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Data handling and data analysis in metabolomic studies of essential oils using GC-MS

Lebanov, L, Ghiasvand, A ORCID: 0000-0002-4570-7988 and Paull, B ORCID: 0000-0001-6373-6582 2021 , 'Data handling and data analysis in metabolomic studies of essential oils using GC-MS' , Journal of Chromatography A, vol. 1640 , pp. 1-19 , doi: 10.1016/j.chroma.2021.461896.

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Gas chromatography electron impact ionization mass spectrometry (GC-EI-MS) has been, and remains, the most widely applied analytical technique for metabolomic studies of essential oils. GC-EI-MS analysis of complex samples, such as essential oils, creates a large volume of data. Creating predictive models for such samples and observing patterns within complex data sets presents a significant challenge and requires application of robust data handling and data analysis methods. Accordingly, a wide variety of software and algorithms has been investigated and developed for this purpose over the years. This review provides an overview and summary of that research effort, and attempts to classify and compare different data handling and data analysis procedures that have been reported to-date in the metabolomic study of essential oils using GC-EI-MS.

Item Type: Article
Authors/Creators:Lebanov, L and Ghiasvand, A and Paull, B
Keywords: gas chromatography, electron impact ionization mass spectrometry, data handling, multivariate statistical analysis, essential oils
Journal or Publication Title: Journal of Chromatography A
Publisher: Elsevier Science Bv
ISSN: 0021-9673
DOI / ID Number: 10.1016/j.chroma.2021.461896
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© 2021 Elsevier B.V. All rights reserved

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