Peak Alignment and Robust Principal Component Analysis of Gas Chromatograms of Fatty Acid Methyl Esters and Volatiles

Møller, Stina Frosch; Jørgensen, Bo

doi:10.1093/chromsci/45.4.169

Cited by 8 publications

(3 citation statements)

References 21 publications

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“…The correction is then conducted by warping these segments relatively to those of the reference profile. Hence, the linear stretching and compression of the length are carried out by shifting the end points with a limited number of data points, defined as the slack size (SS) [36]. The aim of this technique is to find the optimal correction that results in a maximum correlation with respect to the target fingerprint.…”

Section: Automated Correlation-optimized Warping (Acow)mentioning

confidence: 99%

Gas Chromatographic Fingerprint Analysis for the Comparison of Seized Cannabis Samples

et al. 2021

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Cannabis sativa L. is widely used as recreational illegal drugs. Illicit Cannabis profiling, comparing seized samples, is challenging due to natural Cannabis heterogeneity. The aim of this study was to use GC–FID and GC–MS herbal fingerprints for intra (within)- and inter (between)-location variability evaluation. This study focused on finding an acceptable threshold to link seized samples. Through Pearson correlation-coefficient calculations between intra-location samples, ‘linked’ thresholds were derived using 95% and 99% confidence limits. False negative (FN) and false positive (FP) error rate calculations, aiming at obtaining the lowest possible FP value, were performed for different data pre-treatments. Fingerprint-alignment parameters were optimized using Automated Correlation-Optimized Warping (ACOW) or Design of Experiments (DoE), which presented similar results. Hence, ACOW data, as reference, showed 54% and 65% FP values (95 and 99% confidence, respectively). An additional fourth root normalization pre-treatment provided the best results for both the GC–FID and GC–MS datasets. For GC–FID, which showed the best improved FP error rate, 54 and 65% FP for the reference data decreased to 24 and 32%, respectively, after fourth root transformation. Cross-validation showed FP values similar as the entire calibration set, indicating the representativeness of the thresholds. A noteworthy improvement in discrimination between seized Cannabis samples could be concluded.

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Section: Automated Correlation-optimized Warping (Acow)mentioning

confidence: 99%

Gas Chromatographic Fingerprint Analysis for the Comparison of Seized Cannabis Samples

et al. 2021

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“…For that reason, more sophisticated methods, such as Grubbs’ test, exist (Grubbs 1969). Recently, it was shown that modern technologies such as robust principal component analysis (PCA) for GC (Hubert and Engelen 2004, Moller and Jorgensen 2007) and the independent component analysis (ICA) can be used to determine the possible outlier patterns (Baragona and Battaglia 2007). In any case before applying such tests, the data should be normalized, as most statistical procedures for determining outliers are dependent on a normal distribution of the data.…”

Section: Outliersmentioning

confidence: 99%

Metabolite profile analysis: from raw data to regression and classification

Steinfath

Groth

Lisec

et al. 2007

Physiologia Plantarum

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Successful metabolic profile analysis will aid in the fundamental understanding of physiology. Here, we present a possible analysis workflow. Initially, the procedure to transform raw data into a data matrix containing relative metabolite levels for each sample is described. Given that, because of experimental issues in the technical equipment, the levels of some metabolites cannot be universally determined or that different experiments need to be compared, missing value estimation and normalization are presented as helpful preprocessing steps. Regression methods are presented in this review as tools to relate metabolite levels with other physiological properties like biomass and gene expression. As the number of measured metabolites often exceeds the number of samples, dimensionality reduction methods are required. Two of these methods are discussed in detail in this review. Throughout this article, practical examples illustrating the application of the aforementioned methods are given. We focus on the uncovering the relationship between metabolism and growth-related properties.

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“…A plot of the first 2 principal components is therefore representative for data scattering in 2-dimensional space. 28 , 29 …”

Section: Methodsmentioning

confidence: 99%

Reformulation of Traditional Chamomile Oil: Quality Controls and Fingerprint Presentation Based on Cluster Analysis of Attenuated Total Reflectance–Infrared Spectral Data

Zargaran

Sakhteman

Faridi

et al. 2017

J Evid Based Complementary Altern Med

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Herbal oils have been widely used in Iran as medicinal compounds dating back to thousands of years in Iran. Chamomile oil is widely used as an example of traditional oil. We remade chamomile oils and tried to modify it with current knowledge and facilities. Six types of oil (traditional and modified) were prepared. Microbial limit tests and physicochemical tests were performed on them. Also, principal component analysis, hierarchical cluster analysis, and partial least squares discriminant analysis were done on the spectral data of attenuated total reflectance–infrared in order to obtain insight based on classification pattern of the samples. The results show that we can use modified versions of the chamomile oils (modified Clevenger-type apparatus method and microwave method) with the same content of traditional ones and with less microbial contaminations and better physicochemical properties.

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Peak Alignment and Robust Principal Component Analysis of Gas Chromatograms of Fatty Acid Methyl Esters and Volatiles

Cited by 8 publications

References 21 publications

Gas Chromatographic Fingerprint Analysis for the Comparison of Seized Cannabis Samples

Gas Chromatographic Fingerprint Analysis for the Comparison of Seized Cannabis Samples

Metabolite profile analysis: from raw data to regression and classification

Reformulation of Traditional Chamomile Oil: Quality Controls and Fingerprint Presentation Based on Cluster Analysis of Attenuated Total Reflectance–Infrared Spectral Data

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