findCell {scfind} | R Documentation

## Find cells associated with a given gene list

### Description

Calculates p-values of a log-likelihood of a list of genes to be associated with each cell type. Log-likelihood is based on gene expression values.

### Usage

    findCell(input = NULL, genelist = NULL)

    findCell.SCESet(input, genelist)

    ## S4 method for signature 'list'
    findCell(input = NULL, genelist = NULL)

### Arguments

`input` | object of SingleCellExperiment class
`genelist` | column name in the colData slot of the object SingleCellExperiment containing the cell classification information

### Value

a 'list' 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 <- buildCellIndex(sce)
    res <- findCell(index, genelist = c('SOX6', 'SNAI3'))

[Package scfind version 1.9.0 Index]