scib_rapids.kbet_per_label

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scib_rapids.kbet_per_label#

scib_rapids.kbet_per_label(X, batches, labels, alpha=0.05, diffusion_n_comps=100, return_df=False)[source]#

Compute kBET score per cell type label.

Parameters:

  • X (NeighborsResults) – A NeighborsResults object.

  • batches (ndarray) – Array of shape (n_cells,) representing batch values.

  • labels (ndarray) – Array of shape (n_cells,) representing label values.

  • alpha (float (default: 0.05)) – Significance level for the statistical test.

  • diffusion_n_comps (int (default: 100)) – Number of diffusion components for diffusion distance approximation.

  • return_df (bool (default: False)) – Return dataframe of results in addition to score.

Return type:

float | tuple[float, DataFrame]

Returns:

kbet_score Kbet score over all cells.

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