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Gene trajectory inference for single-cell records by optimum transport metrics

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  • Mahdessian, D. et al. Spatiotemporal dissection of the cell cycle with single-cell proteogenomics. Nature 590649–654 (2021).

    Article CAS PubMed Google Scholar

  • Scialdone, A. et al. Computational assignment of cell-cycle stage from single-cell transcriptome records. Programs 8554–61 (2015).

    Article CAS PubMed Google Scholar

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

    Article PubMed PubMed Central Google Scholar

  • Cao, J., Zhou, W., Steemers, F., Trapnell, C. & Shendure, J. Sci-destiny characterizes the dynamics of gene expression in single cells. Nat. Biotechnol. 38980–988 (2020).

    Article CAS PubMed PubMed Central Google Scholar

  • Qu, R. et al. Decomposing a deterministic route to mesenchymal niche formation by two intersecting morphogen gradients. Dev. Cell 571053–1067 (2022).

    Article CAS PubMed PubMed Central Google Scholar

  • Macaulay, I. C. et al. Single-cell RNA-sequencing reveals a exact spectrum of differentiation in hematopoietic cells. Cell Find. 14966–977 (2016).

    Article CAS PubMed PubMed Central Google Scholar

  • Chu, L.-F. et al. Single-cell RNA-seq reveals unique regulators of human embryonic stem cell differentiation to definitive endoderm. Genome Biol. 17173 (2016).

    Article PubMed PubMed Central Google Scholar

  • Chen, R., Wu, X., Jiang, L. & Zhang, Y. Single-cell RNA-seq reveals hypothalamic cell selection. Cell Find. 183227–3241 (2017).

    Article CAS PubMed PubMed Central Google Scholar

  • Avenue, Okay. et al. Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics. BMC Genomics 19477 (2018).

    Article PubMed PubMed Central Google Scholar

  • Cao, J. et al. The one-cell transcriptional panorama of mammalian organogenesis. Nature 566496–502 (2019).

    Article CAS PubMed PubMed Central Google Scholar

  • Wolf, F. A. et al. PAGA: graph abstraction reconciles clustering with trajectory inference thru a topology preserving draw of single cells. Genome Biol. 2059 (2019).

    Article PubMed PubMed Central Google Scholar

  • Van den Berge, Okay. et al. Trajectory-basically based differential expression prognosis for single-cell sequencing records. Nat. Common. 111201 (2020).

    Article PubMed PubMed Central Google Scholar

  • Deconinck, L., Cannoodt, R., Saelens, W., Deplancke, B. & Saeys, Y. Most contemporary advances in trajectory inference from single-cell omics records. Curr. Opin. Syst. Biol. 27100344 (2021).

    Article CAS Google Scholar

  • Saelens, W., Cannoodt, R., Todorov, H. & Saeys, Y. A comparison of single-cell trajectory inference solutions. Nat. Biotechnol. 37547–554 (2019).

    Article CAS PubMed Google Scholar

  • Lange, M. et al. CellRank for directed single-cell destiny mapping. Nat. Programs 19159–170 (2022).

    Article CAS PubMed PubMed Central Google Scholar

  • Qiu, X. et al. Reversed graph embedding resolves complex single-cell trajectories. Nat. Programs 14979–982 (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. Programs 13845–848 (2016).

    Article CAS PubMed Google Scholar

  • Setty, M. et al. Characterization of cell destiny probabilities in single-cell records with Palantir. Nat. Biotechnol. 37451–460 (2019).

    Article CAS PubMed PubMed Central Google Scholar

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

    Article PubMed PubMed Central Google Scholar

  • Tritschler, S. et al. Ideas and barriers for discovering out developmental trajectories from single cell genomics. Pattern 146dev170506 (2019).

    Article PubMed Google Scholar

  • Trapnell, C. et al. The dynamics and regulators of cell destiny choices are printed by pseudotemporal ordering of single cells. Nat. Biotechnol. 32381–386 (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 form-explicit gene expression. Cell Cycle 15196–212 (2016).

    Article CAS PubMed PubMed Central Google Scholar

  • Rougny, A., Paulevé, L., Teboul, M. & Delaunay, F. A detailed draw of coupled circadian clock and cell cycle with qualitative dynamics validation. BMC Bioinformatics 22240 (2021).

    Article PubMed PubMed Central Google Scholar

  • Gupta, Okay. et al. Single-cell prognosis reveals a hair follicle dermal niche molecular differentiation trajectory that begins outdated to morphogenesis. Dev. Cell 4817–31 (2019).

    Article CAS PubMed Google Scholar

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

    Article CAS PubMed PubMed Central Google Scholar

  • Zhu, H., Zhao, S. D., Ray, A., Zhang, Y. & Li, X. A comprehensive temporal patterning gene community in Drosophila medulla neuroblasts printed by single-cell RNA sequencing. Nat. Common. 131247 (2022).

    Article CAS PubMed PubMed Central Google Scholar

  • Li, J. et al. Systematic reconstruction of molecular cascades regulating GP pattern utilizing single-cell RNA-seq. Cell Find. 151467–1480 (2016).

    Article CAS PubMed Google Scholar

  • Huizing, G.-J., Peyré, G. & Cantini, L. Optimum transport improves cell–cell similarity inference in single-cell omics records. Bioinformatics 382169–2177 (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 by utilizing optimum transport. Preprint at arXiv 10.48550/arXiv.2102.01218 (2021).

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

    Article PubMed PubMed Central Google Scholar

  • Schiebinger, G. et al. Optimum-transport prognosis of single-cell gene expression identifies developmental trajectories in reprogramming. Cell 176928–943 (2019).

    Article CAS PubMed PubMed Central Google Scholar

  • Zhang, S., Afanassiev, A., Greenstreet, L., Matsumoto, T. & Schiebinger, G. Optimum transport prognosis reveals trajectories in well-liked-pronounce programs. PLoS Comput. Biol. 17e1009466 (2021).

    Article CAS PubMed PubMed Central Google Scholar

  • Cang, Z. & Nie, Q. Inferring spatial and signaling relationships between cells from single cell transcriptomic records. Nat. Common. 112084 (2020).

    Article CAS PubMed PubMed Central Google Scholar

  • Moriel, N. et al. NovoSpaRc: flexible spatial reconstruction of single-cell gene expression with optimum transport. Nat. Protoc. 164177–4200 (2021).

    Article CAS PubMed Google Scholar

  • Demetci, P., Santorella, R., Sandstede, B., Noble, W. S. & Singh, R. SCOT: single-cell multi-omics alignment with optimum transport. J. Comput. Biol. 293–18 (2022).

    Article CAS PubMed PubMed Central Google Scholar

  • Coifman, R. R. & Lafon, S. Diffusion maps. Appl. Comput. Harmon. Anal. 215–30 (2006).

    Article Google Scholar

  • Singer, A. From graph to manifold Laplacian: the convergence charge. App. Comput. Harmon. Anal. 21128–134 (2006).

    Article Google Scholar

  • Tacke, F. & Randolph, G. J. Migratory destiny and differentiation of blood monocyte subsets. Immunobiology 211609–618 (2006).

    Article CAS PubMed Google Scholar

  • Van de Veerdonk, F. L. & Netea, M. G. Diversity: an indicator of monocyte society. Immunity 33289–291 (2010).

    Article PubMed Google Scholar

  • Patel, A. A. et al. The destiny and lifespan of human monocyte subsets in well-liked pronounce and systemic irritation. J. Exp. Med. 2141913–1923 (2017).

    Article CAS PubMed PubMed Central Google Scholar

  • Chitu, V. & Stanley, E. R. Colony-stimulating element-1 in immunity and irritation. Curr. Opin. Immunol. 1839–48 (2006).

    Article CAS PubMed Google Scholar

  • Imhof, B. A. & Dunon, D. Leukocyte migration and adhesion. Adv. Immunol. 58345–416 (1995).

    CAS PubMed Google Scholar

  • Ghebrehiwet, B., Hosszu, Okay. Okay., Valentino, A., Ji, Y. & Peerschke, E. I. Monocyte expressed macromolecular C1 and C1q receptors as molecular sensors of hazard: implications in SLE. Entrance. Immunol. 5278 (2014).

    Article PubMed PubMed Central Google Scholar

  • Heger, L. et al. Subsets of CD1c+ DCs: dendritic cell versus monocyte lineage. Entrance. Immunol. 11559166 (2020).

    Article CAS PubMed PubMed Central Google Scholar

  • Higashi, N. et al. The macrophage C-form lectin explicit for galactose/N-acetylgalactosamine is an endocytic receptor expressed on monocyte-derived immature dendritic cells. J. Biol. Chem. 27720686–20693 (2002).

    Article CAS PubMed Google Scholar

  • Myung, P., Andl, T. & Atit, R. The origins of pores and skin selection: classes from dermal fibroblasts. Pattern 149dev200298 (2022).

    Article CAS PubMed PubMed Central Google Scholar

  • Chen, D., Jarrell, A., Guo, C., Lang, R. & Atit, R. Dermal β-catenin project per epidermal Wnt ligands is required for fibroblast proliferation and hair follicle initiation. Pattern 1391522–1533 (2012).

    Article CAS PubMed PubMed Central Google Scholar

  • Fu, J. & Hsu, W. Epidermal Wnt controls hair follicle induction by orchestrating dynamic signaling crosstalk between the epidermis and dermis. J. Make investments. Dermatol. 133890–898 (2013).

    Article CAS PubMed Google Scholar

  • Hastie, T. J. Generalized Additive Gadgetspp. 249–307 (Routledge, 2017).

  • Picket, S. mgcv: Mixed GAM Computation Automobile with GCV/AIC/REML Smoothness Estimation (College of Bath, 2012).

  • Pott, S. & Lieb, J. D. Single-cell ATAC–seq: strength in numbers. Genome Biol. 16172 (2015).

    Article PubMed PubMed Central Google Scholar

  • Ståhl, P. L. et al. Visualization and prognosis of gene expression in tissue sections by spatial transcriptomics. Science 35378–82 (2016).

    Article PubMed Google Scholar

  • Macaulay, I. C., Ponting, C. P. & Voet, T. Single-cell multiomics: rather a lot of measurements from single cells. Trends Genet. 33155–168 (2017).

    Article CAS PubMed PubMed Central Google Scholar

  • Balasubramanian, M. & Schwartz, E. L. The isomap algorithm and topological balance. Science 2957 (2002).

    Article PubMed Google Scholar

  • Bernstein, M., De Silva, V., Langford, J. C. & Tenenbaum, J. B. Graph Approximations to Geodesics on Embedded Manifolds Technical Document (Department of Psychology, Stanford College, 2000).

  • Dassule, H. R., Lewis, P., Bei, M., Maas, R. & McMahon, A. P. Sonic hedgehog regulates enhance and morphogenesis of the teeth. Pattern 1274775–4785 (2000).

    Article CAS PubMed Google Scholar

  • Picket worker, A. C., Rao, S., Wells, J. M., Campbell, Okay. & Lang, R. A. Generation of mice with a conditional null allele for Wntless. Genesis 48554–558 (2010).

    Article CAS PubMed PubMed Central Google Scholar

  • Satija, R., Farrell, J. A., Gennert, D., Schier, A. F. & Regev, A. Spatial reconstruction of single-cell gene expression records. Nat. Biotechnol. 33495–502 (2015).

    Article CAS PubMed PubMed Central Google Scholar

  • Santos, A., Wernersson, R. & Jensen, L. J. Cyclebase 3.0: a multi-organism database on cell-cycle rules and phenotypes. Nucleic Acids Res. 43D1140–D1144 (2015).

    Article CAS PubMed Google Scholar

  • Liu, Z. et al. Reconstructing cell cycle pseudo time-assortment by utilizing single-cell transcriptome records. Nat. Common. 822 (2017).

    Article PubMed PubMed Central Google Scholar

  • Günesdogan, U., Jäckle, H. & Herzig, A. Histone provide regulates s share timing and cell cycle progression. eLife 3e02443 (2014).

    Article PubMed PubMed Central Google Scholar

  • Moon, Okay. R. et al. Visualizing structure and transitions in excessive-dimensional organic records. Nat. Biotechnol. 371482–1492 (2019).

    Article CAS PubMed PubMed Central Google Scholar

  • Picket, S. & Picket, M. S. Kit ‘mgcv’. pupil.google.com/citations?view_op=view_citation&hl=it&user=EskiIyEAAAAJ&citation_for_view=EskiIyEAAAAJ:kh2fBNsKQNwC (2015).

  • Bergen, V., Lange, M., Peidli, S., Wolf, F. A. & Theis, F. J. Generalizing RNA velocity to transient cell states thru dynamical modeling. Nat. Biotechnol. 381408–1414 (2020).

    Article CAS PubMed Google Scholar

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