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A current and significant limitation to metabolomics is the large-scale, high-throughput conversion of raw chromatographically coupled mass spectrometry datasets into organized data matrices necessary for further statistical processing and data visualization. This article describes a new data extraction tool, MET-IDEA (Metabolomics Ion-based Data Extraction Algorithm) which surmounts this void. MET-IDEA is compatible with a diversity of chromatographically coupled mass spectrometry systems, generates an output similar to traditional quantification methods, utilizes the sensitivity and selectivity associated with selected ion quantification, and greatly reduces the time and effort necessary to obtain large-scale organized datasets by several orders of magnitude. The functionality of MET-IDEA is illustrated using metabolomics data obtained for elicited cell culture exudates from the model legume, Medicago truncatula …