An R package for preprocessing and Multivariate Analysis of Two-dimensional Gas Chromatography Data
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.
| Quick Links |
|---|
| RGCxGC Paper |
| Installation |
| CRAN Version |
| Tutorials |
|---|
| Introduction to RGCxGC package |
| Customizing 2D chromatogram visualization |
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").
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
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
