Tailor provides a Gaussian mixture modeling workflow for working with flow cytometry data. The first step is a preliminary binning of the data, which is used for both weighted subsampling and initialization of the main algorithm. This serves to address the two main deficiencies of standard mixture modeling approaches: slow runtime and sensitivity to initialization. The main algorithm is a weighted version of the Expectation-Maximization (EM) algorithm, through which Tailor models the data as a superposition of mixture components. Finally, some of these components are merged, if there are strong indications that they belong to the same biological population.
|Bioconductor views||CellBasedAssays CellBiology Clustering FlowCytometry|
|Maintainer||Matei Ionita <firstname.lastname@example.org>|
|Package repository||View on GitHub|
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