Lun Aaron T L, Richard Arianne C, Marioni John C
Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK.
Cambridge Institute for Medical Research, University of Cambridge, Cambridge, UK.
Nat Methods. 2017 Jul;14(7):707-709. doi: 10.1038/nmeth.4295. Epub 2017 May 15.
When comparing biological conditions using mass cytometry data, a key challenge is to identify cellular populations that change in abundance. Here, we present a computational strategy for detecting 'differentially abundant' populations by assigning cells to hyperspheres, testing for significant differences between conditions and controlling the spatial false discovery rate. Our method (http://bioconductor.org/packages/cydar) outperforms other approaches in simulations and finds novel patterns of differential abundance in real data.
在使用质谱流式细胞术数据比较生物学条件时，一个关键挑战是识别丰度发生变化的细胞群体。在此，我们提出一种计算策略，通过将细胞分配到超球体、测试不同条件之间的显著差异以及控制空间错误发现率来检测“差异丰度”群体。我们的方法（http://bioconductor.org/packages/cydar）在模拟中优于其他方法，并在实际数据中发现了差异丰度的新模式。
