文献类型： 外文期刊

作者： Ma, Gui-Mei ¹ ; Wang, Jia-Nan ¹ ; Wang, Xing-Cai ³ ; Ma, Feng-Lian ¹ ; Wang, Wen-Xin ¹ ; Li, Shu-Fang ⁴ ; Liu, Ping-Ping ⁵ ; Lv, Yi ⁶ ; Yu, Yong-Jie ¹ ; Fu, Hai-Yan ⁷ ; She, Yuanbin ³ ;

作者机构： 1.Ningxia Med Univ, Coll Pharm, Yinchuan 750004, Peoples R China

2.Ningxia Med Univ, Key Lab Ningxia Minor Med Modernizat, Minist Educ, Yinchuan 750004, Peoples R China

3.Zhejiang Univ Technol, Coll Chem Engn, Hangzhou 310032, Peoples R China

4.Henan Acad Agr Sci, Inst Qual Stand & Testing Technol Agroprod, Zhengzhou 450002, Peoples R China

5.Zhengzhou Tobacco Res Inst CNTC, Zhengzhou 450001, Peoples R China

6.Ningxia Food Testing & Res Inst, Wolfberry & Wine State Adm Market Regulat, Key Lab Qual & Safety, Yinchuan 750004, Peoples R China

7.South Cent Minzu Univ, Sch Pharmaceut Sci, Wuhan 430074, Peoples R China

期刊名称：ANALYTICAL CHEMISTRY （ 影响因子：7.4； 五年影响因子：7.0 ）

ISSN： 0003-2700

年卷期： 2024 年 96 卷 23 期

页码：

收录情况： SCI

摘要： Over the years, a number of state-of-the-art data analysis tools have been developed to provide a comprehensive analysis of data collected from gas chromatography-mass spectrometry (GC-MS). Unfortunately, the time shift problem remains unsolved in these tools. Here, we developed a novel comprehensive data analysis strategy for GC-MS-based untargeted metabolomics (AntDAS-GCMS) to perform total ion chromatogram peak detection, peak resolution, time shift correction, component registration, statistical analysis, and compound identification. Time shift correction was specifically optimized in this work. The information on mass spectra and elution profiles of compounds was used to search for inherent landmarks within analyzed samples to resolve the time shift problem across samples efficiently and accurately. The performance of our AntDAS-GCMS was comprehensively investigated by using four complex GC-MS data sets with various types of time shift problems. Meanwhile, AntDAS-GCMS was compared with advanced GC-MS data analysis tools and classic time shift correction methods. Results indicated that AntDAS-GCMS could achieve the best performance compared to the other methods.