scHopfield.tools.get_eigenanalysis_table

scHopfield.tools.get_eigenanalysis_table(adata: AnnData, cluster_key: str = 'cell_type', n_genes: int = 20, order: List[str] | None = None) → DataFrame[source]

Create formatted table with top genes from extreme eigenvectors.

Parameters:

  • adata (AnnData) – Annotated data object with computed eigenanalysis

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

  • n_genes (int, optional (default: 20)) – Number of top genes to include per cluster

  • order (list, optional) – Order of clusters in table. If None, uses all clusters

Returns:

DataFrame with MultiIndex columns (cluster, [‘+EV gene’, ‘+EV value’, ‘-EV gene’, ‘-EV value’])

Return type:

pd.DataFrame