Fig. 11
From: BayesFlow: latent modeling of flow cytometry cell populations
Summary statistics of the six cell populations obtained by BayesFlow (run 2) in the dataset GvHD. The outlier component has at most 0.0019 of the cells in a sample. a Each panel displays the locations μ jk of all mixture components that represent the population, across all samples. Different shades of a color represent different latent components k. b Box plots of the soft clusters in the pooled data. The boxes go between the quantiles q k m,0.25 and q k m,0.75, the whiskers extend to q k m,0.01 and q k m,0.99. The α-quantile for (merged) component k in dimension m, q k m,α , is here defined as \(q_{km,\alpha } = \min _{i'j'}\{Y_{i'j'm} : \alpha < \sum _{ij:Y_{ijm} < Y_{i'j'm}} w_{ijk} \}\). c Population proportions in each of the twelve flow cytometry samples