Gondois-Rey F, Granjeaud S, Rouillier P, Rioualen C, Bidaut G, Olive D
Team Immunity and Cancer, Inserm, U1068, CRCM, Marseille, F-13009, France.
Institut Paoli-Calmettes, Marseille, F-13009, France.
Cytometry A. 2016 May;89(5):480-90. doi: 10.1002/cyto.a.22850. Epub 2016 Apr 5.
The wide possibilities opened by the developments of multi-parametric cytometry are limited by the inadequacy of the classical methods of analysis to the multi-dimensional characteristics of the data. While new computational tools seemed ideally adapted and were applied successfully, their adoption is still low among the flow cytometrists. In the purpose to integrate unsupervised computational tools for the management of multi-stained samples, we investigated their advantages and limits by comparison to manual gating on a typical sample analyzed in immunomonitoring routine. A single tube of PBMC, containing 11 populations characterized by different sizes and stained with 9 fluorescent markers, was used. We investigated the impact of the strategy choice on manual gating variability, an undocumented pitfall of the analysis process, and we identified rules to optimize it. While assessing automatic gating as an alternate, we introduced the Multi-Experiment Viewer software (MeV) and validated it for merging clusters and annotating interactively populations. This procedure allowed the finding of both targeted and unexpected populations. However, the careful examination of computed clusters in standard dot plots revealed some heterogeneity, often below 10%, that was overcome by increasing the number of clusters to be computed. MeV facilitated the identification of populations by displaying both the MFI and the marker signature of the dataset simultaneously. The procedure described here appears fully adapted to manage homogeneously high number of multi-stained samples and allows improving multi-parametric analyses in a way close to the classic approach. © 2016 International Society for Advancement of Cytometry.
多参数细胞术发展所带来的广泛可能性受到经典分析方法对数据多维特征适应性不足的限制。虽然新的计算工具似乎非常适用且已成功应用，但在流式细胞仪专家中其采用率仍然很低。为了整合用于管理多染色样本的无监督计算工具，我们通过与免疫监测常规分析的典型样本上的手动设门进行比较，研究了它们的优点和局限性。使用了一管外周血单个核细胞（PBMC），其中包含11个以不同大小为特征且用9种荧光标记染色的细胞群体。我们研究了策略选择对手动设门变异性（分析过程中一个未记录的陷阱）的影响，并确定了优化它 的规则。在评估自动设门作为替代方法时，我们引入了多实验查看器软件（MeV），并对其合并聚类和交互式注释群体的功能进行了验证。该程序能够发现目标群体和意外群体。然而，在标准点图中仔细检查计算出的聚类时发现了一些异质性，通常低于10%，通过增加要计算的聚类数量可以克服这一问题。MeV通过同时显示数据集的平均荧光强度（MFI）和标记特征，促进了群体的识别。这里描述的程序似乎完全适用于统一管理大量多染色样本，并能够以接近经典方法的方式改进多参数分析。© 2016国际细胞计量学促进协会。
