کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5130589 1490842 2017 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
An alignment algorithm for LC-MS-based metabolomics dataset assisted by MS/MS information
موضوعات مرتبط
مهندسی و علوم پایه شیمی شیمی آنالیزی یا شیمی تجزیه
پیش نمایش صفحه اول مقاله
An alignment algorithm for LC-MS-based metabolomics dataset assisted by MS/MS information
چکیده انگلیسی


- A MS/MS-based peak alignment method for LC-MS metabolomics data was developed.
- A rigorous strategy for screening endogenous reference variables was proposed.
- MS/MS data were used to screen rigorous endogenous reference variables and in further peak alignment.
- The developed method had good performance, especially for metabolomics data with larger retention time drift.

Liquid chromatography-mass spectrometry (LC-MS) is an important analytical platform for metabolomics study. Peak alignment of metabolomics dataset is one of the keys for a successful metabolomics study. In this work, a MS/MS-based peak alignment method for LC-MS metabolomics data was developed. A rigorous strategy for screening endogenous reference variables was proposed. Firstly, candidate endogenous reference variables were selected based on MS, MS/MS and retention time in all samples. Multiple robust endogenous reference variables were obtained through further evaluation and confirmation. Then retention time of each metabolite feature was corrected by local linear regression using the four nearest neighbor robust reference variables. Finally, peak alignment was carried out based on corrected retention time, MS and MS/MS. Comparing with the other two peak alignment methods, the developed method showed a good performance and was suitable for metabolomics data with larger retention time drift. Our approach provides a simple and robust alignment method which is reliable to align LC-MS metabolomics dataset.

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ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Analytica Chimica Acta - Volume 990, 16 October 2017, Pages 96-102
نویسندگان
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