Qiu Peng
Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia.
Cytometry A. 2017 Mar;91(3):281-289. doi: 10.1002/cyto.a.23068. Epub 2017 Feb 24.
SPADE stands for spanning-tree progression analysis for density-normalized events. It combines downsampling, clustering and a minimum-spanning tree to provide an intuitive visualization of high-dimensional single-cell data, which assists with the interpretation of the cellular heterogeneity underlying the data. SPADE has been widely used for analysis of high-content flow cytometry data and CyTOF data. The downsampling and clustering components of SPADE are both stochastic, which lead to stochasticity in the tree visualization it generates. Running SPADE twice on the same data may generate two different tree structures. Although they typically lead to the same biological interpretation of subpopulations present in the data, robustness of the algorithm can be improved. Another avenue of improvement is the interpretation of the SPADE tree, which involves visual inspection of multiple colored versions of the tree based on expression of measured markers. This is essentially manual gating on the SPADE tree and can benefit from automated algorithms. This article presents improvements of SPADE in both aspects above, leading to a deterministic SPADE algorithm and a software implementation for semiautomated interpretation. © 2017 International Society for Advancement of Cytometry.
SPADE代表密度归一化事件的生成树进展分析。它结合了下采样、聚类和最小生成树，以提供高维单细胞数据的直观可视化，有助于解释数据背后的细胞异质性。SPADE已广泛用于高内涵流式细胞术数据和质谱流式细胞术（CyTOF）数据的分析。SPADE的下采样和聚类组件都是随机的，这导致其生成的树状可视化具有随机性。在相同数据上运行两次SPADE可能会生成两种不同的树结构。尽管它们通常会对数据中存在的亚群产生相同的生物学解释，但算法的稳健性仍可提高。另一个改进途径是对SPADE树的解释，这涉及基于测量标记的表达对树的多个彩色版本进行目视检查。这本质上是在SPADE树上进行手动设门，并且可以受益于自动化算法。本文在上述两个方面对SPADE进行了改进，得到了一种确定性的SPADE算法和一个用于半自动解释的软件实现方案。© 2017国际细胞计量学促进协会
