MathDAMP: a package for differential analysis of metabolite profiles

Background: With the advent of metabolomics as a powerful tool for both functional and biomarker discovery, the identification of specific differences between complex metabolite profiles is becoming a major challenge in the data analysis pipeline. The task remains difficult, given the datasets' size, complexity, and common shifts in migration (elution/retention) times between samples analyzed by hyphenated mass spectrometry methods. Results: We present a Mathematica (Wolfram Research, Inc.) package MathDAMP (Mathematica package for Differential Analysis of Metabolite Profiles), which highlights differences between raw datasets acquired by hyphenated mass spectrometry methods by applying arithmetic operations to all corresponding signal intensities on a datapoint-by-datapoint basis. Peak identification and integration is thus bypassed and the results are displayed graphically. To facilitate direct comparisons, the raw datasets are automatically preprocessed and normalized in terms...

• Type: Journal
• Year: 2006
• Where: BMCBI
• Authors: Richard Baran, Hayataro Kochi, Natsumi Saito, Makoto Suematsu, Tomoyoshi Soga, Takaaki Nishioka, Martin Robert, Masaru Tomita
• Keywords: BMCBI 2006, Metabolite Profiles, Migration Times, Raw Datasets