DISCO: Distance and Spectrum Correlation Optimization Alignment for Two-Dimensional Gas Chromatography Time-of-Flight Mass Spectrometry-Based Metabolomics

Abstract

A novel peak alignment algorithm using a distance and spectrum correlation optimization (DISCO) method has been developed for two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC/TOF-MS) based metabolomics. This algorithm uses the output of the instrument control software, ChromaTOF, as its input data. It detects and merges multiple peak entries of the same metabolite into one peak entry in each input peak list. After a z-score transformation of metabolite retention times, DISCO selects landmark peaks from all samples based on both two-dimensional retention times and mass spectrum similarity of fragment ions measured by Pearson's correlation coefficient. A local linear fitting method is employed in the original twodimensional retention time space to correct retention time shifts. A progressive retention time map searching method is used to align metabolite peaks in all samples together based on optimization of the Euclidean distance and mass spectrum similarity. The effectiveness of the DISCO algorithm is demonstrated using data sets acquired under different experiment conditions and a spiked-in experiment.

Profiling food volatiles by comprehensive two-dimensional ga schromatography coupled with mass spectrometry: Advanced fingerprinting approaches for comparative analysis of the volatile fraction of roasted hazelnuts (Corylus avellana L.) from different origins

“…separation data) with the chemical composition of samples, and their effectiveness has been demonstrated for different fields of application [2][3][4][5][6]. GC × GC approaches are commonly classified into two main groups: targeted and non-targeted methods [2].…”

MetPP: a computational platform for comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry-based metabolomics

“…Compared with the progressive retention time map searching method implemented in the distance and spectrum correlation optimization (DISCO) algorithm (Wang et al, 2010), the mixture score approach is able to align chromatographic peaks that may have a large variation in either retention time or mass spectral similarity, as long as the overall quality of two peak are similar. Supplementary Figure S7 depicts the alignment results of the spike-in experimental data by DISCO and MetPP.…”

“…The metabolite peaks in different samples are aligned based on their similarity of these three pieces of information measured by a mixture score. The retention time value of each peak in a peak list P i is first transformed into a modified z-score as follows (Wang et al, 2010):…”

“…Many data analysis algorithms have been developed to process the GCÂGC-TOF MS data for peak picking (Hoggard et al, 2009;Reichenbach et al, 2005;Sinha et al, 2004;Vivo-Truyols 2012), chromatogram alignment (Fraga et al, 2001;Pierce et al, 2005;van Mispelaar et al, 2003;Zhang et al, 2008) and peak list alignment (Almstetter et al, 2009;Kim et al, 2011;Wang et al, 2010). Guineu (Castillo et al, 2011) is the only reported tool that uses the peak lists as its input and performs retention time correction, peak list alignment, normalization and statistical significance tests.…”

Comprehensive Two-Dimensional Gas Chromatography Coupled to Time-of-Flight Mass Spectrometry in Human Metabolomics

“…(Panic et al, 2011), and improvement of data handling and evaluation (Wang et al, 2010;Kim et al, 2011;Koek et al, 2011) should be mentioned.…”