MathDAMP

MathDAMP performs differential analysis and visualization of complex metabolite profiles obtained by hyphenated mass spectrometry as a Mathematica package for comparative metabolomics and biomarker discovery.

Key Features:

• Automated preprocessing and normalization: Standardizes migration times and signal intensities across samples.
• Arithmetic operations on signal intensities: Applies arithmetic operations directly to corresponding datapoint-by-datapoint signal intensities, bypassing peak identification and integration.
• Dynamic programming and global optimization: Aligns datasets along the migration-time dimension using dynamic programming combined with global optimization.
• Graphical visualization using density plots: Visualizes results as density plots with axes for migration time and m/z where differences appear as color-coded spots.
• Statistical comparisons and highlighting subtle differences: Applies statistical tests to emphasize subtle differences between profiles.
• Generation of overlaid electropherograms (chromatograms): Generates overlaid electropherograms in descending order of significance around candidate differences.
• Integration with standard library tables: Aligns and overlays standard library tables containing m/z values and migration times for known compounds onto plots.

Scientific Applications:

• Functional genomics: Comparative analysis of metabolite profiles to investigate gene function and metabolic regulation.
• Biomarker discovery: Identification and prioritization of candidate metabolic biomarkers through differential profiling and statistical comparison.
• Comparative metabolomics: Direct comparison of complex metabolite profiles across samples or conditions using aligned migration-time and m/z data.

Methodology:

Computational methods explicitly include automated preprocessing and normalization of migration times and signal intensities, datapoint-by-datapoint arithmetic on signal intensities, dynamic programming with global optimization for migration-time alignment, statistical testing, density-plot visualization (migration time vs m/z), generation of overlaid electropherograms, and alignment/overlay of standard library tables.