Merging Mixture Components for Cell Population Identification in Flow Cytometry

Figure 6

Simulation results for CD4 versus CD8 dimensions of a CLL sample. (a) The 2D kernel density estimate of the real CD4 versus CD8 data. Gates for the CD4+/CD8−, CD8+/CD4−, and CD4−/CD8− subpopulations are represented by light coloured lines. Events outside the gates are considered outliers. (b) An example of the kernel density estimate of simulated data drawn from the distribution defined by the real data. (c) The number of clusters selected by the flowMerge solution, the GMMBIC solution, the flowClustBIC, and flowClustICL solutions over 100 realizations of simulated data. (d) The median flowClustBIC flowClust solution with 9 components. (e) The median flowMerge solution with 5 components. (f) The misclassification rate (MCR) for the flowMergeK solution, the GMMK solution, and the flowClustK solution with the number of clusters fixed to the true number of cell subpopulations (𝐾=3). (g) The misclassification rates for the three components from the optimal GMMBIC, flowClustBIC, and flowMerge solutions minimizing the MCR. (h) A GMM, (i) flowClust, (j) and flowMergeK solution with a fixed number of clusters.

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