Visual analysis of mass cytometry data by hierarchical stochastic neighbour embedding reveals rare cell types - Vincent van Unen (Nature Portfolio, 2017)
Single cell profiling yields high dimensional data of very large numbers of cells, posing challenges of visualization and analysis. Here the authors introduce a method for analysis of mass cytometry data that can handle very large datasets and allows their intuitive and hierarchical exploration.