spatialtis.NCD_marker

class spatialtis.NCD_marker(data, importance_cutoff=0.5, layer_key=None, tree_kwargs=None, test_method='mannwhitneyu', pval=0.01, **kwargs)[source]

Identify neighbor cells dependent marker

This method tells you the dependency between markers and its neighbor cell type. The dependency is calculated by building a gradiant boosting tree (in here lightgbm) to determine the feature importance. A statistic test and fold change will be calculate for importance markers and its neighbor cells, the fold change is between marker with cell type at / not at the neighborhood.

Parameters

  • data (anndata._core.anndata.AnnData) – AnnData object to perform analysis

  • importance_cutoff (Union[int, float]) – Threshold to determine the feature markers

  • selected_markers – Select your interested markers

  • layer_key (Optional[str]) – The layer in AnnData to perform analysis

  • tree_kwargs (Optional[Dict]) – The keyword arguments that pass to the boosting tree class, (Default: n_jobs=-1, random_state=0)

  • test_method (str) – which test method to use, anything from scipy.stats

  • pval (Union[int, float]) – The p-value threshold to determine significance

  • **kwargs – Pass to spatialtis.abc.AnalysisBase

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