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The curvHDR method for gating flow cytometry samples |
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| Authors: | Ulrike Naumann George Luta Matthew P Wand |
| Affiliation: | (1) School of Mathematics and Statistics, The University of New South Wales, Sydney, 2052, Australia;(2) Department of Biostatistics, Bioinformatics, and Biomathematics, Georgetown University Medical Center, Washington, DC 20057-1484, USA;(3) School of Mathematics and Applied Statistics, University of Wollongong, Wollongong, 2522, Australia |
| Abstract: | BackgroundHigh-throughput flow cytometry experiments produce hundreds of large multivariate samples of cellular characteristics. These samples require specialized processing to obtain clinically meaningful measurements. A major component of this processing is a form of cell subsetting known as gating. Manual gating is time-consuming and subjective. Good automatic and semi-automatic gating algorithms are very beneficial to high-throughput flow cytometry. |
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