viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia
Amir, el-A.D., Davis, K.L., Tadmor, M.D. et al.
High-dimensional single-cell technologies are revolutionizing the way we understand biological systems. Technologies such as mass cytometry measure dozens of parameters simultaneously in individual cells, making interpretation daunting. We developed viSNE, a tool to map high-dimensional cytometry data onto 2D while conserving high-dimensional structure. We integrated mass cytometry with viSNE to map healthy and cancerous bone marrow samples. Healthy bone marrow maps into a canonical shape that separates between immune subtypes. In leukemia, however, the shape is malformed: the maps of cancer samples are distinct from the healthy map and from each other. viSNE highlights structure in the heterogeneity of surface phenotype expression in cancer, traverses the progression from diagnosis to relapse, and identifies a rare leukemia population in minimal residual disease settings. As several new technologies raise the number of simultaneously measured parameters in each cell to the hundreds, viSNE will become a mainstay in analyzing and interpreting such experiments.
Amir, el-A.D., Davis, K.L., Tadmor, M.D. et al. "viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia" Nature Biotechnology (2013): 545–52