Automatic time-shift alignment method for chromatographic data analysis

Abstract Time shift among samples remains a significant challenge in data analysis, such as quality control of natural plant extracts and metabolic profiling analysis, because this phenomenon may lead to invalid conclusions. In this work, we propose a new time shift alignment method, namely, automat...

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Autores principales: Qing-Xia Zheng, Hai-Yan Fu, He-Dong Li, Bing Wang, Cui-Hua Peng, Sheng Wang, Jun-Lan Cai, Shao-Feng Liu, Xiao-Bing Zhang, Yong-Jie Yu
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2017
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Acceso en línea:https://doaj.org/article/1a28e3286a0b4e72ad45e9c7c66e70dd
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Sumario:Abstract Time shift among samples remains a significant challenge in data analysis, such as quality control of natural plant extracts and metabolic profiling analysis, because this phenomenon may lead to invalid conclusions. In this work, we propose a new time shift alignment method, namely, automatic time-shift alignment (ATSA), for complicated chromatographic data analysis. This technique comprised the following alignment stages: (1) automatic baseline correction and peak detection stage for providing useful chromatographic information; (2) preliminary alignment stage through adaptive segment partition to correct alignment for the entire chromatogram; and (3) precise alignment stage based on test chromatographic peak information to accurately align time shift. In ATSA, the chromatographic peak information of both reference and test samples can be completely employed for time-shift alignment to determine segment boundaries and avoid loss of information. ATSA was used to analyze a complicated chromatographic dataset. The obtained correlation coefficients among samples and data analysis efficiency indicated that the influences of time shift can be considerably reduced by ATSA; thus accurate conclusion could be obtained.