Reconstructing temporal and spatial dynamics from single-cell pseudotime using prior knowledge of real scale cell densities

Scientific Reports. 2020;10(1):1-10 DOI 10.1038/s41598-020-60400-z

 

Journal Homepage

Journal Title: Scientific Reports

ISSN: 2045-2322 (Online)

Publisher: Nature Publishing Group

LCC Subject Category: Medicine | Science

Country of publisher: United Kingdom

Language of fulltext: English

Full-text formats available: PDF, HTML

 

AUTHORS


Karsten Kuritz (Institute for Systems Theory and Automatic Control, University of Stuttgart)

Daniela Stöhr (Institute of Cell Biology and Immunology, University of Stuttgart)

Daniela Simone Maichl (Institute of Cell Biology and Immunology, University of Stuttgart)

Nadine Pollak (Institute for Systems Theory and Automatic Control, University of Stuttgart)

Markus Rehm (Institute of Cell Biology and Immunology, University of Stuttgart)

Frank Allgöwer (Institute for Systems Theory and Automatic Control, University of Stuttgart)

EDITORIAL INFORMATION

Blind peer review

Editorial Board

Instructions for authors

Time From Submission to Publication: 20 weeks

 

Abstract | Full Text

Abstract Modern cytometry methods allow collecting complex, multi-dimensional data sets from heterogeneous cell populations at single-cell resolution. While methods exist to describe the progression and order of cellular processes from snapshots of such populations, these descriptions are limited to arbitrary pseudotime scales. Here we describe MAPiT, an universal transformation method that recovers real-time dynamics of cellular processes from pseudotime scales by utilising knowledge of the distributions on the real scales. As use cases, we applied MAPiT to two prominent problems in the flow-cytometric analysis of heterogeneous cell populations: (1) recovering the kinetics of cell cycle progression in unsynchronised and thus unperturbed cell populations, and (2) recovering the spatial arrangement of cells within multi-cellular spheroids prior to spheroid dissociation for cytometric analysis. Since MAPiT provides a theoretic basis for the relation of pseudotime values to real temporal and spatial scales, it can be used broadly in the analysis of cellular processes with snapshot data from heterogeneous cell populations.