Department of Microbiology and Immunology, University of Otago, Dunedin, New Zealand.
Myeloma Research Group, Australian Centre for Blood Diseases, Alfred Hospital-Monash University, Melbourne, VIC, Australia.
BMC Bioinformatics. 2020 Apr 15;21(1):145. doi: 10.1186/s12859-020-3469-y.
The advent of mass cytometry has dramatically increased the parameter limit for immunological analysis. New approaches to analysing high parameter cytometry data have been developed to ease analysis of these complex datasets. Many of these methods assign cells into population clusters based on protein expression similarity.
Here we introduce an additional method, termed Brick plots, to visualize these cluster phenotypes in a simplified and intuitive manner. The Brick plot method generates a two-dimensional barcode that displays the phenotype of each cluster in relation to the entire dataset. We show that Brick plots can be used to visualize complex mass cytometry data, both from fundamental research and clinical trials, as well as flow cytometry data.
Brick plots represent a new approach to visualize complex immunological data in an intuitive manner.
随着质谱流式技术的出现,免疫分析的参数极限得到了显著提高。为了便于分析这些复杂的数据集,已经开发了新的方法来分析高参数的流式细胞术数据。这些方法中的许多方法都是基于蛋白质表达的相似性将细胞分配到群体聚类中。
在这里,我们引入了一种额外的方法,称为 Brick plots,以简化和直观的方式可视化这些聚类表型。Brick plots 方法生成一个二维条形码,显示每个聚类相对于整个数据集的表型。我们表明,Brick plots 可用于可视化复杂的质谱流式细胞术数据,包括基础研究和临床试验以及流式细胞术数据。
Brick plots 代表了一种直观地可视化复杂免疫数据的新方法。