Mage Peter L, Konecny Andrew J, Mair Florian
Advanced Technology Group, BD Biosciences, Milpitas, CA 95035, USA.
Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA.
bioRxiv. 2025 May 21:2025.04.17.649396. doi: 10.1101/2025.04.17.649396.
Advances in spectral cytometry instrumentation and fluorescent reagents have led to the possibility of ultra-high-parameter panels exceeding 50 colors. However, panel size is limited in practice by unmixing-dependent spreading (UDS), a mathematical phenomenon which leads to a progressive deterioration of unmixed signal-to-noise ratios in panels that contain fluorochrome combinations with significant spectral overlap. Choosing spectrally compatible sets of fluorochromes that avoid UDS is a complex and labor-intensive task involving substantial trial-and-error experimentation. Here, we provide a detailed explanation of UDS and practical strategies for handling UDS in large spectral panels. We describe the empirical hallmarks of UDS, demonstrate how to quantify its impact, and dissect its underlying mathematical cause in terms of spectral collinearity. We present novel computational metrics that can be used to select optimal combinations of fluorochromes in a platform-agnostic fashion based on publicly available reference data, providing a general tool for spectral panel design.
光谱流式细胞术仪器和荧光试剂的进步使得超过50种颜色的超高参数检测成为可能。然而，在实际应用中，检测组合的大小受到非混合依赖性扩散（UDS）的限制，这是一种数学现象，会导致在包含具有显著光谱重叠的荧光染料组合的检测组合中，非混合信噪比逐渐恶化。选择避免UDS的光谱兼容荧光染料组是一项复杂且耗时的任务，需要大量的反复试验。在此，我们详细解释了UDS以及在大型光谱检测组合中处理UDS的实用策略。我们描述了UDS的经验特征，展示了如何量化其影响，并从光谱共线性的角度剖析其潜在的数学原因。我们提出了新的计算指标，可用于基于公开可用的参考数据，以平台无关的方式选择荧光染料的最佳组合，为光谱检测组合设计提供了一个通用工具。
