calculateTPM: Calculate transcripts-per-million (TPM)

In dynverse/scaterlegacy: Single-cell analysis toolkit for gene expression data in R

Description

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

Usage

calculateTPM(object, effective_length = NULL, calc_from = "counts")

Arguments

object	an SCESet object
effective_length	vector of class "numeric" providing the effective length for each feature in the SCESet object
calc_from	character string indicating whether to compute TPM from "counts", "norm_counts", "fpkm" or "norm_fpkm". Default is to use "counts", in which case the effective_length argument must be supplied.

Value

Matrix of TPM values.

Examples

data("sc_example_counts")
data("sc_example_cell_info")
pd <- new("AnnotatedDataFrame", data = sc_example_cell_info)
example_sceset <- newSCESet(countData = sc_example_counts, phenoData = pd)
effective_length <- rep(1000, 2000)
tpm(example_sceset) <- calculateTPM(example_sceset, effective_length,
    calc_from = "counts")

## calculate from FPKM
fpkm(example_sceset) <- calculateFPKM(example_sceset, effective_length)
tpm(example_sceset) <- calculateTPM(example_sceset, effective_length,
                                    calc_from = "fpkm")

dynverse/scaterlegacy documentation built on Feb. 17, 2020, 5:07 a.m.