scimap.tl.spatial_count

Short description

The spatial_count function allows users to compute the proportion of a categorical variable (e.g. cell-types) within the local neighbourhood of each cell.

The function supports two methods to define a local neighbourhood
Radius method: Can be used to identifies the neighbours within a user defined radius for every cell. KNN method: Can be used to identifies the neighbours based on K nearest neigbours for every cell

The resultant proportion matrix is saved with adata.uns. This can be further clustered to identify similar neighbourhoods.

Parameters

adata : AnnData Object

x_coordinate : float, required (The default is 'X_centroid')
Column name containing the x-coordinates values.

y_coordinate : float, required (The default is 'Y_centroid')
Column name containing the y-coordinates values.

phenotype : string, required (The default is 'phenotype')
Column name of the column containing the phenotype information. It could also be any categorical assignment given to single cells.

method : string, optional (The default is 'radius')
Two options are available: a) 'radius', b) 'knn'. a) radius - Identifies the neighbours within a given radius for every cell. b) knn - Identifies the K nearest neigbours for every cell.

radius : int, optional (The default is 30)
The radius used to define a local neighbhourhood.

knn : int, optional (The default is 10)
Number of cells considered for defining the local neighbhourhood.

imageid : string, optional (The default is 'imageid')
Column name of the column containing the image id.

subset : string, optional (The default is None)
imageid of the image to be subsetted for analyis.

label : string, optional (The default is 'spatial_count')
Key for the returned data, stored in adata.uns.

Returns AnnData object with the results stored in adata.uns['spatial_count'].

Example

# Running the radius method
adata = sm.tl.spatial_count (adata,x_coordinate='X_centroid',y_coordinate='Y_centroid',
                       phenotype='phenotype',method='radius',radius=30,
                       imageid='imageid',subset=None,label='spatial_count_radius')

# Running the knn method
adata = sm.tl.spatial_count (adata,x_coordinate='X_centroid',y_coordinate='Y_centroid',
                       phenotype='phenotype',method='knn',knn=10,
                       imageid='imageid',subset=None,label='spatial_count_knn')