spatialtis.cell_dispersion

spatialtis.cell_dispersion(data, method='id', min_cells=10, pval=0.01, r=None, resample=1000, quad=None, rect_side=None, export_key='cell_dispersion', **kwargs)

Cell distribution pattern

There are three type of distribution pattern (0 if no cells)

• Random (1)

• Regular (2)

• Cluster (3)

Three methods are provided

• Index of Dispersion

• Morisita’s index of dispersion

• Clark and Evans aggregation index

Notice that clark evans’ index usually failed to detect local aggregation.

	Random	Regular	Cluster
Index of dispersion: ID	ID = 1	ID < 1	ID > 1
Morisita’s index of dispersion: I	I = 1	I < 1	I > 1
Clark and Evans aggregation index: R	R = 1	R > 1	R < 1

Parameters

dataAnnData

The AnnData to work with.

method{‘id’, ‘morisita’, ‘clark_evans’}, default: ‘id’

min_cellsint, default: 10

The minimum number of the specific type of cells in a ROI to perform analysis.

pvalfloat

The p-value threshold to determine significance.

rfloat

Parameters for method=’id’, determine diameter of sample window, default will take 1/10 of the shortest side of the ROI as the diameter.

resampleint, default: 1000

Parameters for method=’id’, the number of random permutations to perform.

quadtuple of int, default: (10, 10)

Parameters for method=’morisita’, A tuple (X, Y), Use a grid that is X * Y to tessellation your ROI.

rect_sidetuple of float

Parameters for method=’morisita’, A tuple (X, Y), Use many rectangles with X * Y side to tessellation your ROI.

export_keystr

The key used to store result.

**kwargs

Config for the analysis, for details check spatialtis.abc.AnalysisBase.