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Lange, M. ; Bergen, V. ; Klein, M. ; Setty, M.* ; Reuter, B.* ; Bakhti, M. ; Lickert, H. ; Ansari, M. ; Schniering, J. ; Schiller, H. B. ; Pe'er, D.* ; Theis, F.J.

CellRank for directed single-cell fate mapping.

Nat. Methods 19, 159–170 (2022)
Verlagsversion Forschungsdaten DOI PMC
Open Access Gold (Paid Option)
Creative Commons Lizenzvertrag
Computational trajectory inference enables the reconstruction of cell state dynamics from single-cell RNA sequencing experiments. However, trajectory inference requires that the direction of a biological process is known, largely limiting its application to differentiating systems in normal development. Here, we present CellRank ( https://cellrank.org ) for single-cell fate mapping in diverse scenarios, including regeneration, reprogramming and disease, for which direction is unknown. Our approach combines the robustness of trajectory inference with directional information from RNA velocity, taking into account the gradual and stochastic nature of cellular fate decisions, as well as uncertainty in velocity vectors. On pancreas development data, CellRank automatically detects initial, intermediate and terminal populations, predicts fate potentials and visualizes continuous gene expression trends along individual lineages. Applied to lineage-traced cellular reprogramming data, predicted fate probabilities correctly recover reprogramming outcomes. CellRank also predicts a new dedifferentiation trajectory during postinjury lung regeneration, including previously unknown intermediate cell states, which we confirm experimentally.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
Schlagwörter Rna-seq; Stem-cells; Lineage; Mechanisms; Expression; Mouse; Differentiation; Transcriptome; Regeneration; Progenitors
ISSN (print) / ISBN 1548-7091
e-ISSN 1548-7105
Zeitschrift Nature Methods
Quellenangaben Band: 19, Heft: , Seiten: 159–170 Artikelnummer: , Supplement: ,
Verlag Nature Publishing Group
Verlagsort New York, NY
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Computational Biology (ICB)
Institute of Diabetes and Regeneration Research (IDR)
Lung Health and Immunity (LHI)
Förderungen Bundesministerium fur Bildung und Forschung (BMBF)
Joachim Herz Stiftung
National Cancer Institute (NCI)
Helmholtz Association’s Initiative and Networking Fund through Helmholtz AI
Helmholtz AI
Bayer Foundation
Deutsche Forschungsgemeinschaft (German Research Foundation)
Joachim Herz Stiftung (Joachim Herz Foundation)