• Philipp Angerer, Laleh Haghverdi, Maren Büttner, Fabian J Theis, Carsten Marr, and Florian Buettner.
• Helmholtz Zentrum München - German Research Center for Environmental Health, Institute of Computational Biology, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany and.
• Bioinformatics. 2016 Apr 15; 32 (8): 1241-3.

Unlabelled: 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 Implementationdestiny is an open-source R/Bioconductor package "bioconductor.org/packages/destiny" also available at www.helmholtz-muenchen.de/icb/destiny A detailed vignette describing functions and workflows is provided with the package.Contactcarsten.marr@helmholtz-muenchen.de or f.buettner@helmholtz-muenchen.deSupplementary InformationSupplementary data are available at Bioinformatics online.© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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