scib_rapids.utils.principal_component_regression

scib_rapids.utils.principal_component_regression#

scib_rapids.utils.principal_component_regression(X, covariate, categorical=False, n_components=None)[source]#

Principal component regression (PCR) using CuPy.

Parameters:

  • X (ndarray | ndarray) – Array of shape (n_cells, n_features).

  • covariate (ndarray | ndarray) – Array of shape (n_cells,) or (n_cells, 1) representing batch/covariate values.

  • categorical (bool (default: False)) – If True, batch will be treated as categorical and one-hot encoded.

  • n_components (int | None (default: None)) – Number of components to compute. If None, all components are used.

Return type:

float

Returns:

pcr: float