pyVIA.plotting_via.plot_sc_lineage_probability

pyVIA.plotting_via.plot_sc_lineage_probability(via_object, embedding=None, idx=None, cmap_name='plasma', dpi=150, scatter_size=None, marker_lineages=[], fontsize=8, alpha_factor=0.9, majority_cluster_population_dict=None, cmap_sankey='rainbow', do_sankey=False)[source]

G is the igraph knn (low K) used for shortest path in high dim space. no idx needed as it’s made on full sample knn_hnsw is the knn made in the embedded space used for query to find the nearest point in the downsampled embedding that corresponds to the single cells in the full graph

Parameters:

  • via_object –

  • embedding (ndarray) – n_samples x 2. embedding is either the full or downsampled 2D representation of the full dataset.

  • idx (list) – if one uses a downsampled embedding of the original data, then idx is the selected indices of the downsampled samples used in the visualization

  • cmap_name –

  • dpi –

  • scatter_size – if None, then auto determined based on n_cells

  • marker_lineages – Default is to use all lineage pathways. other provide a list of lineage number (terminal cluster number).

  • alpha_factor (float) – float transparency

Returns:

fig, axs