gcxgclab: An R Package for Two-Dimensional Gas Chromatography Preprocessing and Analysis

Area of Science:

• Analytical Chemistry
• Chromatography
• Data Science

Background:

• Comprehensive two-dimensional gas chromatography (GC×GC) generates large, complex datasets.
• Existing GC×GC software is often limited to low-throughput qualitative analysis on desktops.
• Limited flexibility in commercial software hinders exploration of novel data processing methods.

Purpose of the Study:

• To develop an open-source R package, gcxgclab, for efficient GC×GC data processing.
• To provide a customizable and flexible alternative to commercial GC×GC software.
• To enable high-throughput analysis of complex GC×GC data.

Main Methods:

• Development of the 'gcxgclab' R package.
• Implementation of functions for baseline correction, smoothing, peak detection, and alignment.
• Inclusion of tools for extracted ion chromatogram generation, mass spectra extraction, and mass defect analysis.
• Support for both targeted and nontargeted data analysis.

Main Results:

• The gcxgclab package provides a comprehensive suite of data preprocessing and analysis functions.
• The package supports customizable workflows and batch processing.
• gcxgclab facilitates increased throughput for GC×GC data analysis on various computing systems.

Conclusions:

• gcxgclab offers a flexible, open-source solution for GC×GC data analysis.
• The package enhances the efficiency and capabilities for researchers working with complex chromatographic data.
• gcxgclab is freely available on CRAN, promoting wider adoption and development.