Optimal transport analysis reveals trajectories in steady-state systems.

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 that is applicable to both stationary and non-stationary systems. Our method, StationaryOT, is mathematically motivated in a natural way from the hypothesis of a Waddington's epigenetic landscape. We implement StationaryOT as a software package and demonstrate its efficacy in applications to simulated data as well as single-cell data from Arabidopsis thaliana root development.

Abstract licence: CC BY

1. 7.

   Quantification of cell identity from single-cell gene expression profiles · 2015

2. 12.

   Stem Cell Differentiation as a Non-Markov Stochastic Process · 2017

3. 15.

   Comparative genome and phenotypic analysis of three Clostridioides difficile strains isolated from a single patient provide insight into multiple infection of C. difficile · 2018

4. 24.

   PAGA: graph abstraction reconciles clustering with trajectory inference through a topology preserving map of single cells · 2019

5. 28.

   Performance of neural network basecalling tools for Oxford Nanopore sequencing · 2019

6. 29.

   Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics · 2018

34 more references, whose wording the paper’s licence keeps private.

• Brassinosteroid gene regulatory networks at cellular resolution in the Arabidopsis root · 2023

• Corrected

  Learning single-cell perturbation responses using neural optimal transport · 2023

• RNA velocity unraveled · 2022

• A single-cell Arabidopsis root atlas reveals developmental trajectories in wild-type and cell identity mutants · 2022

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.