calcIsExprs {scater} | R Documentation

## Calculate which features are expressed in which cells using a threshold on observed counts, transcripts-per-million, counts-per-million, FPKM, or defined expression levels.

### Description

Calculate which features are expressed in which cells using a threshold on observed counts, transcripts-per-million, counts-per-million, FPKM, or defined expression levels.

### Usage

    calcIsExprs(object, lowerDetectionLimit = 0, exprs_values = "counts")

### Arguments

`object` | a `SingleCellExperiment` object with expression and/or count data.
`lowerDetectionLimit` | numeric scalar giving the minimum expression level for an expression observation in a cell for it to qualify as expressed.
`exprs_values` | character scalar indicating whether the count data (`"counts"`), the log-transformed count data (`"logcounts"`), transcript-per-million (`"tpm"`), counts-per-million (`"cpm"`) or FPKM (`"fpkm"`) should be used to define if an observation is expressed or not. Defaults to the first available value of those options in the order shown.

### Value

a logical matrix indicating whether or not a feature in a particular cell is expressed.

### Examples

    data("sc_example_counts")
    data("sc_example_cell_info")
    example_sce <- SingleCellExperiment(
    assays = list(counts = sc_example_counts), colData = sc_example_cell_info)
    assay(example_sce, "is_exprs") <- calcIsExprs(example_sce,
    lowerDetectionLimit = 1, exprs_values = "counts")

[Package scater version 1.6.3 Index]