ArticleDevelopment (Cambridge, England)2023
scTOP: physics-inspired order parameters for cellular identification and visualization.
Article in Development (Cambridge, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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13 citing papers in PubMed.
- The chromatin remodeling complex PRC2 safeguards cell fate in alveolar epithelial type 2 cells.bioRxiv : the preprint server for biology · 2026Article
- Parameter-free representations outperform single-cell foundation models on downstream benchmarks.ArXiv · 2026Article
- Parameter-free representations outperform single-cell foundation models on downstream benchmarks.bioRxiv : the preprint server for biology · 2026Article
- Bidirectional fibrogenic cross-talk revealed in a human iPSC-derived epithelial-mesenchymal co-culture model of pulmonary fibrosis.bioRxiv : the preprint server for biology · 2026Article
- Generative epigenetic landscapes map the topology and topography of cell fates.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- The intrinsic dimension of gene expression during cell differentiation.Nucleic acids research · 2025Article
- Article
- Finding signatures of low-dimensional geometric landscapes in high-dimensional cell fate transitions.bioRxiv : the preprint server for biology · 2025Article
- Finding signatures of low-dimensional geometric landscapes in high-dimensional cell fate transitions.ArXiv · 2025Article
- EnhancerNet: a predictive model of cell identity dynamics through enhancer selection.Development (Cambridge, England) · 2024Article
- Generation of human alveolar epithelial type I cells from pluripotent stem cells.Cell stem cell · 2024Article
- Durable alveolar engraftment of PSC-derived lung epithelial cells into immunocompetent mice.Cell stem cell · 2023Article
- Multipotent Embryonic Lung Progenitors: Foundational Units of In Vitro and In Vivo Lung Organogenesis.Advances in experimental medicine and biology · 2023Article
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5 authors.
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Abstract
Advances in single-cell RNA sequencing provide an unprecedented window into cellular identity. The abundance of data requires new theoretical and computational frameworks to analyze the dynamics of differentiation and integrate knowledge from cell atlases. We present 'single-cell Type Order Parameters' (scTOP): a statistical, physics-inspired approach for quantifying cell identity given a reference basis of cell types. scTOP can accurately classify cells, visualize developmental trajectories and assess the fidelity of engineered cells. Importantly, scTOP does this without feature selection, statistical fitting or dimensional reduction (e.g. uniform manifold approximation and projection, principle components analysis, etc.). We illustrate the power of scTOP using human and mouse datasets. By reanalyzing mouse lung data, we characterize a transient hybrid alveolar type 1/alveolar type 2 cell population. Visualizations of lineage tracing hematopoiesis data using scTOP confirm that a single clone can give rise to multiple mature cell types. We assess the transcriptional similarity between endogenous and donor-derived cells in the context of murine pulmonary cell transplantation. Our results suggest that physics-inspired order parameters can be an important tool for understanding differentiation and characterizing engineered cells. scTOP is available as an easy-to-use Python package.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.