26 research outputs found

    SWIFT: Scalable weighted iterative sampling for flow cytometry clustering

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    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 number of desired clusters. The resulting algorithm offers a reduction in complexity over conventional mixture modeling while simultaneously allowing for better detection of small populations. We demonstrate the effectiveness of our method both on simulated data and actual flow cytometry datasets. Index Terms — Flow cytometry, clustering, Gaussian mixture model, sampling, expectation-maximizatio

    Effects of maturation on parameters used for pass/fail criteria in neonatal hearing screening programmes using evoked otoacoustic emissions

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    We aimed to investigate the incidence of false alarms that occurred with the pass/fail criteria used in a published series of neonatal hearing screening programmes, as a function of age. We analysed the database of 19137 normally hearing babies (38274 ears) tested in the Wessex Universal Neonatal Hearing Screening Project. Otoacoustic emissions were recorded prior to discharge from maternity units, using IL088 equipment. We assessed the pass/fail rate using the Wessex criteria and 10 other pass/fail criteria published in the literature. Using Pearson's correlation coefficient, a statistically significant correlation between signal-to-noise ratio at each of the frequency bands 1, 2, 3, 4 and 5 kHz and babies' age in hours at the 0.01 level was identified. The correlation was also significant (0.01 level) between age and frequency reproducibility in each of the bands at 1, 2, 3, 4 and 5 kHz as well as the whole reproducibility. The number of false alarms reduced significantly after the first 24 h of life with all the criteria examined. We conclude that in the first hours after birth due to insufficient maturation of the otoacoustic emission, there is a high rate of false alarms. This increase in the false alarm rate, whilst dependent on the criteria used, occurs with all criteria. This leads to the consideration of whether the establishment of age-dependent pass/fail criteria could reduce the false alarm rate and the subsequent strain on diagnostic centres. Copyright (c) 2007 S. Karger AG, Base
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