Desarrollo de una librería estadística en R para el manejo de datos de cromatografía gaseosa bidimensional

Abstract

Comprehensive two-dimensional gas chromatography (GC×GC) offers detailed chemical information about volatile and semivolatile analytes from complex samples. However, the high complexity of the data structure encourages the development of new tools for a more efficient data handling and analysis. Although some tools have already been presented to overcome this challenge, there is still need for improvement. In this manuscript, we present a toolbox containing a pipeline for end-to-end basic GC×GC data processing which can be used for both, signal pre-processing and multivariate data analysis. The pre-processing algorithms perform signal smoothing, baseline correction, and peak alignment, while the multivariate analysis is done through Multiway Principal Component Analysis (MPCA). The software is capable to prepare the chromatographic data for further applications with other chemometric tools, e.g.: cluster analysis, regression, discriminant analysis, etc. The performance of this new software was tested on in-house experimental dataset and on two other published datasets.