Visual analytics is the science of analytical reasoning facilitated by interactive interfaces for visual analysis and exploration. The OMIC Explorer, developed by the Purdue University Regional Visualization and Analytics Center (PURVAC), helps metabolomics research laboratories analyze massive, multi-dimensional GCxGC-MS datasets to discover new metabolic markers for the early detection of disease.
Comprehensive 2-dimensional Gas Chromatography (GCxGC) is a diagnostic process for analyzing chemicals and mass spectrometry (MS) is a useful method for computer-assisted, automated analyses of the complex separations produced by GCxGC. In GCxGC-MS, each sample output of the GCxGC separation is analyzed by time-of-flight MS. As a result, instead of a single value at each sample output, there is a mass spectrum consisting of an array of (mass/z, intensity) pairs. These mass spectra can be used in identifying unknown chemicals and in separating co-eluting peaks for more accurate quantification.
If we let x=retention-time-1 and y=retention-time-2, each pixel value of the Total Ion Count (TIC) image above denotes the sum of intensities of the mass spectra at time (x,y). The mass spectra is an array that records the intensity of each kind of mass measured in the given time (x,y). Because the mass ranges from 50 to 900, the size of the array is 851 and thus the input raw data can be regarded as a 542x400x851 volume. Intensity values range from 0 to 1,000,000,000 which makes the visualization quite difficult. Traditionally, commercial software visualize TIC data as a 2D image.
You can use the OMIC Explorer for
- visual exploration of the 3D mass spectrum
- visual identification of interesting potential biomarkers
- comparative exploration across datasets (i.e., cancer vs. control)
- evaluation of the TIC to refine input parameters for GCxGC-MS statistical modeling tools.
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