Megan A. Catterton, Matthew DiSalvo, Paul N. Patrone, Gregory A. Cooksey
{"title":"Uncertainty Quantification of Fluorescence Signals for Cytometry Part II: Comparison of Serial and Traditional Flow Cytometers","authors":"Megan A. Catterton, Matthew DiSalvo, Paul N. Patrone, Gregory A. Cooksey","doi":"10.1002/cyto.a.24952","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>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.</p>\n </div>","PeriodicalId":11068,"journal":{"name":"Cytometry Part A","volume":"107 8","pages":"524-537"},"PeriodicalIF":2.1000,"publicationDate":"2025-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cytometry Part A","FirstCategoryId":"99","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cyto.a.24952","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
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.
期刊介绍:
Cytometry Part A, the journal of quantitative single-cell analysis, features original research reports and reviews of innovative scientific studies employing quantitative single-cell measurement, separation, manipulation, and modeling techniques, as well as original articles on mechanisms of molecular and cellular functions obtained by cytometry techniques.
The journal welcomes submissions from multiple research fields that fully embrace the study of the cytome:
Biomedical Instrumentation Engineering
Biophotonics
Bioinformatics
Cell Biology
Computational Biology
Data Science
Immunology
Parasitology
Microbiology
Neuroscience
Cancer
Stem Cells
Tissue Regeneration.