Removal of false positive features to generate authentic peak table for high-resolution mass spectrometry-based metabolomics study

doi:10.1016/j.aca.2019.04.011

	Removal of false positive features to generate authentic peak table for high-resolution mass spectrometry-based metabolomics study
	Ju, Ran 1; Liu, Xinyu 2; Zheng, Fujian 2; Zhao, Xinjie 2; Lu, Xin 2; Zeng, Zhongda 2,3; Lin, Xiaohui 1; Xu, Guowang 2
刊名	ANALYTICA CHIMICA ACTA
	2019-08-27
卷号	1067 页码:79-87
关键词	High-resolution mass spectrometry Metabolomics False positive features Data quality
ISSN号	0003-2670
DOI	10.1016/j.aca.2019.04.011
通讯作者	Zeng, Zhongda(ZENG@chemdatasolution.com) ; Lin, Xiaohui(datas@dlut.edu.cn) ; Xu, Guowang(xugw@dicp.ac.cn)
英文摘要	In metabolomics research, false positive features from non-sample sources and noises usually exist in the peak table, they will make the results of screening differential metabolites or biomarkers unreliable. In this study, a method to remove false positive features (rFPF) was developed to improve the quality of the peak table. rFPF recognizes real peak profiles based on the information entropy and statistical correlation, and eliminates false positive features from non-sample sources and noises. A standard mixture with 42 standards (14 isotopic labeled internal standards and 28 common standards) and a urine sample were applied to evaluate the effectiveness of the rFPF method. The analysis results of metabolite standards showed that more than 92% false positive features were removed by rFPF, but target standards completely remained. The analysis results of urine sample showed that the number of features was significantly reduced from 7182 to 2522. Interestingly, 98% of the identified metabolites remained after removing false positive features. The proposed rFPF shows great prospects as a new data handling method for metabolomics studies. (C) 2019 Elsevier B.V. All rights reserved.
资助项目	National Natural Science Foundation of China[81472374] ; National Natural Science Foundation of China[21375011] ; National Key Research and Development Program of China[2017YFC0906900] ; innovation program of science and research from the DICP, CAS[DICP TMSR201601]
WOS关键词	LARGE-SCALE ; QUANTIFICATION ; IDENTIFICATION ; ANNOTATION ; STRATEGIES ; ALIGNMENT
WOS研究方向	Chemistry
语种	英语
出版者	ELSEVIER SCIENCE BV
WOS记录号	WOS:000466150300008
资助机构	National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Key Research and Development Program of China ; National Key Research and Development Program of China ; innovation program of science and research from the DICP, CAS ; innovation program of science and research from the DICP, CAS ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Key Research and Development Program of China ; National Key Research and Development Program of China ; innovation program of science and research from the DICP, CAS ; innovation program of science and research from the DICP, CAS ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Key Research and Development Program of China ; National Key Research and Development Program of China ; innovation program of science and research from the DICP, CAS ; innovation program of science and research from the DICP, CAS ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Key Research and Development Program of China ; National Key Research and Development Program of China ; innovation program of science and research from the DICP, CAS ; innovation program of science and research from the DICP, CAS
内容类型	期刊论文
源URL	[http://cas-ir.dicp.ac.cn/handle/321008/165512]
专题	大连化学物理研究所_中国科学院大连化学物理研究所
通讯作者	Zeng, Zhongda; Lin, Xiaohui; Xu, Guowang
作者单位	1.Dalian Univ Technol, Sch Comp Sci & Technol, Dalian 116024, Peoples R China 2.Chinese Acad Sci, Dalian Inst Chem Phys, CAS Key Lab Separat Sci Analyt Chem, Dalian 116023, Peoples R China 3.Dalian ChemDataSolut Informat Technol Co Ltd, Dalian 116023, Peoples R China
推荐引用方式 GB/T 7714	Ju, Ran,Liu, Xinyu,Zheng, Fujian,et al. Removal of false positive features to generate authentic peak table for high-resolution mass spectrometry-based metabolomics study[J]. ANALYTICA CHIMICA ACTA,2019,1067:79-87.
APA	Ju, Ran.,Liu, Xinyu.,Zheng, Fujian.,Zhao, Xinjie.,Lu, Xin.,...&Xu, Guowang.(2019).Removal of false positive features to generate authentic peak table for high-resolution mass spectrometry-based metabolomics study.ANALYTICA CHIMICA ACTA,1067,79-87.
MLA	Ju, Ran,et al."Removal of false positive features to generate authentic peak table for high-resolution mass spectrometry-based metabolomics study".ANALYTICA CHIMICA ACTA 1067(2019):79-87.