cellrefiner.tl.contact_communication

cellrefiner.tl.contact_communication(df_ligrec, adata, sem=None, contact_key='contacts', lr_delimiter='-', heteromeric_delimiter='_')[source]

Contact-base communication inference

Parameters:

  • df_ligrec (DataFrame) – Dataframe where each row corresponds to a ligand-receptor pair with ligands, receptors, and the associated signaling pathways in the three columns, respectively.

  • adata (Anndata) – Anndata object, must contain cell-cell contact information in .obsp[contact_key] if sem is None.

  • sem (SEM, optional) –

    Cell shape model object that contains cell-cell contact matrix and associated AnnData.

    If provided, contact matrix will be obtained from sem.contact_matrix.

    If both sem and adata are provided, adata parameter takes precedence.

  • contact_key (str, default 'contacts') – Key in adata.obsp containing the cell-cell contact matrix (csr_matrix).

  • lr_delimiter (str, default '-') – Delimiter used to construct ligand-receptor pair names in output.

  • heteromeric_delimiter (str, default '_') –

    Delimiter used to separate subunits in heteromeric complexes within df_ligrec.

    For example, if a receptor complex is ‘TGFBR1_TGFBR2’, this parameter should be ‘_’.

Returns:

add .obsp[‘{ligand}{lr_delimiter}{receptor}’], contact-base communication matrix via ligand-receptor pairs (rows are sender cells, columns are receiver cells)

add .obsp[‘{pathway}’], pathway-level contact-base communication matrix

add .obsp[‘total’], sum of all pathway communication matrix

add .obsm[‘sender_signal’], dataFrame with sender communication strengths per cell

add .obsm[‘receiver_signal’], dataFrame with receiver communication strengths per cell

add .uns[‘contact_signal_info’], metadata of the analysis

  • ’lr_pair’: List of L-R pair names

  • ’pathway’: List of pathway names

  • ’total’: [‘total’]

  • ’db’: Filtered ligand-receptor database

Return type:

Sets the following fields in adata

Examples

>>> db_lr = cr.pp.ligand_receptor_database()
>>> db_lr = cr.pp.filter_lr_database(db_lr,adata_cr, min_cell_pct=0.01)
>>> cr.tl.contact_communication(db_lr, adata)