commot.tl.communication_spatial_autocorrelation
- commot.tl.communication_spatial_autocorrelation(adata, keys=None, method='Moran', normalize_vf=False, summary='sender', weight_bandwidth=None, weight_k=10, weight_function='triangular', weight_row_standardize=False, n_permutations=999)
Spatial autocorrelation of communication directions.
- Parameters
adata (
AnnData
) – The data matrix with the communication vector fields info stored inadata.ubsm
.keys (
Optional
[list
]) – A list of keys for the analyzed communication connections as tuples (database_name, ligand, receptor).method (
str
) – The method to use. Currently, only Moran’s I [Liu2015] for vectors is implemented.normalize_vf (
bool
) – Whether to normalize the vector field so that the autocorrelation only reflects directions.summary (
str
) – If ‘sender’, use the vector field describing to which direction the signals are sent. If ‘receiver’, use the vector field describing from which direction the signals are from.weight_bandwidth (
Optional
[float
]) – The bandwidth for the kernel to assign knn graph weights. If given, weight_k is ignored.weight_k (
int
) – The number of nearest neighbors for the knn graph.weight_function (
str
) – Kernel functions for assigning weight. Choices: ‘triangular’,’uniform’,’quadratic’,’quartic’,’gaussian’. See libpysal.weights.Kernel of thelibpysal
package for details.weight_row_standardize (
bool
) – Whether to standardize the weights so that the heterogeneity in local cell/position density does not affect the results.n_permutations (
int
) – Number of permutations for computing p-values.
- Returns
keys (list) – The list of keys for the analyzed communication connections as tuples (pathway_name, ligand, receptor).
moranI (np.ndarray) – A vector of moran’s I statistics for corresponding to each key in keys.
p_value (np.ndarray) – The p-values.
References
- Liu2015
Liu, Y., Tong, D., & Liu, X. (2015). Measuring spatial autocorrelation of vectors. Geographical Analysis, 47(3), 300-319.