{"title":"高维流式细胞仪数据:金矿还是傻子的黄金?","authors":"Paula Niewold","doi":"10.1002/cyto.a.24849","DOIUrl":null,"url":null,"abstract":"<p>Since its inception in the 1970s flow cytometry has been a valuable tool to study the characteristics of cells. Technical advancements lead to a rapid increase in the number of lasers and detectors, enabling assessment of an expanding number of parameters. As every flow cytometry user has experienced the frustration of not being able to fit all markers of interest into their panel, the prevailing mindset seemingly became the bigger the better. So, when spectral flow cytometers became commercially available, their ability to combine spectrally similar fluorophores, measure cellular autofluorescence and utilize the full light spectrum more effectively was received with enthusiasm. These attributes make spectral cytometry particularly applicable for limited or precious (clinical) material.</p><p>The recent paper from Dott et al. describes the development of a standardized protocol for sample handling, staining and acquisition, for the application of two large spectral panels in a cohort study using the ID7000™ Spectral Cell Analyzer (Sony Biotechnology).<span><sup>1</sup></span> The authors specifically address the repeatability and reproducibility of staining over time, which is relevant in the context of cohort studies. By combining a 34- and 35-color spectral panel, the authors were able to quantify and identify 182 cell phenotypes in whole blood samples.</p><p>Our expanding immunological knowledge of rare and unique subsets through deep profiling has necessitated the increasing number of cellular parameters required in a single panel for accurate cell identification. However, a new set of challenges arise with increasing panel size. Although the principle of panel design and analysis remain similar, assessing data quality, defining cell populations and translating phenotypic changes into biological insight become increasingly difficult. While many papers have addressed one of these challenges, Dott et al. touch upon all three of these concerns.<span><sup>1</sup></span></p><p><b>Paula Niewold:</b> Conceptualization; writing – original draft.</p>","PeriodicalId":11068,"journal":{"name":"Cytometry Part A","volume":null,"pages":null},"PeriodicalIF":2.5000,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cyto.a.24849","citationCount":"0","resultStr":"{\"title\":\"High-dimensional flow cytometry data: goldmine or fool's gold?\",\"authors\":\"Paula Niewold\",\"doi\":\"10.1002/cyto.a.24849\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Since its inception in the 1970s flow cytometry has been a valuable tool to study the characteristics of cells. Technical advancements lead to a rapid increase in the number of lasers and detectors, enabling assessment of an expanding number of parameters. As every flow cytometry user has experienced the frustration of not being able to fit all markers of interest into their panel, the prevailing mindset seemingly became the bigger the better. So, when spectral flow cytometers became commercially available, their ability to combine spectrally similar fluorophores, measure cellular autofluorescence and utilize the full light spectrum more effectively was received with enthusiasm. These attributes make spectral cytometry particularly applicable for limited or precious (clinical) material.</p><p>The recent paper from Dott et al. describes the development of a standardized protocol for sample handling, staining and acquisition, for the application of two large spectral panels in a cohort study using the ID7000™ Spectral Cell Analyzer (Sony Biotechnology).<span><sup>1</sup></span> The authors specifically address the repeatability and reproducibility of staining over time, which is relevant in the context of cohort studies. By combining a 34- and 35-color spectral panel, the authors were able to quantify and identify 182 cell phenotypes in whole blood samples.</p><p>Our expanding immunological knowledge of rare and unique subsets through deep profiling has necessitated the increasing number of cellular parameters required in a single panel for accurate cell identification. However, a new set of challenges arise with increasing panel size. Although the principle of panel design and analysis remain similar, assessing data quality, defining cell populations and translating phenotypic changes into biological insight become increasingly difficult. 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High-dimensional flow cytometry data: goldmine or fool's gold?
Since its inception in the 1970s flow cytometry has been a valuable tool to study the characteristics of cells. Technical advancements lead to a rapid increase in the number of lasers and detectors, enabling assessment of an expanding number of parameters. As every flow cytometry user has experienced the frustration of not being able to fit all markers of interest into their panel, the prevailing mindset seemingly became the bigger the better. So, when spectral flow cytometers became commercially available, their ability to combine spectrally similar fluorophores, measure cellular autofluorescence and utilize the full light spectrum more effectively was received with enthusiasm. These attributes make spectral cytometry particularly applicable for limited or precious (clinical) material.
The recent paper from Dott et al. describes the development of a standardized protocol for sample handling, staining and acquisition, for the application of two large spectral panels in a cohort study using the ID7000™ Spectral Cell Analyzer (Sony Biotechnology).1 The authors specifically address the repeatability and reproducibility of staining over time, which is relevant in the context of cohort studies. By combining a 34- and 35-color spectral panel, the authors were able to quantify and identify 182 cell phenotypes in whole blood samples.
Our expanding immunological knowledge of rare and unique subsets through deep profiling has necessitated the increasing number of cellular parameters required in a single panel for accurate cell identification. However, a new set of challenges arise with increasing panel size. Although the principle of panel design and analysis remain similar, assessing data quality, defining cell populations and translating phenotypic changes into biological insight become increasingly difficult. While many papers have addressed one of these challenges, Dott et al. touch upon all three of these concerns.1
Paula Niewold: Conceptualization; writing – original draft.
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.