normalizeScaling: Normalization by scaling

In crukci-bioinformatics/qPLEXanalyzer: Tools for quantitative proteomics data analysis

Normalization by scaling

Description

Performs scaling normalization on the peptide/protein intensities (median or mean)

Usage

normalizeScaling(MSnSetObj, scalingFunction = median, ProteinId = NULL)

Arguments

MSnSetObj	MSnSet; an object of class MSnSet
scalingFunction	function; median or mean
ProteinId	character; protein Id

Details

In this normalization method the central tendencies (mean or median) of the samples are aligned. The central tendency for each sample is computed and log transformed. A scaling factor is determined by subtracting from each central tendency the mean of all the central tendencies. The raw intensities are then divided by the scaling factor to get normalized intensities.

The intensities can also be normalized based on the peptide intensities of a selected protein. For this the argument "ProteinId" allows you to define the protein that will be used for scaling the intensities.

Value

An object of class MSnSet (see MSnSet-class)

Examples

data(human_anno)
data(exp3_OHT_ESR1)
MSnSet_data <- convertToMSnset(exp3_OHT_ESR1$intensities_qPLEX1, 
                               metadata=exp3_OHT_ESR1$metadata_qPLEX1,
                               indExpData=c(7:16), 
                               Sequences=2, 
                               Accessions=6)
MSnset_norm <- normalizeScaling(MSnSet_data, scalingFunction=median)

crukci-bioinformatics/qPLEXanalyzer documentation built on Oct. 23, 2023, 2:27 a.m.