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

作者：Philipp Angerer, Laleh Haghverdi, Maren Büttner, Fabian J. Theis, Carsten Marr, Florian Buettner · 发表于：Bioinformatics · 年份：2015 · DOI：10.1093/bioinformatics/btv715 · 被引用次数：713 · 研究领域：Single-cell and spatial transcriptomics、Cell Image Analysis Techniques、Mathematical Biology Tumor Growth

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. CONTACT: carsten.marr@helmholtz-muenchen.de or f.buettner@helmholtz-muenchen.de SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.