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2010
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Swift: Scalable weighted iterative sampling for flow cytometry clustering

10 years 1 months ago
Swift: Scalable weighted iterative sampling for flow cytometry clustering
Flow cytometry (FC) is a powerful technology for rapid multivariate analysis and functional discrimination of cells. Current FC platforms generate large, high-dimensional datasets which pose a significant challenge for traditional manual bivariate analysis. Automated multivariate clustering, though highly desirable, is also stymied by the critical requirement of identifying rare populations that form rather small clusters, in addition to the computational challenges posed by the large size and dimensionality of the datasets. In this paper, we address these twin challenges by developing a two-stage scalable multivariate parametric clustering algorithm. In the first stage, we model the data as a mixture of Gaussians and use an iterative weighted sampling technique to estimate the mixture components successively in order of decreasing size. In the second stage, we apply a graphbased hierarchical merging technique to combine Gaussian components with significant overlaps into the final...
Iftekhar Naim, Suprakash Datta, Gaurav Sharma, Jam
Added 06 Dec 2010
Updated 06 Dec 2010
Type Conference
Year 2010
Where ICASSP
Authors Iftekhar Naim, Suprakash Datta, Gaurav Sharma, James S. Cavenaugh, Tim R. Mosmann
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