CountNormalize: Normalize a SingleCellExperiment object using total counts
In debsin/dropClust: Single Cell Transcriptome Analysis

Description Usage Arguments Details Value Examples

Compute normalized expression values from count data in a SingleCellExperiment object, using the median normalized total count stored in the object.

1	CountNormalize(object, return_log = FALSE)

`object`	A SingleCellExperiment object.
`return_log`	Logical scalar, should normalized values be returned on the log2 scale? If `TRUE`, output is stored as `"logcounts"` in the returned object; if `FALSE` output is stored as `"normcounts"`.#'

Normalized expression values are computed by dividing the counts for each cell by median normalized total count of that cell. If log=TRUE, log-normalized values are calculated by adding a pseudocount of 1 to the normalized count and performing a log2 transformation.

A SingleCellExperiment object containing normalized expression values in "normcounts" if log=FALSE, and log-normalized expression values in "logcounts" if log=TRUE.

library(SingleCellExperiment)
ncells <- 100
ngenes <- 2000
x <- matrix(rpois(ncells*ngenes, lambda = 10), ncol=ncells, nrow=ngenes, byrow=TRUE)
rownames(x) <- paste0("Gene", seq_len(ngenes))
colnames(x) <- paste0("Cell", seq_len(ncells))
sce <- SingleCellExperiment(list(counts=x))
sce <- CountNormalize(sce)