The cell-level analysis of cell differentiation made possible by single-cell RNA sequencing can be modelled using trajectory inference techniques. Although a lot of work has gone into inventing these algorithms, it is still challenging to infer precise trajectories automatically.The typical strategy therefore entails testing various trajectory inference techniques and selecting the trajectory producing the best biologically plausible model. The tweaking of the default parameters demands methodological skill because they are frequently not ideal.
The authors present Totem, a free and simple-to-use R programme that makes it easier to predict tree-shaped trajectories from single-cell data. Totem produces a lot of clustering findings, calculates their topologies as minimal spanning trees, and then uses them to gauge the cell connection. Cell connectivity allows for the visual identification of branching points and milestones pertinent to the trajectory in addition to the automatic selection of an acceptable route. Additionally, using Totem to test various paths is quick, simple, and necessitates little scientific expertise.
The R package for Totem can be found at https://github.com/elolab/Totem.
Reference:
Johannes Smolander et. al. (2023)Gene expression Cell-connectivity-guided trajectory inference from single-cell data.Bioinformatics 39(9):btad 515