netmap.downstream.regulon.select_top_edges

netmap.downstream.regulon.select_top_edges(gene_inter_adata, adata, top_per_source=10, col_cluster='leiden_remap', min_reg_size=10, verbose=True, return_copy=False, tf_column=None, min_edge_support=0.5)[source]

Select the top-attribution edges per source TF per cluster.

For each cluster, computes per-cell mean attribution across cluster cells for each source gene’s edges, filters by min_edge_support from the mask layer, and keeps the top top_per_source edges per source. Returns the processed edge dict.

Parameters:

  • gene_inter_adata (anndata.AnnData) – GRN AnnData with X (attributions), layers['mask'], and cluster labels in obs.

  • adata (anndata.AnnData) – Expression AnnData (currently unused, reserved).

  • top_per_source (int) – Max edges per source TF per cluster. Defaults to 10.

  • col_cluster (str) – Cluster column in obs. Defaults to 'leiden_remap'.

  • min_reg_size (int) – Minimum edges required to keep a regulon. Defaults to 10.

  • verbose (bool) – Print progress. Defaults to True.

  • return_copy (bool) – Unused, reserved. Defaults to False.

  • tf_column (str or None) – var column flagging TF rows; restricts sources to TFs.

  • min_edge_support (float) – Minimum mask fraction required per edge. Defaults to 0.5.

Returns:

Nested result from process_cell_edges().

Return type:

dict