Mahdessian, D. et al. Spatiotemporal dissection of the cell cycle with single-cell proteogenomics. Nature 590, 649–654 (2021).

Article  CAS  PubMed  Google Scholar 

Scialdone, A. et al. Computational assignment of cell-cycle stage from single-cell transcriptome data. Methods 85, 54–61 (2015).

Article  CAS  PubMed  Google Scholar 

Skinner, S. O. et al. Single-cell analysis of transcription kinetics across the cell cycle. eLife 5, e12175 (2016).

Article  PubMed  PubMed Central  Google Scholar 

Cao, J., Zhou, W., Steemers, F., Trapnell, C. & Shendure, J. Sci-fate characterizes the dynamics of gene expression in single cells. Nat. Biotechnol. 38, 980–988 (2020).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Qu, R. et al. Decomposing a deterministic path to mesenchymal niche formation by two intersecting morphogen gradients. Dev. Cell 57, 1053–1067 (2022).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Macaulay, I. C. et al. Single-cell RNA-sequencing reveals a continuous spectrum of differentiation in hematopoietic cells. Cell Rep. 14, 966–977 (2016).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Chu, L.-F. et al. Single-cell RNA-seq reveals novel regulators of human embryonic stem cell differentiation to definitive endoderm. Genome Biol. 17, 173 (2016).

Article  PubMed  PubMed Central  Google Scholar 

Chen, R., Wu, X., Jiang, L. & Zhang, Y. Single-cell RNA-seq reveals hypothalamic cell diversity. Cell Rep. 18, 3227–3241 (2017).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Street, K. et al. Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics. BMC Genomics 19, 477 (2018).

Article  PubMed  PubMed Central  Google Scholar 

Cao, J. et al. The single-cell transcriptional landscape of mammalian organogenesis. Nature 566, 496–502 (2019).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Wolf, F. A. et al. PAGA: graph abstraction reconciles clustering with trajectory inference through a topology preserving map of single cells. Genome Biol. 20, 59 (2019).

Article  PubMed  PubMed Central  Google Scholar 

Van den Berge, K. et al. Trajectory-based differential expression analysis for single-cell sequencing data. Nat. Commun. 11, 1201 (2020).

Article  PubMed  PubMed Central  Google Scholar 

Deconinck, L., Cannoodt, R., Saelens, W., Deplancke, B. & Saeys, Y. Recent advances in trajectory inference from single-cell omics data. Curr. Opin. Syst. Biol. 27, 100344 (2021).

Article  CAS  Google Scholar 

Saelens, W., Cannoodt, R., Todorov, H. & Saeys, Y. A comparison of single-cell trajectory inference methods. Nat. Biotechnol. 37, 547–554 (2019).

Article  CAS  PubMed  Google Scholar 

Lange, M. et al. CellRank for directed single-cell fate mapping. Nat. Methods 19, 159–170 (2022).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Qiu, X. et al. Reversed graph embedding resolves complex single-cell trajectories. Nat. Methods 14, 979–982 (2017).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Haghverdi, L., Büttner, M., Wolf, F. A., Buettner, F. & Theis, F. J. Diffusion pseudotime robustly reconstructs lineage branching. Nat. Methods 13, 845–848 (2016).

Article  CAS  PubMed  Google Scholar 

Setty, M. et al. Characterization of cell fate probabilities in single-cell data with Palantir. Nat. Biotechnol. 37, 451–460 (2019).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Lönnberg, T. et al. Single-cell RNA-seq and computational analysis using temporal mixture modeling resolves Th1/Tfh fate bifurcation in malaria. Sci. Immunol. 2, eaal2192 (2017).

Article  PubMed  PubMed Central  Google Scholar 

Tritschler, S. et al. Concepts and limitations for learning developmental trajectories from single cell genomics. Development 146, dev170506 (2019).

Article  PubMed  Google Scholar 

Trapnell, C. et al. The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells. Nat. Biotechnol. 32, 381–386 (2014).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Ruijtenberg, S. & van den Heuvel, S. Coordinating cell proliferation and differentiation: antagonism between cell cycle regulators and cell type-specific gene expression. Cell Cycle 15, 196–212 (2016).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Rougny, A., Paulevé, L., Teboul, M. & Delaunay, F. A detailed map of coupled circadian clock and cell cycle with qualitative dynamics validation. BMC Bioinformatics 22, 240 (2021).

Article  PubMed  PubMed Central  Google Scholar 

Gupta, K. et al. Single-cell analysis reveals a hair follicle dermal niche molecular differentiation trajectory that begins prior to morphogenesis. Dev. Cell 48, 17–31 (2019).

Article  CAS  PubMed  Google Scholar 

Sood, P. et al. Modular, cascade-like transcriptional program of regeneration in stentor. eLife 11, e80778 (2022).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Zhu, H., Zhao, S. D., Ray, A., Zhang, Y. & Li, X. A comprehensive temporal patterning gene network in Drosophila medulla neuroblasts revealed by single-cell RNA sequencing. Nat. Commun. 13, 1247 (2022).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Li, J. et al. Systematic reconstruction of molecular cascades regulating GP development using single-cell RNA-seq. Cell Rep. 15, 1467–1480 (2016).

Article  CAS  PubMed  Google Scholar 

Huizing, G.-J., Peyré, G. & Cantini, L. Optimal transport improves cell–cell similarity inference in single-cell omics data. Bioinformatics 38, 2169–2177 (2022).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Bellazzi, R., Codegoni, A., Gualandi, S., Nicora, G. & Vercesi, E. The gene mover’s distance: single-cell similarity via optimal transport. Preprint at arXiv 10.48550/arXiv.2102.01218 (2021).

Orlova, D. Y. et al. Earth mover’s distance (EMD): a true metric for comparing biomarker expression levels in cell populations. PLoS ONE 11, e0151859 (2016).

Article  PubMed  PubMed Central  Google Scholar 

Schiebinger, G. et al. Optimal-transport analysis of single-cell gene expression identifies developmental trajectories in reprogramming. Cell 176, 928–943 (2019).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Zhang, S., Afanassiev, A., Greenstreet, L., Matsumoto, T. & Schiebinger, G. Optimal transport analysis reveals trajectories in steady-state systems. PLoS Comput. Biol. 17, e1009466 (2021).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Cang, Z. & Nie, Q. Inferring spatial and signaling relationships between cells from single cell transcriptomic data. Nat. Commun. 11, 2084 (2020).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Moriel, N. et al. NovoSpaRc: flexible spatial reconstruction of single-cell gene expression with optimal transport. Nat. Protoc. 16, 4177–4200 (2021).

Article  CAS  PubMed  Google Scholar 

Demetci, P., Santorella, R., Sandstede, B., Noble, W. S. & Singh, R. SCOT: single-cell multi-omics alignment with optimal transport. J. Comput. Biol. 29, 3–18 (2022).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Coifman, R. R. & Lafon, S. Diffusion maps. Appl. Comput. Harmon. Anal. 21, 5–30 (2006).

Article  Google Scholar 

Singer, A. From graph to manifold Laplacian: the convergence rate. App. Comput. Harmon. Anal. 21, 128–134 (2006).

Article  Google Scholar 

Tacke, F. & Randolph, G. J. Migratory fate and differentiation of blood monocyte subsets. Immunobiology 211, 609–618 (2006).