API Reference¶

Config¶

Global configurations for spatialtis

`read_ROIs`	Extract single cell expression matrix and geometry information from stacked images and masks
`get_result`	Read spatialtis result from AnnData.uns as pandas.DataFrame object
`transform_points`	Transform normal coordination in AnnData.obs to wkt-format
`transform_shapes`	Transform normal coordination in AnnData.obs to wkt-format

`cell_components`	Count the proportion of each types of cells in each group
`cell_density`	Calculating cell density in each ROI
`cell_morphology`	Cell morphology variation between different groups
`cell_co_occurrence`	The likelihood of two type of cells occur simultaneously in a ROI

`find_neighbors`	To find the neighbors of each cell
`hotspot`	Getis-ord hotspot detection
`cell_dispersion`	Cell distribution pattern
`cell_interaction`	Profiling cell-cell interaction using permutation test
`spatial_heterogeneity`	Evaluate tissue heterogeneity based on entropy
`spatial_autocorr`	Spatial auto-correlation for every markers
`spatial_enrichment`	Profiling markers spatial enrichment using permutation test
`spatial_coexp`	Identifying spatial co-expression markers using correlation
`NCD_marker`	Identify neighbor cells dependent marker
`NMD_marker`	Identify neighbor markers dependent marker
`somde`	This is a wrapper around somde
`GCNG`	A pytorch reimplementation of GCNG

The base class for all analysis function