Cell-connectivity-guided trajectory inference from single-cell data

Johannes Smolander, Sini Junttila, Laura L. Elo*

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

3 Citations (Scopus)
18 Downloads (Pure)

Abstract

Motivation: Single-cell RNA-sequencing enables cell-level investigation of cell differentiation, which can be modelled using trajectory inference methods. While tremendous effort has been put into designing these methods, inferring accurate trajectories automatically remains difficult. Therefore, the standard approach involves testing different trajectory inference methods and picking the trajectory giving the most biologically sensible model. As the default parameters are often suboptimal, their tuning requires methodological expertise. Results: We introduce Totem, an open-source, easy-to-use R package designed to facilitate inference of tree-shaped trajectories from single-cell data. Totem generates a large number of clustering results, estimates their topologies as minimum spanning trees, and uses them to measure the connectivity of the cells. Besides automatic selection of an appropriate trajectory, cell connectivity enables to visually pinpoint branching points and milestones relevant to the trajectory. Furthermore, testing different trajectories with Totem is fast, easy, and does not require in-depth methodological knowledge.

Original languageEnglish
Article numberbtad515
Number of pages9
JournalBioinformatics
Volume39
Issue number9
DOIs
Publication statusPublished - Sept 2023
MoE publication typeA1 Journal article-refereed

Fingerprint

Dive into the research topics of 'Cell-connectivity-guided trajectory inference from single-cell data'. Together they form a unique fingerprint.

Cite this