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Tritschler, S. ; Büttner, M. ; Fischer, D.S. ; Lange, M. ; Bergen, V. ; Lickert, H. ; Theis, F.J.

Concepts and limitations for learning developmental trajectories from single cell genomics.

Development 146:dev170506 (2019)
Verlagsversion DOI PMC
Free by publisher
Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
Single cell genomics has become a popular approach to uncover the cellular heterogeneity of progenitor and terminally differentiated cell types with great precision. This approach can also delineate lineage hierarchies and identify molecular programmes of cell-fate acquisition and segregation. Nowadays, tens of thousands of cells are routinely sequenced in single cell-based methods and even more are expected to be analysed in the future. However, interpretation of the resulting data is challenging and requires computational models at multiple levels of abstraction. In contrast to other applications of single cell sequencing, where clustering approaches dominate, developmental systems are generally modelled using continuous structures, trajectories and trees. These trajectory models carry the promise of elucidating mechanisms of development, disease and stimulation response at very high molecular resolution. However, their reliable analysis and biological interpretation requires an understanding of their underlying assumptions and limitations. Here, we review the basic concepts of such computational approaches and discuss the characteristics of developmental processes that can be learnt from trajectory models.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Review
Korrespondenzautor
Schlagwörter Computational Approaches ; Developmental Trajectories ; Pseudotime ; Single Cell Genomics ; Trajectory Inference; Regulatory Network Inference; Rna-sequencing Data; Spatial Transcriptomics; Blood Stem; Dynamics; Reveals; Reconstruction; Heterogeneity; Information; Mechanisms
ISSN (print) / ISBN 0950-1991
e-ISSN 1477-9129
Zeitschrift Development / Company of Biologists
Quellenangaben Band: 146, Heft: 12, Seiten: , Artikelnummer: dev170506 Supplement: ,
Verlag Company of Biologists
Verlagsort Bidder Building, Station Rd, Histon, Cambridge Cb24 9lf, England
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Computational Biology (ICB)
Institute of Diabetes and Regeneration Research (IDR)