RGCxGC

The goal of RGCxGC is to provide an easy-to-use platform to analyze two-dimensional gas chromatography data. RGCxGC offers common pre-processing algorithms for signal enhancement, such as baseline correction based on asymetric least squares, smoothing based on the Whittaker smoother, and peak alignment 2D COW. Furthermore, the multiway principal component analysis is implemented based on the Wold’s approach.

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RGCxGC Paper
Installation
CRAN Version
Tutorial

Installation

Install the released version of RGCxGC from CRAN with install.packages("RGCxGC").

Install the working version of RGCxGC from GitHub with devtools::install_github("DanielQuiroz97/RGCxGC").

Citing RGCxGC

Quiroz-Moreno, C., Furlan, M. F., Belinato, J. R., Augusto, F., Alexandrino, G. L., & Mogollón, N. G. (2020). RGCxGC toolbox: An R-package for data processing in comprehensive two-dimensional gas chromatography-mass spectrometry. Microchemical Journal, 156, 104830. https://doi.org/10.1016/j.microc.2020.104830

References

Eilers, P. H. (2003). A Perfect Smoother. Analytical Chemistry, 75(14), 3631-3636. https://doi.org/10.1021/ac034173t

Eilers, P. H. (2004). Parametric Time Warping. Analytical Chemistry, 76(2), 404-411. https://doi.org/10.1021/ac034800e

Wold, S., Geladi, P., Esbensen, K., & Öhman, J. (1987). Multi-way principal components-and PLS-analysis. Journal of Chemometrics, 1(1), 41-56. https://doi.org/10.1002/cem.1180010107

Zhang, D., Huang, X., Regnier, F. E., & Zhang, M. (2008). Two-Dimensional Correlation Optimized Warping Algorithm for Aligning GC×GC−MS Data. Analytical Chemistry, 80(8), 2664-2671. https://doi.org/10.1021/ac7024317