normalizeCounts: Normalization of count data

Description Usage Arguments Value Examples

View source: R/celda_functions.R

Description

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

Usage

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normalizeCounts(
  counts,
  normalize = c("proportion", "cpm", "median", "mean"),
  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.

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

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

celda documentation built on June 9, 2020, 2 a.m.