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

Tools

Item Type:	Article
Title:	destiny: diffusion maps for large-scale single-cell data in R
Creators Name:	Angerer, P., Haghverdi, L., Büttner, M., Theis, F.J., Marr, C. and Buettner, F.
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.
Keywords:	Algorithms, Cluster Analysis, Diffusion, Single-Cell Analysis, Software
Source:	Bioinformatics
ISSN:	1367-4803
Publisher:	Oxford University Press
Volume:	32
Number:	8
Page Range:	1241-1243
Date:	15 April 2016
Official Publication:	https://doi.org/10.1093/bioinformatics/btv715
PubMed:	View item in PubMed

Repository Staff Only: item control page