scSLAT.model.loaddata.load_anndatas

scSLAT.model.loaddata.load_anndatas(adatas, feature='DPCA', dim=50, self_loop=False, join='inner', backend='sklearn', singular=True, check_order=True, n_top_genes=2500)[source]

Transfer adatas with spatial info into PyG datasets

Return type:

typing.List[torch_geometric.data.data.Data]

Parameters:

adatas

List of Anndata objects

feature

use which data to build graph - PCA (default) - DPCA (For batch effect correction) - Harmony (For batch effect correction) - GLUE (NOTE: only suitable for multi-omics integration)

dim

dimension of embedding, works for [‘PCA’, ‘DPCA’, ‘Harmony’, ‘GLUE’]

self_loop

whether to add self loop on graph

join

how to concatenate two adata

backend

backend to calculate DPCA

singular

whether to multiple singular value in DPCA

check_order

whether to check the order of adata1 and adata2

n_top_genes

number of highly variable genes

Note:

Only support ‘Spatial_Net’ which store in adata.uns yet