Normalization: Normalization

In xia-lab/MetaboAnalystR3.0: An R Package for Comprehensive Analysis of Metabolomics Data

Description

This function performs row-wise normalization, transformation, and scaling of your metabolomic data.

Usage

Normalization(mSetObj, rowNorm, transNorm, scaleNorm, ref=NULL, ratio=FALSE, ratioNum=20)

Arguments

mSetObj	Input the name of the created mSetObj (see InitDataObjects)
rowNorm	Select the option for row-wise normalization, "QuantileNorm" for Quantile Normalization, "ProbNormT" for Probabilistic Quotient Normalization without using a reference sample, "ProbNormF" for Probabilistic Quotient Normalization based on a reference sample, "CompNorm" for Normalization by a reference feature, "SumNorm" for Normalization to constant sum, "MedianNorm" for Normalization to sample median, and "SpecNorm" for Normalization by a sample-specific factor.
transNorm	Select option to transform the data, "LogNorm" for Log Normalization, and "CrNorm" for Cubic Root Transformation.
scaleNorm	Select option for scaling the data, "MeanCenter" for Mean Centering, "AutoNorm" for Autoscaling, "ParetoNorm" for Pareto Scaling, amd "RangeNorm" for Range Scaling.
ref	Input the name of the reference sample or the reference feature, use " " around the name.
ratio	This option is only for biomarker analysis.
ratioNum	Relevant only for biomarker analysis.

Author(s)

Jeff Xia [e-mail], Jasmine Chong McGill University, Canada

xia-lab/MetaboAnalystR3.0 documentation built on May 6, 2020, 11:03 p.m.