FlowSOM: Using self-organizing maps for visualization and interpretation of cytometry data
Author:
Affiliation:
1. Department of Information Technology; Ghent University, iMinds; Ghent Belgium
2. Inflammation Research Center, VIB; Ghent Belgium
3. Department of Respiratory Medicine; Ghent University Hospital; Ghent Belgium
Funder
Agency for Innovation by Science and Technology (IWT); Ghent University Multidisciplinary Research Partnership Bioinformatics
Publisher
Wiley
Subject
Cell Biology,Histology,Pathology and Forensic Medicine
Reference18 articles.
1. Visne enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia;Amir;Nat Biotechnol,2013
2. Extracting a cellular hierarchy from high-dimensional cytometry data with spade;Qiu;Nat Biotechnol,2011
3. Automated gating of flow cytometry data via robust model-based clustering;Lo;Cytometry A,2008
4. Automated high-dimensional flow cytometric data analysis;Pyne;Proc Natl Acad Sci USA,2009
5. FlowClust: A bioconductor package for automated gating of flow cytometry data;Lo;BMC Bioinform,2009
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