Paul N. Patrone, Anthony J. Kearsley, Megan A. Catterton, Gregory A. Cooksey
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引用次数: 0
摘要
该手稿是开发和实现计量和不确定度量化(UQ)应用于流式细胞术的核心思想系列中的第一篇。本文工作的动机是估计细胞仪的检测效率(Q)和背景(B)的问题。尽管经过了30多年的研究,该问题的规范解所做的近似忽略和放大了各种噪声源,从而导致Q $$ Q $$的不稳定估计和B $$ B $$的负值。此外,如何在这些属性的基础上比较工具并不总是很清楚。为了解决这些问题,我们提出了一种全球数据分析策略,该策略结合了不同增益的测量结果,同时考虑了增益无关的背景效应,这些背景效应通常被忽视,但往往占主导地位。值得注意的是,这种技术产生了Q $$ Q $$和B $$ B $$的稳定估计,同时也量化了其他噪声源的相对影响。在概念上,我们的分析也统一并解释了现有数据分析方法的不足。然而,最重要的是,这项工作使我们能够严格定义与仪器性能相关的检测和定量限制等概念,并以一种消除与样品制备、操作员效应等相关影响的方式。重要的是,这允许在与样品无关的不确定度指标的基础上对细胞仪进行直接比较,并根据仪器引起的不确定度产生优化细胞仪性能的信息。使用商业仪器和nist开发的串联细胞仪对结果进行了实验验证,并在本系列的配套手稿中考虑了扩展。
Uncertainty Quantification of Fluorescence Signals in Flow Cytometry Part I: An Analytical Perspective Beyond Q and B
This manuscript is the first in a series that develops and realizes core ideas from metrology and uncertainty quantification (UQ) as applied to flow cytometry. The work herein is motivated by the problem of estimating the detection efficiency (Q) and background (B) of cytometers. Despite more than 30 years of study, canonical solutions to this problem make approximations that both ignore and amplify various sources of noise, thereby leading to unstable estimators of and negative values of . Moreover, it is not always clear how to compare instruments on the basis of such properties. To address these issues, we propose a global data analysis strategy that combines measurements taken with different gains while simultaneously accounting for gain-independent background effects, which are typically ignored but often dominant. Of note, this technique yields stable estimates of and while also quantifying the relative impacts of other noise sources. Conceptually, our analysis also unifies and explains the shortcomings of existing data analysis methods. Most importantly, however, this work allows us to rigorously define concepts such as limits of detection and quantification associated with instrument performance alone and in a way that removes effects associated with sample preparation, operator effects, and so forth. Importantly, this allows for direct comparison of cytometers on the basis of sample-independent uncertainty metrics and yields information for optimizing cytometer performance in terms of instrument-induced uncertainties. Results are experimentally verified using both commercial instruments and a NIST-developed serial cytometer, with extensions considered in companion manuscripts of this series.
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.