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.

Keywords

InferenceComputer scienceSnapshot (computer storage)ScalabilityRandom walkStatistical physicsDiffusion MRIBranching (polymer chemistry)AlgorithmArtificial intelligenceBiologyTheoretical computer sciencePhysicsMathematicsStatisticsChemistry

MeSH Terms

AlgorithmsAnimalsCell DifferentiationCell LineageCluster AnalysisComputer SimulationDiffusionEmbryonic Stem CellsHigh-Throughput Nucleotide SequencingMiceModelsGeneticModelsStatisticalNumerical AnalysisComputer-AssistedSingle-Cell Analysis

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Publication Info

Year
2016
Type
article
Volume
13
Issue
10
Pages
845-848
Citations
1367
Access
Closed

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Cite This

Laleh Haghverdi, Maren Büttner, F. Alexander Wolf et al. (2016). Diffusion pseudotime robustly reconstructs lineage branching. Nature Methods , 13 (10) , 845-848. https://doi.org/10.1038/nmeth.3971

Identifiers

DOI
10.1038/nmeth.3971
PMID
27571553

Data Quality

Data completeness: 81%