A tool for unsupervised projection of single cell RNA-seq data


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Documentation for package ‘scmap’ version 1.28.0

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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.