A Comprehensive Two-Dimensional Retention Time Alignment Algorithm To Enhance Chemometric Analysis of Comprehensive Two-Dimensional Separation Data

Abstract

A comprehensive two-dimensional (2D) retention time alignment algorithm was developed using a novel indexing scheme. The algorithm is termed comprehensive because it functions to correct the entire chromatogram in both dimensions and it preserves the separation information in both dimensions. Although the algorithm is demonstrated by correcting comprehensive two-dimensional gas chromatography (GC x GC) data, the algorithm is designed to correct shifting in all forms of 2D separations, such as LC x LC, LC x CE, CE x CE, and LC x GC. This 2D alignment algorithm was applied to three different data sets composed of replicate GC x GC separations of (1) three 22-component control mixtures, (2) three gasoline samples, and (3) three diesel samples. The three data sets were collected using slightly different temperature or pressure programs to engender significant retention time shifting in the raw data and then demonstrate subsequent corrections of that shifting upon comprehensive 2D alignment of the data sets. Thirty 12-min GC x GC separations from three 22-component control mixtures were used to evaluate the 2D alignment performance (10 runs/mixture). The average standard deviation of first column retention time improved 5-fold from 0.020 min (before alignment) to 0.004 min (after alignment). Concurrently, the average standard deviation of second column retention time improved 4-fold from 3.5 ms (before alignment) to 0.8 ms (after alignment). Alignment of the 30 control mixture chromatograms took 20 min. The quantitative integrity of the GC x GC data following 2D alignment was also investigated. The mean integrated signal was determined for all components in the three 22-component mixtures for all 30 replicates. The average percent difference in the integrated signal for each component before and after alignment was 2.6%. Singular value decomposition (SVD) was applied to the 22-component control mixture data before and after alignment to show the restoration of trilinearity to the data, since trilinearity benefits chemometric analysis. By applying comprehensive 2D retention time alignment to all three data sets (control mixtures, gasoline samples, and diesel samples), classification by principal component analysis (PCA) substantially improved, resulting in 100% accurate scores clustering.

Comprehensive two-dimensional gas chromatography for fingerprint pattern recognition in olive oils produced by two different techniques in Portuguese olive varieties Galega Vulgar, Cobrançosa e Carrasquenha

“…Data from the contour plots (1000 s in the 1 D and 2 s in the 2 D, as indicated above) are divided in quadrants and the values used represents the sum of the areas/pixels from each quadrant. Due to this fact, retention time alignment could be precluded, since the expected highest average standard deviation, considering slightly differences in temperature and pressure programs, of the first and second columns retention times (1.2 s and 0.0035 s, respectively) [31] are correspondently relatively low −0.12% of the period of time considered in the 1 D (1000 s) and 0.18% of the period of time considered in 2 D (2 s). The issue here is, in fact, to consider for each quadrant a surface, defined by the retention times on the 1 D and 2 D, sufficiently high in order to dilute any deviation on both dimensions of a particular compound.…”

“…The complex and time consuming task of identifying all the data obtained by GC × GC/ToF-MS is simplified considerably. This methodology was never applied before, as far as we know, although it has already been considered to be an evident application for pattern analysis obtained after a GC × GC experiment [31]. Using this quick and user friendly methodology, one can reduce drastically the amount of data needed for fingerprint characterization.…”

“…In the last decade, two-dimensional-GC (2D-GC) experienced a broader diffusion mainly due to its selectivity (three dimensions if mass spectrometric data are considered), high sensitivity (allowed by the peak focusing), enhance separation power and speed [25,26]. The quantity and variety of information thus provided by 2D-GC systems promoted the increasingly application of chemometrics in order to allow the data interpretation in a useful and potentially easy way [27][28][29][30][31][32].…”

Comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry peak sorting algorithm

“…However, these two methods only can be used to align small regions of interest in the two-dimensional data set and they both require a standard as a point of reference. Recently, Pierce et al proposed an alignment algorithm that can correct the entire chromatogram in both GC dimensions [14]. The algorithm used a novel indexing scheme together with a piecewise retention time alignment algorithm [15][16][17], in which one chromatogram is used as the target and other chromatograms aligned to it.…”

LC-MS Data Analysis for Differential Protein Expression Detection

“…Thus, alignment with respect to both m/z and retention time is a prerequisite for quantitative comparison of proteins/peptides by LC-MS. Alignment algorithms have traditionally been used on data points and/or feature vectors of fixed dimension (5). Applications of these algorithms for LC-MS data alignment have been reported in the literature (6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16). The most common approaches for aligning LC-MS data are based on the identification of landmarks or structural points (referring to the unique charge species in data) and the use of internal standards, respectively.…”