This function performs row-wise normalization, transformation, and scaling of your metabolomic data.
Normalization(mSetObj, rowNorm, transNorm, scaleNorm, ref=NULL, ratio=FALSE, ratioNum=20)Input the name of the created mSetObj (see InitDataObjects)
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.
Select option to transform the data, "LogNorm" for Log Normalization, and "CrNorm" for Cubic Root Transformation.
Select option for scaling the data, "MeanCenter" for Mean Centering, "AutoNorm" for Autoscaling, "ParetoNorm" for Pareto Scaling, amd "RangeNorm" for Range Scaling.
Input the name of the reference sample or the reference feature, use " " around the name.
This option is only for biomarker analysis.
Relevant only for biomarker analysis.