calculateTPM {scater}R Documentation

Calculate transcripts-per-million (TPM)

Description

Calculate transcripts-per-million (TPM) values for expression from counts for a set of features.

Usage

calculateTPM(object, effective_length = NULL, exprs_values = "counts",
  subset_row = NULL)

Arguments

object

A SingleCellExperiment object or a count matrix.

effective_length

Numeric vector containing the effective length for each feature in object. If NULL, it is assumed that exprs_values has already been adjusted for transcript length.

exprs_values

String or integer specifying the assay containing the counts in object, if it is a SingleCellExperiment.

subset_row

A vector specifying the subset of rows of object for which to return a result.

Details

For read count data, this function assumes uniform coverage along the (effective) length of the transcript. Thus, the number of transcripts for a gene is proportional to the read count divided by the transcript length.

For UMI count data, this function should be run with effective_length=NULL, i.e., no division by the effective length. This is because the number of UMIs is a direct (albeit probably biased) estimate of the number of transcripts.

Value

A numeric matrix of TPM values.

Examples

data("sc_example_counts")
data("sc_example_cell_info")
example_sce <- SingleCellExperiment(
    assays = list(counts = sc_example_counts), 
    colData = sc_example_cell_info)

eff_len <- runif(nrow(example_sce), 500, 2000)
tout <- calculateTPM(example_sce, effective_length = eff_len)



[Package scater version 1.12.2 Index]