. L., Kipnis, J., Merkler, D., et al. (2018) · Immunity · doi:10.1016/j.immuni.2018.01.011 · Cited by 1,010
Metadata
- Authors
- Van Gassen, S., Callebaut, B., Van Helden, M. J., Lambrecht, B. N., Demeester, P., Dhaene, T., & Saeys, Y.
- Venue
- Cytometry Part A
- Publisher
- Wiley
- Published
- 2015-01-08
- Volume
- 87
- Issue
- 7
- Pages
- 636-645
- ISSN
- 1552-4922 (ISSN-L)
- 1552-4930
- OpenAlex
- W1993835819
- Cited by
- 1,919
- References
- 3
- FWCI
- 12.09
- Type
- journal article
- Language
- en
- Open access
- closed
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- Van Gassen, S., Callebaut, B., Van Helden, M. J., Lambrecht, B. N., Demeester, P., Dhaene, T., & Saeys, Y. (2015). FlowSOM: Using self‐organizing maps for visualization and interpretation of cytometry data. Cytometry Part A. https://doi.org/10.1002/cyto.a.22625
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