computeLogCPM: Compute log normalized counts

In GabrielHoffman/dreamlet: Scalable differential expression analysis of single cell transcriptomics datasets with complex study designs

Compute log normalized counts

Description

Compute normalized counts as log2 counts per million

Usage

computeLogCPM(
  sce,
  lib.size = colSums2(counts(sce)),
  prior.count = 2,
  scaledByLib = FALSE
)

Arguments

sce	SingleCellExperiment with counts stored as counts(sce)
lib.size	library size for each cell
prior.count	average count to be added to each observation to avoid taking log of zero
scaledByLib	if TRUE, scale pseudocount by lib.size. Else do standard constant pseudocount addition

Details

This function gives same result as edgeR::cpm(counts(sce), log=TRUE)

Value

matrix of log CPM values

See Also

also edgeR::cpm()

Examples

library(muscat)
library(SingleCellExperiment)

data(example_sce)

logcounts(example_sce) <- computeLogCPM(example_sce)

GabrielHoffman/dreamlet documentation built on Nov. 23, 2024, 12:28 a.m.