[en] Comprehensive 2D gas chromatography coupled with mass spectrometry (GC × GC-MS) is a powerful analytical technique. However, the complexity and volume of data generated pose significant challenges for data processing and interpretation, limiting a broader adoption. Chemometric approaches, particularly multiway models like Parallel Factor Analysis (PARAFAC), have proven effective in addressing these challenges by enabling the extraction of meaningful chemical information from multi-dimensional datasets. However, traditional PARAFAC is constrained by its assumption of data tri-linearity, which may not be valid in all cases, leading to potential inaccuracies. To overcome these limitations, we present GcDUO, an open-source software implemented in R, designed specifically for the processing and analysis of GC × GC-MS data. GcDUO integrates advanced chemometric methods, including both PARAFAC and PARAFAC2, for a more accurate and comprehensive analysis. PARAFAC is particularly useful for deconvoluting overlapping peaks and extracting pure chemical signals, while PARAFAC2 relaxes de tri-linearity constraint, allowing the alignment between samples. The software is structured into six modules-data import, region of interest (ROI) selection, deconvolution, peak annotation, data integration, and visualization-facilitating comprehensive and flexible data processing. GcDUO was validated against the gold-standard software for comprehensive GC, demonstrating a high correlation (R2 = 0.9) in peak area measurements, confirming its effectiveness and reliability. GcDUO provides a valuable, open-source platform for researchers in metabolomics and related fields, enabling more accessible and customizable GC × GC-MS data analysis.
Disciplines :
Chemistry
Author, co-author :
Llambrich, Maria; Department of Electrical Electronic Engineering and Automation, Universitat Rovira i Virgili (URV), IISPV, C/Escorxador S/N, 43003, Tarragona, Spain
van der Kloet, Frans M; Biosystems Data Analysis Group, Swammerdam Institute for Life Sciences, University of Amsterdam, P.O. Box 94215, 1090 GE Amsterdam, Netherlands
Sementé, Lluc; Oncology Department, Hospital Universitari Sant Joan de Reus, Institut d'Investigació Sanitària Pere Virgili (IISPV), CERCA, Av. Joan Laporte 2, 43204, Reus, Spain
Rodrigues, Anaïs ; Université de Liège - ULiège > Molecular Systems (MolSys)
Samanipour, Saer; Van't Hoff Institute for Molecular Sciences (HIMS), University of Amsterdam, PO Box 94157, 1090 GD Amsterdam, Netherlands
Westerhuis, Johan A; Biosystems Data Analysis Group, Swammerdam Institute for Life Sciences, University of Amsterdam, P.O. Box 94215, 1090 GE Amsterdam, Netherlands
Cumeras, Raquel ; Department of Electrical Electronic Engineering and Automation, Universitat Rovira i Virgili (URV), IISPV, C/Escorxador S/N, 43003, Tarragona, Spain ; Oncology Department, Hospital Universitari Sant Joan de Reus, Institut d'Investigació Sanitària Pere Virgili (IISPV), CERCA, Av. Joan Laporte 2, 43204, Reus, Spain
Brezmes, Jesús; Department of Electrical Electronic Engineering and Automation, Universitat Rovira i Virgili (URV), IISPV, C/Escorxador S/N, 43003, Tarragona, Spain
Language :
English
Title :
GcDUO: an open-source software for GC × GC-MS data analysis.
This project received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No (798038). Grants PID2021-126543OB-C22 and RTI2018–098577-B-C21 funded by MICIU/AEI/ 10.13039/501100011033 and by ERDF/EU. MLL is thankful for her graduate fellowship from the URV PMF-PIPF program (ref. 2019PMF-PIPF-37) and Boehringer Ingelheim Fonds Travel Grant 2022. The Secretaria d’Universitats i Recerca del Departament d’Economia i Coneixement (2021 SGR 00818 and 2021 SGR 00842), CERCA program/Generalitat de Catalunya. AR is supported by the SRA-STEMA post-doctoral fellowship from Liège University.
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