normalizeCounts: Normalization of count data

In celda: CEllular Latent Dirichlet Allocation

Description

Performs normalization, transformation, and/or scaling of a counts matrix

Usage

normalizeCounts(
  counts,
  normalize = c("proportion", "cpm", "median", "mean"),
  scaleFactor = NULL,
  transformationFun = NULL,
  scaleFun = NULL,
  pseudocountNormalize = 0,
  pseudocountTransform = 0
)

Arguments

counts	Integer matrix. Rows represent features and columns represent cells.
normalize	Character. Divides counts by the library sizes for each cell. One of 'proportion', 'cpm', 'median', or 'mean'. 'proportion' uses the total counts for each cell as the library size. 'cpm' divides the library size of each cell by one million to produce counts per million. 'median' divides the library size of each cell by the median library size across all cells. 'mean' divides the library size of each cell by the mean library size across all cells.
scaleFactor	Numeric. Sets the scale factor for cell-level normalization. This scale factor is multiplied to each cell after the library size of each cell had been adjusted in normalize. Default NULL which means no scale factor is applied.
transformationFun	Function. Applys a transformation such as sqrt, log, log2, log10, or log1p. If NULL, no transformation will be applied. Occurs after normalization. Default NULL.
scaleFun	Function. Scales the rows of the normalized and transformed count matrix. For example, 'scale' can be used to z-score normalize the rows. Default NULL.
pseudocountNormalize	Numeric. Add a pseudocount to counts before normalization. Default 0.
pseudocountTransform	Numeric. Add a pseudocount to normalized counts before applying the transformation function. Adding a pseudocount can be useful before applying a log transformation. Default 0.

Value

Numeric Matrix. A normalized matrix.

Examples

data(celdaCGSim)
normalizedCounts <- normalizeCounts(celdaCGSim$counts, "proportion",
  pseudocountNormalize = 1)

celda documentation built on Nov. 8, 2020, 8:24 p.m.