An iterative block-shifting approach to retention time alignment that preserves the shape and area of gas chromatography-mass spectrometry peaks

<p>Abstract</p> <p>Background</p> <p>Metabolomics, petroleum and biodiesel chemistry, biomarker discovery, and other fields which rely on high-resolution profiling of complex chemical mixtures generate datasets which contain millions of detector intensity readings, each uniquely addressed along dimensions of <it>time </it>(<it>e.g.</it>, <it>retention time </it>of chemicals on a chromatographic column), a <it>spectral value </it>(<it>e.g., mass-to-charge ratio </it>of ions derived from chemicals), and the <it>analytical run number</it>. They also must rely on data preprocessing techniques. In particular, inter-run variance in the retention time of chemical species poses a significant hurdle that must be cleared before feature extraction, data reduction, and knowledge discovery can ensue. <it>Alignment methods</it>, for calibrating retention reportedly (and in our experience) can misalign matching chemicals, falsely align distinct ones, be unduly sensitive to chosen values of input parameters, and result in distortions of peak shape and area.</p> <p>Results</p> <p>We present an iterative block-shifting approach for retention-time calibration that detects chromatographic features and qualifies them by retention time, spectrum, and the effect of their inclusion on the quality of alignment itself. Mass chromatograms are aligned pairwise to one selected as a reference. In tests using a 45-run GC-MS experiment, block-shifting reduced the absolute deviation of retention by greater than 30-fold. It compared favourably to COW and XCMS with respect to alignment, and was markedly superior in preservation of peak area.</p> <p>Conclusion</p> <p>Iterative block-shifting is an attractive method to align GC-MS mass chromatograms that is also generalizable to other two-dimensional techniques such as HPLC-MS.</p

Profiling of Volatile Organic Compounds in Exhaled Breath as a Strategy to Find Early Predictive Signatures of Asthma in Children

Wheezing is one of the most common respiratory symptoms in preschool children under six years old. Currently, no tests are available that predict at early stage who will develop asthma and who will be a transient wheezer. Diagnostic tests of asthma are reliable in adults but the same tests are difficult to use in children, because they are invasive and require active cooperation of the patient. A non-invasive alternative is needed for children. Volatile Organic Compounds (VOCs) excreted in breath could yield such non-invasive and patient-friendly diagnostic. The aim of this study was to identify VOCs in the breath of preschool children (inclusion at age 2-4 years) that indicate preclinical asthma. For that purpose we analyzed the total array of exhaled VOCs with Gas Chromatography time of flight Mass Spectrometry of 252 children between 2 and 6 years of age. Breath samples were collected at multiple time points of each child. Each breath-o-gram contained between 300 and 500 VOCs; in total 3256 different compounds were identified across all samples. Using two multivariate methods, Random Forests and dissimilarity Partial Least Squares Discriminant Analysis, we were able to select a set of 17 VOCs which discriminated preschool asthmatic children from transient wheezing children. The correct prediction rate was equal to 80% in an independent test set. These VOCs are related to oxidative stress caused by inflammation in the lungs and consequently lipid peroxidation. In conclusion, we showed that VOCs in the exhaled breath predict the subsequent development of asthma which might guide early treatment