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. |