Slingshot: Cell lineage and pseudotime inference for single-cell transcriptomics

Abstract

Single-cell transcriptomics allows researchers to investigate complex communities of heterogeneous cells. These methods can be applied to stem cells and their descendants in order to chart the progression from multipotent progenitors to fully differentiated cells. While a number of statistical and computational methods have been proposed for analyzing cell lineages, the problem of accurately characterizing multiple branching lineages remains difficult to solve. Here, we introduce a novel method, Slingshot, for inferring multiple developmental lineages from single-cell gene expression data. Slingshot is a uniquely robust and flexible tool for inferring developmental lineages and ordering cells to reflect continuous, branching processes.

Code

The associated R package can be found on Bioconductor here. Development versions and issues can be tracked on GitHub here.

Preprint

A version of this paper was previously published as a preprint. The final peer-reviewed version is substantially expanded. The citation for the preprint is as follows:

Kelly Street, Davide Risso, Russell B. Fletcher, Diya Das, John Ngai, Nir Yosef, Elizabeth Purdom, and Sandrine Dudoit. (2017). Slingshot: Cell lineage and pseudotime inference for single-cell transcriptomics. bioRxiv 128843; doi: https://doi.org/10.1101/128843.