destiny: diffusion maps for large-scale single-cell data in R

Bioinformatics. 2016 Apr 15;32(8):1241-3. doi: 10.1093/bioinformatics/btv715. Epub 2015 Dec 14.


: Diffusion maps are a spectral method for non-linear dimension reduction and have recently been adapted for the visualization of single-cell expression data. Here we present destiny, an efficient R implementation of the diffusion map algorithm. Our package includes a single-cell specific noise model allowing for missing and censored values. In contrast to previous implementations, we further present an efficient nearest-neighbour approximation that allows for the processing of hundreds of thousands of cells and a functionality for projecting new data on existing diffusion maps. We exemplarily apply destiny to a recent time-resolved mass cytometry dataset of cellular reprogramming.

Availability and implementation: destiny is an open-source R/Bioconductor package "" also available at A detailed vignette describing functions and workflows is provided with the package.

Contact: or

Supplementary information: Supplementary data are available at Bioinformatics online.

MeSH terms

  • Algorithms*
  • Cluster Analysis
  • Diffusion
  • Single-Cell Analysis / methods*
  • Software