sceleto.annotation

Label Transfer

sceleto.annotation.transfer(input_adata, y_id, output_adata, y_out, select_num=200, log=None, exclude=[], raw=True, max_iter=100)

sceleto.annotation.generate_training_X(adata, ct_key, select_num=200, exclude=[])

sceleto.annotation.logistic_model(data, cell_types, sparsity=0.2, fraction=0.2, penalty='l2', max_iter=100)

sceleto.annotation.plot_roc(y_prob, y_test, lr)

sceleto.annotation.update_label(from_adata, from_label, to_adata, old_label, new_label, exclude=None, include=None, replace=False, unknown=None, keep_replaced=True)

sceleto.annotation.predict_high(lr, adata, out_name, cl_to_focus=None, p=0.9)

sceleto.annotation.get_common_var_raw(a, b)

pangeapy Integration

sceleto.annotation.cellannotator(adata, **kwargs)

Run pangeapy CellAnnotator on an AnnData object.

Returns the annotated prediction object.

sceleto.annotation.metaannotator(pred, **kwargs)

Run pangeapy MetaAnnotator on a CellAnnotator prediction.

Returns the meta-annotated result.