Diffusion pseudotime robustly reconstructs lineage branching

Laleh Haghverdi; Maren Büttner; F. Alexander Wolf; Florian Buettner; Fabian J. Theis

doi:10.1038/nmeth.3971

Diffusion pseudotime robustly reconstructs lineage branching

Laleh Haghverdi
, Maren Büttner
, F. Alexander Wolf
, Florian Buettner
, Fabian J. Theis

Chair of Mathematical Modelling of Biological Systems

Research output: Contribution to journal › Article › peer-review

870 Scopus citations

Abstract

The temporal order of differentiating cells is intrinsically encoded in their single-cell expression profiles. We describe an efficient way to robustly estimate this order according to diffusion pseudotime (DPT), which measures transitions between cells using diffusion-like random walks. Our DPT software implementations make it possible to reconstruct the developmental progression of cells and identify transient or metastable states, branching decisions and differentiation endpoints.

Original language	English
Pages (from-to)	845-848
Number of pages	4
Journal	Nature Methods
Volume	13
Issue number	10
DOIs	https://doi.org/10.1038/nmeth.3971
State	Published - 1 Oct 2016

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title = "Diffusion pseudotime robustly reconstructs lineage branching",

abstract = "The temporal order of differentiating cells is intrinsically encoded in their single-cell expression profiles. We describe an efficient way to robustly estimate this order according to diffusion pseudotime (DPT), which measures transitions between cells using diffusion-like random walks. Our DPT software implementations make it possible to reconstruct the developmental progression of cells and identify transient or metastable states, branching decisions and differentiation endpoints.",

author = "Laleh Haghverdi and Maren B{\"u}ttner and Wolf, \{F. Alexander\} and Florian Buettner and Theis, \{Fabian J.\}",

year = "2016",

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AU - Büttner, Maren

AU - Wolf, F. Alexander

AU - Buettner, Florian

AU - Theis, Fabian J.

PY - 2016/10/1

Y1 - 2016/10/1

N2 - The temporal order of differentiating cells is intrinsically encoded in their single-cell expression profiles. We describe an efficient way to robustly estimate this order according to diffusion pseudotime (DPT), which measures transitions between cells using diffusion-like random walks. Our DPT software implementations make it possible to reconstruct the developmental progression of cells and identify transient or metastable states, branching decisions and differentiation endpoints.

AB - The temporal order of differentiating cells is intrinsically encoded in their single-cell expression profiles. We describe an efficient way to robustly estimate this order according to diffusion pseudotime (DPT), which measures transitions between cells using diffusion-like random walks. Our DPT software implementations make it possible to reconstruct the developmental progression of cells and identify transient or metastable states, branching decisions and differentiation endpoints.

UR - https://www.scopus.com/pages/publications/84984643819

U2 - 10.1038/nmeth.3971

DO - 10.1038/nmeth.3971

M3 - Article

C2 - 27571553

AN - SCOPUS:84984643819

SN - 1548-7091

VL - 13

SP - 845

EP - 848

JO - Nature Methods

JF - Nature Methods

IS - 10

ER -

Diffusion pseudotime robustly reconstructs lineage branching

Abstract

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