2016
DOI: 10.1021/acs.analchem.6b02254
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Effectiveness of Global, Low-Degree Polynomial Transformations for GCxGC Data Alignment

Abstract: As columns age and differ between systems, retention times for comprehensive two-dimensional gas chromatography (GCxGC) may vary between runs. To properly analyze GCxGC chromatograms, it often is desirable to align the retention times of chromatographic features, such as analyte peaks, between chromatograms. Previous work by the authors has shown that global, low-degree polynomial transformation functions, namely affine, second-degree polynomial, and third-degree polynomial, are effective for aligning pairs of… Show more

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Cited by 24 publications
(25 citation statements)
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“…Pattern coherence, between mutually translatable methods, enabled effective transfer of metadata from the reference methodology by template matching algorithms [11,12,35].…”
Section: Background For the Present Study And Reference Methodsmentioning
confidence: 99%
“…Pattern coherence, between mutually translatable methods, enabled effective transfer of metadata from the reference methodology by template matching algorithms [11,12,35].…”
Section: Background For the Present Study And Reference Methodsmentioning
confidence: 99%
“…The software identified compounds when the LRI match was within ± 10 units of published values and the NIST spectral match for that compound was >950. After the analysis, positively matched peaks were used to re-align chromatograms [47,48] and combined into a single, composite chromatogram. 2D-peak detection was performed on the composite chromatogram with peak outlines recorded as peak-region objects in the chromatographic plane.…”
Section: Methodsmentioning
confidence: 99%
“…In this study, chromatographic fingerprinting was applied by comprehensively extracting peak features information (i.e., summed data for each component peak with associated metadata) including for untargeted and targeted components. To enable effective crosscomparative analysis, peak features pattern matching across multiple chromatograms was guided by mass spectral similarity with DMF ≥ 800 [23,51] and a second-order-polynomial retention-times transformation [52,53]. For targeted components, the approach explicitly matches corresponding peak-features across chromatograms by the target name.…”
Section: Mapping Hazelnut Metabolome By Chromatographic Fingerprintingmentioning
confidence: 99%