Rapid cell population identification in flow cytometry data
نویسندگان
چکیده
منابع مشابه
Rapid cell population identification in flow cytometry data.
We have developed flowMeans, a time-efficient and accurate method for automated identification of cell populations in flow cytometry (FCM) data based on K-means clustering. Unlike traditional K-means, flowMeans can identify concave cell populations by modelling a single population with multiple clusters. flowMeans uses a change point detection algorithm to determine the number of sub-population...
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We present a framework for the identification of cell subpopulations in flow cytometry data based on merging mixture components using the flowClust methodology. We show that the cluster merging algorithm under our framework improves model fit and provides a better estimate of the number of distinct cell subpopulations than either Gaussian mixture models or flowClust, especially for complicated ...
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flowDensity: reproducing manual gating of flow cytometry data by automated density-based cell population identification
SUMMARY flowDensity facilitates reproducible, high-throughput analysis of flow cytometry data by automating a predefined manual gating approach. The algorithm is based on a sequential bivariate gating approach that generates a set of predefined cell populations. It chooses the best cut-off for individual markers using characteristics of the density distribution. The Supplementary Material is li...
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ژورنال
عنوان ژورنال: Cytometry Part A
سال: 2010
ISSN: 1552-4922
DOI: 10.1002/cyto.a.21007