stlearn.spatial.trajectory.pseudotimespace_global

stlearn.spatial.trajectory.pseudotimespace_global(adata: AnnData, use_label: str = 'leiden', use_rep: str = 'X_pca', n_dims: int = 40, list_clusters=None, model: Literal['spatial', 'gene_expression', 'mixed'] = 'spatial', step=0.01, k=10) → AnnData | None[source]

Perform pseudo-time-space analysis with global level.

Parameters:

  • adata (AnnData) – Annotated data matrix.

  • use_label (str, default = "leiden") – Use label result of cluster method.

  • use_rep (str, default = "X_pca") – Which obsm location to use.

  • n_dims (int, default = 40) – Number of dimensions to use in PCA

  • list_clusters (list, optional) – List of cluster used to reconstruct spatial trajectory. If None, uses all clusters.

  • model (Literal["spatial", "gene_expression", "mixed"] = "mixed",) – Can be mixed, spatial or gene expression. spatial sets weight to 0, gene expression sets weight to 1 and mixed uses the list_clusters, step and k.

  • step (float, default = 0.01) – Step for screening weighting factor.

  • k (int, default = 10) – The number of eigenvalues to be compared.

Return type:

Anndata