Breaking New Ground in the Landscape of Single-Cell Analysis

Kenji Kamimoto; Samantha A Morris

doi:10.1016/j.cels.2017.12.015

Breaking New Ground in the Landscape of Single-Cell Analysis

Cell Syst. 2018 Jan 24;6(1):5-7. doi: 10.1016/j.cels.2017.12.015.

Authors

Kenji Kamimoto¹, Samantha A Morris²

Affiliations

¹ Department of Developmental Biology, Washington University School of Medicine in St. Louis. 660 S. Euclid Avenue, Campus Box 8103, St. Louis, MO 63110, USA; Department of Genetics, Washington University School of Medicine in St. Louis. 660 S. Euclid Avenue, Campus Box 8103, St. Louis, MO 63110, USA; Center of Regenerative Medicine, Washington University School of Medicine in St. Louis. 660 S. Euclid Avenue, Campus Box 8103, St. Louis, MO 63110, USA.
² Department of Developmental Biology, Washington University School of Medicine in St. Louis. 660 S. Euclid Avenue, Campus Box 8103, St. Louis, MO 63110, USA; Department of Genetics, Washington University School of Medicine in St. Louis. 660 S. Euclid Avenue, Campus Box 8103, St. Louis, MO 63110, USA; Center of Regenerative Medicine, Washington University School of Medicine in St. Louis. 660 S. Euclid Avenue, Campus Box 8103, St. Louis, MO 63110, USA. Electronic address: [email protected].

PMID: 29401450
DOI: 10.1016/j.cels.2017.12.015

Abstract

Here, we outline p-Creode, a new algorithm to construct multi-branching cell lineage trajectories from single-cell data. Application of this platform to diverse sources of single-cell data demonstrates its robustness and scalability, while the discovery of a new origin for rare gut tuft cells showcases the utility of p-Creode.

Publication types

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MeSH terms

Algorithms
Cell Lineage
RNA*
Single-Cell Analysis*

Substances

RNA