scmapCell: For each cell in a query dataset, we search for the nearest...

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

Description

For each cell in a query dataset, we search for the nearest neighbours by cosine distance within a collection of reference datasets.

Usage

scmapCell(projection = NULL, index_list = NULL, w = 10)

scmapCell.SingleCellExperiment(projection, index_list, w)

## S4 method for signature 'SingleCellExperiment'
scmapCell(projection = NULL,
  index_list = NULL, w = 10)

Arguments

projection	an object of SingleCellExperiment class
index_list	list of index objects each coming from the output of 'indexCell'
w	a positive integer specifying the number of nearest neighbours to find

Value

a list of 3 objects: 1) a matrix with the closest w neighbours by cell number of each query cell stored by column 2) a matrix of integers giving the reference datasets from which the above cells came from 3) a matrix with the cosine similarities corresponding to each of the nearest neighbours

Examples

library(SingleCellExperiment)
sce <- SingleCellExperiment(assays = list(normcounts = as.matrix(yan)), colData = ann)
# this is needed to calculate dropout rate for feature selection
# important: normcounts have the same zeros as raw counts (fpkm)
counts(sce) <- normcounts(sce)
logcounts(sce) <- log2(normcounts(sce) + 1)
# use gene names as feature symbols
rowData(sce)$feature_symbol <- rownames(sce)
# remove features with duplicated names
sce <- sce[!duplicated(rownames(sce)), ]
sce <- selectFeatures(sce)
sce <- indexCell(sce)
scmapCell_results <- scmapCell(sce, list(metadata(sce)$scmap_cell_index))

scmap documentation built on Nov. 8, 2020, 8:07 p.m.