| ann | Cell type annotations for data extracted from a publication by Yan et al. |
| EuclSqNorm | The Euclidean Squared Norm of each column of a matrix is computed and the whole result is returned as a vector. Used as part of the approx. calculations of the cosine similarity between the query and the reference. |
| getSankey | Plot Sankey diagram comparing two clusterings |
| indexCell | Create an index for a dataset to enable fast approximate nearest neighbour search |
| indexCell-method | Create an index for a dataset to enable fast approximate nearest neighbour search |
| indexCell.SingleCellExperiment | Create an index for a dataset to enable fast approximate nearest neighbour search |
| indexCluster | Create a precomputed Reference |
| indexCluster-method | Create a precomputed Reference |
| indexCluster.SingleCellExperiment | Create a precomputed Reference |
| NN | Main nearest neighbour calculation function. Used on the first reference dataset. Returns a list of three objects: 1) the cell indices of the w nearest neighbours 2) the corresponding approx. cosine similarities |
| normalise | Normalises each column of a matrix |
| scmapCell | For each cell in a query dataset, we search for the nearest neighbours by cosine distance within a collection of reference datasets. |
| scmapCell-method | For each cell in a query dataset, we search for the nearest neighbours by cosine distance within a collection of reference datasets. |
| scmapCell.SingleCellExperiment | For each cell in a query dataset, we search for the nearest neighbours by cosine distance within a collection of reference datasets. |
| scmapCell2Cluster | Approximate k-NN cell-type classification using scfinemap |
| scmapCell2Cluster-method | Approximate k-NN cell-type classification using scfinemap |
| scmapCell2Cluster.SingleCellExperiment | Approximate k-NN cell-type classification using scfinemap |
| scmapCluster | scmap main function |
| scmapCluster-method | scmap main function |
| scmapCluster.SingleCellExperiment | scmap main function |
| selectFeatures | Find the most informative features (genes/transcripts) for projection |
| selectFeatures-method | Find the most informative features (genes/transcripts) for projection |
| selectFeatures.SingleCellExperiment | Find the most informative features (genes/transcripts) for projection |
| setFeatures | Set the most important features (genes/transcripts) for projection |
| setFeatures-method | Set the most important features (genes/transcripts) for projection |
| setFeatures.SingleCellExperiment | Set the most important features (genes/transcripts) for projection |
| subdistsmult | Computes the dot product between the subcentroids from the indexed reference and the subvectors of an element of the query dataset. Returns an M by k matrix. Used as an intermediate step (in NNfirst and NNmult) for calculating an approximation of the cosine similarity between the query and the reference. |
| yan | Single cell RNA-Seq data extracted from a publication by Yan et al. |