<i>destiny</i> : diffusion maps for large-scale single-cell data in R

Abstract

Abstract Summary: 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 “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. Contact: carsten.marr@helmholtz-muenchen.de or f.buettner@helmholtz-muenchen.de Supplementary information: Supplementary data are available at Bioinformatics online.

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Affiliated Institutions

• Technical University of Munich DE
• Helmholtz Zentrum München DE

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