normaliseGeneExpression {psichomics}R Documentation

Filter and normalise gene expression

Description

Filter and normalise gene expression

Usage

normaliseGeneExpression(
  geneExpr,
  geneFilter = NULL,
  method = "TMM",
  p = 0.75,
  log2transform = TRUE,
  priorCount = 0.25,
  performVoom = FALSE
)

Arguments

geneExpr

Matrix or data frame: gene expression

geneFilter

Boolean: filtered genes

method

Character: normalisation method, including TMM, RLE, upperquartile, none or quantile (see Details)

p

percentile (between 0 and 1) of the counts that is aligned when method="upperquartile"

log2transform

Boolean: perform log2-transformation?

priorCount

Average count to add to each observation to avoid zeroes after log-transformation

performVoom

Boolean: perform mean-variance modelling (voom)?

Details

edgeR::calcNormFactors will be used to normalise gene expression if one of the following methods is set: TMM, RLE, upperquartile or none. However, voom will be used for normalisation if performVoom = TRUE and the selected method is quantile.

Value

Filtered and normalised gene expression

See Also

Other functions for gene expression pre-processing: convertGeneIdentifiers(), filterGeneExpr(), plotGeneExprPerSample(), plotRowStats()

Examples

geneExpr <- readFile("ex_gene_expression.RDS")
normaliseGeneExpression(geneExpr)

[Package psichomics version 1.12.1 Index]