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 http://bioconductor.org/packages/destiny also available at https://www.helmholtz-muenchen.de/icb/destiny. A detailed vignette describing functions and workflows is provided with the package.