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Diffusion pseudotime robustly reconstructs lineage branching.
Haghverdi, Laleh; Büttner, Maren; Wolf, F Alexander; Buettner, Florian; Theis, Fabian J.
Afiliação
  • Haghverdi L; Helmholtz Zentrum München, German Research Center for Environmental Health, Institute of Computational Biology, Neuherberg, Germany.
  • Büttner M; Department of Mathematics, Technische Universität München, Munich, Germany.
  • Wolf FA; Helmholtz Zentrum München, German Research Center for Environmental Health, Institute of Computational Biology, Neuherberg, Germany.
  • Buettner F; Helmholtz Zentrum München, German Research Center for Environmental Health, Institute of Computational Biology, Neuherberg, Germany.
  • Theis FJ; Helmholtz Zentrum München, German Research Center for Environmental Health, Institute of Computational Biology, Neuherberg, Germany.
Nat Methods ; 13(10): 845-8, 2016 10.
Article em En | MEDLINE | ID: mdl-27571553
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.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Diferenciação Celular / Modelos Estatísticos / Linhagem da Célula / Análise de Célula Única / Sequenciamento de Nucleotídeos em Larga Escala / Modelos Genéticos Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Animals Idioma: En Ano de publicação: 2016 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Diferenciação Celular / Modelos Estatísticos / Linhagem da Célula / Análise de Célula Única / Sequenciamento de Nucleotídeos em Larga Escala / Modelos Genéticos Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Animals Idioma: En Ano de publicação: 2016 Tipo de documento: Article