Sign in
BioinformaticsbioRxiv
Preprint

Totem: a user-friendly tool for clustering-based inference of tree-shaped trajectories from single-cell data

Johannes SmolanderiD, Sini JunttilaiD, Laura L. EloiD

Abstract

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. 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.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISSaelens '19Zhang '21Li '26Smolander '21Dong '24Weng '21
71% semantic matchBioinformatics
Wouter Saelens, Robrecht Cannoodt, Helena Todorov+1 more·Nature Biotechnology·Apr 1, 2019· 1,669 citations