stereo.core.StPipeline.spatial_hotspot#

StPipeline.spatial_hotspot(use_highly_genes=True, hvg_res_key='highly_variable_genes', model='normal', n_neighbors=30, n_jobs=20, fdr_threshold=0.05, min_gene_threshold=10, outdir=None, res_key='spatial_hotspot', use_raw=True)[source]#

Identify informative genes or gene modules.

Parameters:

  • use_highly_genes (bool) – whether to use only the expression of hypervariable genes as input, default True.

  • hvg_res_key (Optional[str]) – the key of highly variable genes to get corresponding result.

  • model (Literal['danb', 'bernoilli', 'normal', 'none']) – specify the null model on gene expression from below: 'danb': Depth-Adjusted Negative Binomial 'bernoulli': Models probability of detection 'normal': Depth-Adjusted Normal 'none': Assumes data has been pre-standardized

  • n_neighbors (int) – the neighborhood size.

  • n_jobs (int) – the number of parallel jobs to run.

  • fdr_threshold (float) – correlation threshold at which to stop assigning genes into modules.

  • min_gene_threshold (int) – threshold that controls how small the modules could be. Increase if there are too many modules being formed, and decrease if substructre is not being captured.

  • outdir (Optional[str]) – the path to output file(hotspot.pkl), containing total hotspot object.

  • res_key (str) – the key for storing result of spatial hotspot.

  • use_raw (bool) – whether to use raw express matrix for analysis.

Returns:

The result of spatial hotspot is stored in self.result where the key is 'spatial_hotspot'.