commot.tl.group_cluster_communication
- commot.tl.group_cluster_communication(adata, clustering=None, keys=None, p_value_cutoff=0.05, quantile_cutoff=0.99, dissimilarity_method=None, leiden_k=5, leiden_resolution=1.0, leiden_random_seed=1, leiden_n_iterations=- 1, d_global_structure_weights=(0.45, 0.45, 0.1))
Idenfitify groups of cluster-cluster communication with similar pattern.
- Parameters
adata (
AnnData
) – The data matrix with the cluster-cluster communication info stored inadata.uns
.clustering (
Optional
[str
]) – Name of clustering with the labels stored in.obs[clustering]
.keys – A list of keys for the analyzed communication connections as tuples (database_name, ligand, receptor).
quantile_cutoff (
float
) – The quantile cutoff for including an edge. Set to 1 to disable this criterion. The quantile_cutoff and p_value_cutoff works in the “or” logic to avoid missing significant signaling connections.p_value_cutoff (
float
) – The cutoff of p-value to plot an edge.dissimilarity_method (
Optional
[str
]) – The dissimilarity measurement between graphs to use. ‘jaccard’ for Jaccard distance. ‘jaccard_weighted’ for weighted Jaccard distance. ‘global_structure’ for a metric focusing on global structure [Schieber2017].leiden_k (
int
) – Number of neighbors for the knn-graph to be fed to leiden clustering algorithm.leiden_resolution (
float
) – The resolution parameter for the leiden clustering algorithm.leiden_random_seed (
int
) – The random seed for the leiden clustering algorithm.leiden_n_iterations (
int
) – The maximum number of iterations for the leiden algorithm. The algorithm will run until convergence if set to -1.d_global_structure_weights (
tuple
) – The weights for the three terms in the global structural dissimilarity. See [Schieber2017] for more information.
- Returns
keys (list) – The list of keys for the analyzed communication connections as tuples (pathway_name, ligand, receptor).
communication_clusterid (np.ndarray) – The group id of the cluster-cluster communications.
D (np.ndarray) – The dissimilarity matrix for the cluster-cluster communications.
References