Velocity Ligand Importance Heatmap — plot_ligand_importance

Visualize the ligands and their feature importances towards the velocity clusters, in python.

Usage

plot_ligand_importance_heatmap(
  adata,
  n_top_ligands = 5,
  colorscale = "inferno",
  velocity_clusters = None,
  filename = "velocity_importances.png",
  figsize = None,
  rescale_columns = True,
  return_plot = True
)

Arguments

adata: Anndata object that has been analyzed with python function get_velocity_ligands
n_top_ligands: Number of top ligands to visualize. Default 5.
colorscale: Name of a color palette to be passed to seaborn.
velocity_clusters: Character vector of velocity clusters to include in the plot. Default None - include all velocity clusters,
filename: Filename to save as.
figsize: Tuple to pass to matplotlib figure(). Default (10,8)
rescale_columns: Boolean. If TRUE, rescales all ligand importances between 0 and 1. This is recommended because random forest importances are relative.
return_plot: Boolean. If TRUE, returns a matplotlib ax object.

Value

a matplotlib ax object, if return_plot is True.