omicverse.space.moranI¶
- omicverse.space.moranI(adata, connectivity_key='spatial_connectivities', genes=None, transformation=True, n_perms=None, two_tailed=False, corr_method='fdr_bh', layer=None, seed=None, copy=False, auto_spatial_neighbors=False, n_neighs=6, radius=None, spatial_key='spatial')[source]¶
Compute Moran’s I spatial autocorrelation for gene expression.
A convenience wrapper around
spatial_autocorr()withmode='moran'. Set auto_spatial_neighbors toTrueto build the spatial neighborhood graph automatically viaspatial_neighbors()when the connectivity matrix is missing fromadata.obsp.- Parameters:
adata – AnnData with spatial coordinates in
adata.obsmand optionally a precomputed connectivity inadata.obsp.connectivity_key (
str(default:'spatial_connectivities')) – Key of the spatial connectivity matrix inadata.obsp. Default: ‘spatial_connectivities’.genes (default:
None) – Gene names/indices to test.Nonetests all genes. Default: None.transformation (
bool(default:True)) – Row-normalise the weight matrix before scoring. Default: True.n_perms (default:
None) – Permutations for empirical p-values;Noneuses only the analytical value. Default: None.two_tailed (
bool(default:False)) – Two-tailed z-score test. Default: False.corr_method (default:
'fdr_bh') – Multiple-testing correction ('fdr_bh','bonferroni', …). Default: ‘fdr_bh’.layer (default:
None) – Expression layer to use;Noneusesadata.X. Default: None.seed (default:
None) – Random seed for permutation reproducibility. Default: None.copy (
bool(default:False)) – Return the result DataFrame. Default: False.auto_spatial_neighbors (
bool(default:False)) – Automatically build the spatial neighborhood graph if connectivity_key is absent fromadata.obsp. Default: False.n_neighs (
int(default:6)) – Number of KNN neighbours used when auto_spatial_neighbors isTrue. Default: 6.radius (default:
None) – Radius for radius-based graph when auto_spatial_neighbors isTrue. Default: None.spatial_key (
str(default:'spatial')) – Key inadata.obsmholding 2-D coordinates. Default: ‘spatial’.
- Returns:
Moran’s I results with columns
I,pval_norm, and optionallypval_sim,pval_z_sim,pval_adj. Also stored inadata.uns['moranI'].- Return type:
DataFrame
Examples
>>> import omicverse as ov >>> ov.space.spatial_neighbors(adata, n_neighs=6) >>> df = ov.space.moranI(adata) >>> df.head() >>> # One-liner with auto graph building >>> df = ov.space.moranI(adata, auto_spatial_neighbors=True)