Mass cytometry is an emerging technology capable of 40 or more correlated measurements on a single cell. The complexity and volume of data generated by this platform have accelerated the creation of novel methods for high-dimensional data analysis and visualization. A key step in any high-level data analysis is the removal of unwanted events, a process often referred to as data cleanup. Data cleanup as applied to mass cytometry typically focuses on elimination of dead cells, debris, normalization beads, true aggregates, and coincident ion clouds from raw data. We describe a probability state modeling (PSM) method that automatically identifies and removes these elements, resulting in FCS files that contain mostly live and intact events. This approach not only leverages QC measurements such as DNA, live/dead, and event length but also four additional pulse-processing parameters that are available on Fluidigm Helios™ and CyTOF® (Fluidigm, Markham, Canada) 2 instruments with software versions of 6.3 or higher. These extra Gaussian-derived parameters are valuable for detecting well-formed pulses and eliminating coincident positive ion clouds. The automated nature of this new routine avoids the subjectivity of other gating methods and results in unbiased elimination of unwanted events. © 2019 International Society for Advancement of Cytometry.

中文翻译：

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质谱流式细胞术的自动数据清理。

质谱流式细胞仪是一项新兴技术，能够对单个细胞进行 40 次或更多相关测量。该平台生成的数据的复杂性和数量加速了高维数据分析和可视化新方法的创建。任何高级数据分析的关键步骤是删除不需要的事件，这个过程通常称为数据清理。应用于质谱流式分析的数据清理通常侧重于从原始数据中消除死细胞、碎片、归一化珠、真实聚集体和重合离子云。我们描述了一种概率状态建模 (PSM) 方法，该方法可自动识别并删除这些元素，从而生成主要包含实时且完整事件的 FCS 文件。该方法不仅利用 DNA、活/死和事件长度等 QC 测量，还利用 Fluidigm Helios™ 和 CyTOF®（Fluidigm，加拿大万锦市）2 台软件版本为 6.3 的仪器上提供的四个附加脉冲处理参数或更高。这些额外的高斯派生参数对于检测形状良好的脉冲和消除重合的正离子云非常有价值。这种新例程的自动化性质避免了其他门控方法的主观性，并导致公正地消除不需要的事件。© 2019 国际细胞计数促进会。