Feature detection and alignment of hyphenated chromatographic–mass spectrometric data: Extraction of pure ion chromatograms using Kalman tracking

In this paper we present a new method, called TracMass, for analyzing data obtained using hyphenated chromatography–mass spectrometry (XC/MS). The method uses a Kalman filter to extract pure, noise-free ion chromatograms by exploiting the latent second order structure in the XC/MS data. TracMass differs from current state-of-the-art methodologies, which extract chromatograms by binning along the m/z axis and further processes the data in various ways, e.g. by baseline correction, component detection algorithm, peak detection, and curve resolution to extract molecular features. The proposed method was validated by analyzing two plasma datasets: one derived from 99 quality control samples where TracMass extracted 8880 Pure Ion Chromatograms (PICs) present in ≥90 of the samples. The second dataset was spiked with two different internal standard mixtures to test differential expression analysis. Here TracMass found 20 000 PICs present in 10 samples, all differentially expressed analytes, and also a previously unreported discriminating metabolite. Finding as many PICs as possible is in this context essential to ensure that even small differentiating features are found (if they exist). The resulting data representation from TracMass (PICs) can be used directly for statistical analysis, and the method is fast (approximately 5 min/sample), with few adjustable parameters.