Comprehensive 2D gas chromatography coupled with mass spectrometry (GCâÃâGC-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 GCâÃâGC-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 (R2â=â0.9) 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 GCâÃâGC-MS data analysis.
GcDUO: an open-source software for GCâÃâGC-MS data analysis.
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作者:Llambrich Maria, van der Kloet Frans M, Sementé Lluc, Rodrigues Anaïs, Samanipour Saer, Stefanuto Pierre-Hugues, Westerhuis Johan A, Cumeras Raquel, Brezmes Jesús
| 期刊: | Briefings in Bioinformatics | 影响因子: | 7.700 |
| 时间: | 2025 | 起止号: | 2025 Mar 4; 26(2):bbaf080 |
| doi: | 10.1093/bib/bbaf080 | ||
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