kirtiprakash / dynamic-visualization-of-high-dimensional-data

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.

  • 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

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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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