buildCellTypeIndex: Build a cell type Index

Description Usage Arguments Value Examples

Description

Calculates a fraction of expressed cells per gene per cell type

Usage

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buildCellTypeIndex(object = NULL, cell_type_column = "cell_type1")

buildCellTypeIndex.SCESet(object, cell_type_column)

## S4 method for signature 'SingleCellExperiment'
buildCellTypeIndex(object = NULL,
  cell_type_column = "cell_type1")

Arguments

object

object of SingleCellExperiment class

cell_type_column

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

Value

a 'data.frame' containing calculated gene index

Examples

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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)), ]
index <- buildCellTypeIndex(sce)

scfind documentation built on Nov. 1, 2018, 3:31 a.m.