mAPKL (version 1.4.2)

preprocess: Performs normalization and/or log2 transformation

Description

This function performs normalization and/or log2 transformation on gene expression data.

Usage

preprocess(exprsObj,log2=TRUE, norm="ALL", destname=NULL)

Arguments

exprsObj

An eSet object where its assay data will be normalized

log2

Performs logarithmic transformation of base 2 prior to any normalzation. The default value is TRUE

norm

The user may define a specific normalization method rather than "ALL" which is the default case. The available abbreviations are described in the details section

destname

Here we define the destination path and the name of the jpeg file with the density plots. The default path is the working directory

Value

• rawdata
  The initial gene expression values
• mc.normdata
  The values after 'mean-centering' normalization
• z.normdata
  The values after 'z-score' normalization
• q.normdata
  The values after 'quantile' normalization
• cl.normdata
  The values after 'cyclic loess' normalization
• mcL2.normdata
  The values after 'mean-centering' normalization and log2
• zL2.normdata
  The values after 'z-score' normalization and log2
• qL2.normdata
  The values after 'quantile' normalization and log2
• clL2.normdata
  The values after 'cyclic loess' normalization and log2

Details

The available normalization methods are: Mean-centering normalization "mc" z-score normalization "z" Quantile normalization "q" Cyclic loess normalization "cl" Mean-centering normalization and log2 transformation "mcL2" z-score normalization and log2 transformation "zL2" Quantile normalization and log2 transformation "qL2" Cyclic loess normalization and log2 transformation "clL2"

Examples

library(mAPKLData)
data(mAPKLData)
varLabels(mAPKLData)
breast <- sampling(Data=mAPKLData, valPercent=40, classLabels="type", seed=135)
normTrainData <- preprocess(exprsObj=breast$trainData)