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bioRxiv · 10.1101/023309

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

Philipp Angerer·Laleh Haghverdi·Maren Büttner·Fabian Theis·Carsten Marr·Florian Buettner
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Abstract

SummaryDiffusion 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.\n\nAvailability and implementationdestiny 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.\n\nContactcarsten.marr@helmholtz-muenchen.de, f.buettner@helmholtz-muenchen.de

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Philipp Angerer, Laleh Haghverdi, Maren Büttner, Fabian Theis, Carsten Marr, Florian Buettner. 2015-07-27. destiny – diffusion maps for large-scale single-cell data in R. https://doi.org/10.1101/023309

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