spateo.tools.cluster.cluster_spagcn
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Module Contents#
Functions#
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Integrating gene expression and spatial location to identify spatial domains via SpaGCN. |
- spateo.tools.cluster.cluster_spagcn.spagcn_vanilla(adata: anndata.AnnData, spatial_key: str = 'spatial', key_added: str | None = 'spagcn_pred', n_pca_components: int | None = None, e_neigh: int = 10, resolution: float = 0.4, n_clusters: int | None = None, refine_shape: Literal[hexagon, square] = 'hexagon', p: float = 0.5, seed: int = 100, numIterMaxSpa: int = 2000, copy: bool = False) anndata.AnnData | None [source]#
Integrating gene expression and spatial location to identify spatial domains via SpaGCN. Original Code Repository: https://github.com/jianhuupenn/SpaGCN
- Reference:
Jian Hu, Xiangjie Li, Kyle Coleman, Amelia Schroeder, Nan Ma, David J. Irwin, Edward B. Lee, Russell T. Shinohara & Mingyao Li. SpaGCN: Integrating gene expression, spatial location and histology to identify spatial domains and spatially variable genes by graph convolutional network. Nature Methods volume 18, pages1342–1351 (2021)
- Parameters:
- adata
An Anndata object after normalization.
- spatial_key
the key in .obsm that corresponds to the spatial coordinate of each bucket.
- key_added
adata.obs key under which to add the cluster labels. The initial clustering results of SpaGCN are under key_added, and the refined clustering results are under f’{key_added}_refined’.
- n_pca_components
Number of principal components to compute. If n_pca_components == None, the value at the inflection point of the PCA curve is automatically calculated as n_comps.
- e_neigh
Number of nearest neighbor in gene expression space. Used in dyn.pp.neighbors(adata, n_neighbors=e_neigh).
- resolution
Resolution in the Louvain clustering method. Used when `n_clusters`==None.
- n_clusters
Number of spatial domains wanted. If n_clusters != None, the suitable resolution in the initial Louvain clustering method will be automatically searched based on n_clusters.
- refine_shape
Smooth the spatial domains with given spatial topology, “hexagon” for Visium data, “square” for ST data. Defaults to None.
- p
Percentage of total expression contributed by neighborhoods.
- seed
Global seed for random, torch, numpy. Defaults to 100.
- numIterMaxSpa
SpaGCN maximum number of training iterations.
- copy
Whether to copy adata or modify it inplace.
- Returns:
Depending on the parameter copy, when True return an updates adata with the field
adata.obs[key_added]
andadata.obs[f'{key_added}_refined']
, containing the cluster result based on SpaGCN; else inplace update the adata object.