buildCellTypeIndex {scfind} | R Documentation

## Build a cell type Index

### Description

Calculates a fraction of expressed cells per gene per cell type

### Usage

    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

    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)

[Package scfind version 1.2.0 Index]