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dynamic-visualization-of-high-dimensional-data

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Jupyter notebooks and Python scripts associated with experiments and analyses presented in "Dynamic visualization of high-dimensional data" by Sun et al. (2022).

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# Dynamic visualization of high-dimensional data

### Eric Sun

All Jupyter notebooks and Python scripts for generating figures, experiments, and analyses in "Dynamic visualization of high-dimensional data" by Sun et al., 2022. The paper can be found here: https://doi.org/10.1038/s43588-022-00380-4

- **Figure1_visualizations.ipynb** contains code for generating Figure 1 panels and associated panels in the Extended Data
- **Figure2_scores_theory.ipynb** contains code for generating Figure 2 panels and associated panels in the Extended Data
- **Figure3_scores_applications.ipynb** contains code for generating Figure 3 panels and associated panels in the Extended Data
- **Figure4_rna_velocity.ipynb** contains code for generating Figure 4 panels and associated panels in the Extended Data
- **Supplement.ipynb** contains code for generating additional Extended Data figure panels
- **process_single_cell_data.ipynb** contains code for preprocessing of some of the single-cell datasets used in the experiments
- **scg_scripts/** contains Python scripts for doing some of the heavier computations/simulations to get results for visualization in the notebooks above.
- **Supplementary_Videos.zip** contains HTML and GIF files corresponding to dynamic visualizations in Figure 1 of the manuscript.

The Python package for the associated DynamicViz software can be found at: https://github.com/sunericd/dynamicviz

If you find this code useful, please cite the following paper:

Sun, E.D., Ma, R. & Zou, J. Dynamic visualization of high-dimensional data. Nat Comput Sci 3, 86–100 (2023). https://doi.org/10.1038/s43588-022-00380-4

dynamic-visualization-of-high-dimensional-data

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