scHopfield.plotting.plot_network_centrality_rank

scHopfield.plotting.plot_network_centrality_rank(adata: AnnData, metric: str = 'degree_centrality_all', clusters: str | List[str] | None = None, cluster_key: str = 'cell_type', n_genes: int = 50, colors: Dict[str, str] | None = None, skip_first_n: int = 0, figsize: tuple | None = None, ax: Axes | None = None) → Axes[source]

Plot top genes ranked by network centrality score.

Parameters:

  • adata (AnnData) – Annotated data object with computed centrality metrics

  • metric (str, optional (default: 'degree_centrality_all')) – Centrality metric to plot. Available: ‘degree_all’, ‘degree_centrality_all’, ‘degree_in’, ‘degree_centrality_in’, ‘degree_out’, ‘degree_centrality_out’, ‘betweenness_centrality’, ‘eigenvector_centrality’

  • clusters (str or list, optional) – Cluster(s) to plot. If None, plots all clusters

  • cluster_key (str, optional (default: 'cell_type')) – Key in adata.obs for cluster labels

  • n_genes (int, optional (default: 50)) – Number of top genes to show

  • colors (dict, optional) – Colors for each cluster

  • skip_first_n (int, optional (default: 0)) – Skip top N genes

  • figsize (tuple, optional) – Figure size

  • ax (plt.Axes, optional) – Axes to plot on

Returns:

Axes with plot

Return type:

plt.Axes