omicverse.utils.weighted_knn_transfer¶

omicverse.utils.weighted_knn_transfer(query_adata, query_adata_emb, ref_adata_obs, label_keys, knn_model, threshold=1, pred_unknown=False, mode='package')[source]¶

Annotates query_adata cells with an input trained weighted KNN classifier.

Return type:: tuple

Arguments: query_adata: Annotated dataset to be used to queryate KNN classifier. Embedding to be used query_adata_emb: Name of the obsm layer to be used for label transfer. If set to “X”, query_adata.X will be used ref_adata_obs: obs of ref Anndata label_keys: Names of the columns to be used as target variables (e.g. cell_type) in query_adata. knn_model: knn model trained on reference adata with weighted_knn_trainer function threshold: Threshold of uncertainty used to annotating cells as “Unknown”. cells with uncertainties higher than this value will be annotated as “Unknown”. Set to 1 to keep all predictions. This enables one to later on play with thresholds. pred_unknown: False by default. Whether to annotate any cell as “unknown” or not. If False, threshold will not be used and each cell will be annotated with the label which is the most common in its n_neighbors nearest cells. mode: Has to be one of “paper” or “package”. If mode is set to “package”, uncertainties will be 1 - P(pred_label), otherwise it will be 1 - P(true_label).
Returns: pred_labels: Dataframe with predicted labels for each cell in query_adata. uncertainties: Dataframe with uncertainties for each cell in query_adata.