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

Kelly Street(Berkeley Public Health Division), Davide Risso(Cornell University), Russell B. Fletcher(University of California, Berkeley), Diya Das(University of California, Berkeley), John Ngai(Innovative Genomics Institute), Nir Yosef(University of California, Berkeley), Elizabeth Purdom(University of California, Berkeley), Sandrine Dudoit(Berkeley Public Health Division)
bioRxiv (Cold Spring Harbor Laboratory)
April 19, 2017
Cited by 284Open Access
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Abstract

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.


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