, query, field, n_neighbors=30, use_rep=None, key_added=None, **kwargs)[源代码]

Transfer discrete labels from reference dataset to query dataset

  • ref (AnnData) – Reference dataset

  • query (AnnData) – Query dataset

  • field (str) – Field to be transferred in ref.obs (must be discrete)

  • n_neighbors (int) – Number of nearest neighbors used for label transfer

  • use_rep (typing.Optional[str]) – Data representation based on which to find nearest neighbors, by default uses {ref, query}.X.

  • key_added (typing.Optional[str]) – New query.obs key added for the transfered labels, by default the same as field.

  • **kwargs – Additional keyword arguments are passed to sklearn.neighbors.NearestNeighbors


First, nearest neighbors between reference and query cells are searched and weighted by Jaccard index of SNN (shared nearest neighbors). The Jaccard indices are then normalized per query cell to form a mapping matrix. To obtain predictions for query cells, we multiply the above mapping matrix to the one-hot matrix of reference labels. The category with the highest score is taken as the final prediction, while its score is interpreted as transfer confidence (stored as “{key_added}_confidence” in query.obs).