Institute for Advanced Biosciences Keio University
MathDAMP Mathematica package for differential analysis of metabolite profiles
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MathDAMP > Examples > MathDAMP source > Assemblies of Core Functions for Common Tasks > Normalizing multiple datasets

Normalizing multiple datasets

The DAMPNormalizeGroup function aligns msdatas datasets to a reference dataset (one picked from msdatas specified by the Reference option) and normalizes them according to the area of the peak of the internal standard. Additional normalization coefficients may be passed to DAMPNormalizeGroup via the ExternalNormalizationCoefficients options (to account for different sample weights, etc.). Annotation tables may be passed to the function via the AnnotationTables option. These are aligned to the reference dataset as well. For automatic internal standard localization, its short name in the first annotation table must be specified by the InternalStandard option. The annotation table is aligned to the reference dataset and the vicinity of the location of the peak of the selected internal standard, as extrapolated from the aligned annotation table, is integrated. This integration is blind, overlaid chromatograms/electropherograms with the integrated area are shown for visual confirmation. The location of the peak of the internal standard in the reference dataset may also be specified explicitly. Also, peak picks, representative peak selection, aligned peaks and aligned annotation table layouts are shown for visual confirmation.
RepresentativePeakOptions were set to rather low values for the peak numbers to allow fast alignment with default options.
With many groups, Mathematica may run into memory problems. To limit this, signal intensities in internal calculations may be converted to integers to save memory. This is determined by the SaveMemory option (default: True).

Options[DAMPNormalizeGroup] = {Global`Reference1, Global`AlignmentTimeRangeA ... 62754;None, Global`AutoISIntegrationVicinity {-.25, .25}, Global`SaveMemoryTrue}

DAMPNormalizeGroup[msdatas_, opts___] := Module[{reference, aligntr, rpopts, ppopts, fsfopts ... edDatasetsaligneddatasets, Global`AlignedAnnotationTables->alignedannotbls} ]