A visual analysis system for metabolomics data

When analyzing metabolomics data, cancer care researchers are searching for differences between known healthy samples and unhealthy samples. By analyzing and understanding these differences, researchers hope to identify cancer biomarkers. In this work we present a novel system that enables interactive comparative visualization and analysis of metabolomics data obtained by two-dimensional gas chromatography-mass spectrome-try (GCxGC-MS). Our system allows the user to produce, and interactively explore, visualizations of multiple GCxGC-MS data sets, thereby allowing a user to discover differences and features in real time. Our system provides statistical support in the form of mean and standard deviation calculations to aid users in identifying meaningful differences between sample groups. We combine these with multiform, linked visualizations in order to provide researchers with a powerful new tool for GCxGC-MS exploration and bio-marker discovery.