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bioRxiv · 10.1101/2023.12.07.570655

CytoSimplex: Visualizing Single-cell Fates and Transitions on a Simplex

Liu, J.·Wang, Y.·Li, C.·Gu, Y.·Ono, N.·Welch, J. D.
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Abstract

SummaryCells differentiate to their final fates along unique trajectories, often involving multi-potent progenitors that can produce multiple terminally differentiated cell types. Recent developments in single-cell transcriptomic and epigenomic measurement provide tremendous opportunities for mapping these trajectories. The visualization of single-cell data often relies on dimension reduction methods such as UMAP to simplify high-dimensional single-cell data down into an understandable two-dimensional (2D) form. However, these visualization methods can be misleading and often do not effectively represent the direction of cell differentiation. To address these limitations, we developed a new approach that places each cell from a single-cell dataset within a simplex whose vertices correspond to terminally differentiated cell types. Our approach can quantify and visualize current cell fate commitment and future cell potential. We developed CytoSimplex, a standalone open-source package implemented in R and Python that provides simple and intuitive visualizations of cell differentiation in 2D ternary and three-dimensional (3D) quaternary plots. We believe that CytoSimplex can help researchers gain a better understanding of cell type transitions in specific tissues and characterize developmental processes. Availability and implementationThe R version of CytoSimplex is available on Github at https://github.com/welch-lab/CytoSimplex. The Python version of CytoSimplex is available on Github at https://github.com/welch-lab/pyCytoSimplex.

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Liu, J., Wang, Y., Li, C., Gu, Y., Ono, N., Welch, J. D.. 2023-12-08. CytoSimplex: Visualizing Single-cell Fates and Transitions on a Simplex. https://doi.org/10.1101/2023.12.07.570655

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