Hierarchical Modeling for Rare Event Detection and Cell Subset Alignment across Flow Cytometry Samples
Figure 9
Performance of HDPGMM with different numbers of events, samples and markers.
Left panel shows time taken to fit HDPGMM to 10 samples with 50,000 to 500,000 events and 10 markers. Middle panel shows time taken to fit HDPGMM to 3 to 30 samples each with 100,000 events and 10 markers. Right panel shows time taken to fit 10 samples each with 100,000 events with the number of markers varying from 5 to 15. In each case, the model was run for 1,000 MCMC steps with an upper limit of 128 mixture components on a NVidia GTX 580 GPU, and the times from three replicate runs are shown.