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Diffusion Pseudotime Robustly Reconstructs Lineage Branching

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Journal Nat Methods
Date 2016 Aug 30
PMID 27571553
Citations 576
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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.

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References
1.
Finak G, McDavid A, Yajima M, Deng J, Gersuk V, Shalek A . MAST: a flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single-cell RNA sequencing data. Genome Biol. 2015; 16:278. PMC: 4676162. DOI: 10.1186/s13059-015-0844-5. View

2.
Bendall S, Davis K, Amir E, Tadmor M, Simonds E, Chen T . Single-cell trajectory detection uncovers progression and regulatory coordination in human B cell development. Cell. 2014; 157(3):714-25. PMC: 4045247. DOI: 10.1016/j.cell.2014.04.005. View

3.
Angerer P, Haghverdi L, Buttner M, Theis F, Marr C, Buettner F . destiny: diffusion maps for large-scale single-cell data in R. Bioinformatics. 2015; 32(8):1241-3. DOI: 10.1093/bioinformatics/btv715. View

4.
Setty M, Tadmor M, Reich-Zeliger S, Angel O, Salame T, Kathail P . Wishbone identifies bifurcating developmental trajectories from single-cell data. Nat Biotechnol. 2016; 34(6):637-45. PMC: 4900897. DOI: 10.1038/nbt.3569. View

5.
Klein A, Mazutis L, Akartuna I, Tallapragada N, Veres A, Li V . Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells. Cell. 2015; 161(5):1187-1201. PMC: 4441768. DOI: 10.1016/j.cell.2015.04.044. View