@article {Zhang2021.03.02.433630, author = {Stephen Zhang and Anton Afanassiev and Laura Greenstreet and Tetsuya Matsumoto and Geoffrey Schiebinger}, title = {Optimal transport analysis reveals trajectories in steady-state systems}, elocation-id = {2021.03.02.433630}, year = {2021}, doi = {10.1101/2021.03.02.433630}, publisher = {Cold Spring Harbor Laboratory}, abstract = {Understanding how cells change their identity and behaviour in living systems is an important question in many fields of biology. The problem of inferring cell trajectories from single-cell measurements has been a major topic in the single-cell analysis community, with different methods developed for equilibrium and non-equilibrium systems (e.g. haematopoeisis vs. embryonic development). We show that optimal transport analysis, a technique originally designed for analysing time-courses, may also be applied to infer cellular trajectories from a single snapshot of a population in equilibrium. Therefore optimal transport provides a unified approach to inferring trajectories, applicable to both stationary and non-stationary systems. Our method, StationaryOT, is mathematically motivated in a natural way from the hypothesis of a Waddington{\textquoteright}s epigenetic landscape. We implemented StationaryOT as a software package and demonstrate its efficacy when applied to simulated data as well as single-cell data from Arabidopsis thaliana root development.Competing Interest StatementThe authors have declared no competing interest.}, URL = {https://www.biorxiv.org/content/early/2021/03/08/2021.03.02.433630}, eprint = {https://www.biorxiv.org/content/early/2021/03/08/2021.03.02.433630.full.pdf}, journal = {bioRxiv} }