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Plate IV.486 · Publications

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

Article in Bioinformatics, 14 December 2015.

Open accessSingle Cell RNA, Gene Expression

  1. Philipp Angerer
  2. Laleh Haghverdi
  3. Maren Büttner
  4. Fabian J. Theis
  5. Carsten Marr
  6. Florian Buettner

Abstract

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 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. Supplementary information Supplementary data are available at Bioinformatics online.

Versions2

  1. PublishedBioinformatics10.1093/bioinformatics/btv715
  2. PreprintbioRxiv10.1101/023309

Cite

@article{angerer2015destiny,
  title = {{destiny: diffusion maps for large-scale single-cell data in R}},
  author = {Angerer, Philipp and Haghverdi, Laleh and Büttner, Maren and Theis, Fabian J. and Marr, Carsten and Buettner, Florian},
  journal = {Bioinformatics},
  publisher = {Oxford University Press (OUP)},
  year = {2015},
  month = dec,
  doi = {10.1093/bioinformatics/btv715},
  url = {https://doi.org/10.1093/bioinformatics/btv715},
  pmid = {26668002}
}
.bib file