Flow cytometers are powerful tools for bioanalytical applications, yet new systems that promise better measurements are continuously being introduced as sensors and other technologies advance. One such advancement by NIST was the recently demonstrated a serial microcytometer that enables unique capabilities for uncertainty quantification on a per-object basis. In an effort to benchmark and improve the measurement capabilities of the serial microcytometer, we found limitations to the quantitative comparison of instruments using conventional metrics and methods. To address these shortcomings, we recently developed an improved model that builds upon conventional models to improve comparability (Patrone et al. "Uncertainty Quantification of Fluorescence Signals in Flow Cytometry Part I: An Analytical Perspective Beyond Q and B" submitted in conjunction with this manuscript). In Part I, and continued here, our aim was to develop metrics that enable comparisons based on upper limit of linearity, limit of background, limit of detection, noise-to-signal ratio, and uncertainty decomposition thereof. We found that the NIST serial microcytometer has similar performance capabilities to a conventional analytical flow cytometer. This manuscript continues the development of uncertainty quantification (UQ) for flow cytometry by demonstrating how a serial microcytometer facilitates separation of the instrument-and population-dependent contributions to UQ. Component-level contributions to UQ can also be analyzed. Ultimately, these methods establish robust metrics for instrument performance and introduce per-object uncertainty as a mechanism facilitating better classification and utilization of cytometry data in research and clinical use.
Catterton et al. (Sat,) studied this question.