mechanochat.preprocessing.ligand_receptor_database#

mechanochat.preprocessing.ligand_receptor_database(database: Literal['CellChat', 'CellPhoneDB'] = 'CellChat', species: Literal['mouse', 'human'] = 'mouse', signaling_type: Literal['Secreted Signaling', 'Cell-Cell Contact', 'ECM-Receptor'] = 'Secreted Signaling') → DataFrame[source]#

Extract ligand-receptor pairs from LR database.

Parameters:

  • database – The name of the ligand-receptor database. Use ‘CellChat’ for CellChatDB [Jin2021] of ‘CellPhoneDB’ for CellPhoneDB_v4.0 [Efremova2020].

  • species – The species of the ligand-receptor pairs. Choose between ‘mouse’ and ‘human’.

  • signaling_type – The type of signaling. Choose from ‘Secreted Signaling’, ‘Cell-Cell Contact’, and ‘ECM-Receptor’ for CellChatDB or ‘Secreted Signaling’ and ‘Cell-Cell Contact’ for CellPhoneDB_v4.0. If None, all pairs in the database are returned.

Returns:

df_ligrec (pandas.DataFrame) – A pandas DataFrame of the LR pairs. Columns: ‘Ligands’, ‘Receptor’, ‘Pathway’, ‘Type’.

References

[Jin2021]

Jin, S., Guerrero-Juarez, C. F., Zhang, L., Chang, I., Ramos, R., Kuan, C. H., … & Nie, Q. (2021). Inference and analysis of cell-cell communication using CellChat. Nature communications, 12(1), 1-20.

[Efremova2020]

Efremova, M., Vento-Tormo, M., Teichmann, S. A., & Vento-Tormo, R. (2020). CellPhoneDB: inferring cell–cell communication from combined expression of multi-subunit ligand–receptor complexes. Nature protocols, 15(4), 1484-1506.