R: Create a precomputed Reference

indexCluster {scmap}

R Documentation

Create a precomputed Reference

Description

Calculates centroids of each cell type and merge them into a single table.

Usage

indexCluster(object = NULL, cluster_col = "cell_type1")

indexCluster.SingleCellExperiment(object, cluster_col)

## S4 method for signature 'SingleCellExperiment'
indexCluster(object = NULL,
  cluster_col = "cell_type1")

Arguments

`object`	SingleCellExperiment object
`cluster_col`	column name in the 'colData' slot of the SingleCellExperiment object containing the cell classification information

Value

a 'data.frame' containing calculated centroids of the cell types of the Reference dataset

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)$feature_symbol <- rownames(sce)
isSpike(sce, 'ERCC') <- grepl('^ERCC-', rownames(sce))
# remove features with duplicated names
sce <- sce[!duplicated(rownames(sce)), ]
sce <- selectFeatures(sce)
sce <- indexCluster(sce[rowData(sce)$scmap_features, ])

[Package scmap version 1.1.5 Index]