commot.tl.cluster_communication
- commot.tl.cluster_communication(adata, database_name=None, pathway_name=None, lr_pair=None, clustering=None, n_permutations=100, random_seed=1, copy=False)
Summarize cell-cell communication to cluster-cluster communication and compute p-values by permutating cell/spot labels.
- Parameters
adata (
AnnData
) – The data matrix of shapen_obs
×n_var
. Rows correspond to cells or positions and columns to genes.database_name (
Optional
[str
]) – Name of the ligand-receptor database. If both pathway_name and lr_pair are None, the cluster signaling through all ligand-receptor pairs is summarized.pathway_name (
Optional
[str
]) – Name of the signaling pathway. If given, the signaling through all ligand-receptor pairs of the given pathway is summarized.lr_pair – A tuple of ligand-receptor pair. If given, only the cluster signaling through this pair is computed.
clustering (
Optional
[str
]) – Name of clustering with the labels stored in.obs[clustering]
.n_permutations (
int
) – Number of label permutations for computing the p-value.random_seed (
int
) – The numpy random_seed for reproducible random permutations.copy (
bool
) – Whether to return a copy of theanndata.AnnData
.
- Returns
adata – Add cluster-cluster communication matrix to
.uns['commot_cluster-databaseX-clustering-ligA-recA']
for the ligand-receptor database named ‘databaseX’ and the cell clustering named ‘clustering’ through the ligand-receptor pair ‘ligA’ and ‘recA’. The first object is the communication score matrix and the second object contains the corresponding p-values. If copy=True, return the AnnData object and return None otherwise.- Return type
anndata.AnnData