Fast interpolation-based t-SNE for improved visualization of single-cell RNA-seq data

Nat Methods. 2019 Mar;16(3):243-245. doi: 10.1038/s41592-018-0308-4. Epub 2019 Feb 11.


t-distributed stochastic neighbor embedding (t-SNE) is widely used for visualizing single-cell RNA-sequencing (scRNA-seq) data, but it scales poorly to large datasets. We dramatically accelerate t-SNE, obviating the need for data downsampling, and hence allowing visualization of rare cell populations. Furthermore, we implement a heatmap-style visualization for scRNA-seq based on one-dimensional t-SNE for simultaneously visualizing the expression patterns of thousands of genes. Software is available at and .

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Animals
  • Base Sequence
  • Computational Biology / methods
  • Gene Expression Profiling / methods
  • Genetic Markers
  • Mice
  • RNA / genetics
  • Sequence Analysis, RNA / methods*
  • Single-Cell Analysis / methods*
  • Stochastic Processes


  • Genetic Markers
  • RNA