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QPMASS: A parallel peak alignment and quantification software for the analysis of large-scale gas chromatography-mass spectrometry (GC-MS)-based metabolomics datasets
Duan, Lixin1; Ma, Aimin2,3; Meng, Xianbin; Shen, Guo-an; Qi, Xiaoquan3
2020
Source PublicationJOURNAL OF CHROMATOGRAPHY A
ISSN0021-9673
Volume1620
AbstractGas chromatography-mass spectrometry (GC-MS) is a robust analytical platform for analysis of small molecules. Recently, it is widely used for large-scale metabolomics studies, in which hundreds or even thousands of samples are analyzed simultaneously, producing a very large and complex GC-MS datasets. A number of software are currently available for processing GC-MS data, but it is too compute-intensive for them to efficiently and accurately align chromatographic peaks from thousands of samples. Here, we report a newly developed software, QPMASS, for analysis of large-scale GC-MS data. The parallel computing with an advanced dynamic programming approach is implemented in QPMASS to align peaks from multiple samples based on retention time and mass spectra, enabling fast processing large-scale datasets. Furthermore, the missing value filtering and backfilling are introduced into the program, greatly reducing false positive and false negative errors to be less than 5%. We demonstrated that it took only 8 h to align and quantify a GC-TOF-MS dataset from 300 rice leaves samples, and 17 h to process a GC-qMS dataset from 1000 rice seed samples by using a personal computer (3.70 GHz CPU, 16 GB of memory and > 100 GB hard disk). QPMASS is written in C++ programming language, and is able to run under Windows operation system with a user-friendly interface. (C) 2020 Elsevier B.V. All rights reserved.
KeywordQPMASS GC-MS Metabolomics Data analysis Parallel computing
Subject AreaBiochemical Research Methods ; Chemistry, Analytical
DOI10.1016/j.chroma.2020.460999
Indexed BySCI
Language英语
WOS KeywordGC/TOF-MS DATA ; DECONVOLUTION ; TOOL ; IDENTIFICATION ; METABOLITES ; EXTRACTION ; RNA
WOS Research AreaBiochemistry & Molecular Biology ; Chemistry
WOS IDWOS:000530686600023
PublisherELSEVIER
SubtypeArticle
Publication PlaceAMSTERDAM
EISSN1873-3778
Funding OrganizationNational Key Research and Development Program of China [2016YFD0100904] ; Strategic Priority Research Program of the Chinese Academy of SciencesChinese Academy of Sciences [XDB27010202] ; National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [31530050, 81874333, 31570306] ; Science and Technology Program of Guangzhou, China [2018-1002-SF-0437]
Corresponding Author Emailxqi@ibcas.ac.cn
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Cited Times:8[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ibcas.ac.cn/handle/2S10CLM1/21769
Collection中科院植物分子生理学重点实验室
Affiliation1.Chinese Acad Sci, Inst Bot, Key Lab Plant Mol Physiol, Beijing 100093, Peoples R China
2.Guangzhou Univ Chinese Med, Int Inst Translat Chinese Med, Guangzhou 510006, Peoples R China
3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
4.Chinese Acad Sci, Innovat Acad Seed Design, Beijing 100049, Peoples R China
5.Chinese Acad Med Sci, Peking Union Med Coll, Inst Med Plant Dev, Beijing 100193, Peoples R China
Recommended Citation
GB/T 7714
Duan, Lixin,Ma, Aimin,Meng, Xianbin,et al. QPMASS: A parallel peak alignment and quantification software for the analysis of large-scale gas chromatography-mass spectrometry (GC-MS)-based metabolomics datasets[J]. JOURNAL OF CHROMATOGRAPHY A,2020,1620.
APA Duan, Lixin,Ma, Aimin,Meng, Xianbin,Shen, Guo-an,&Qi, Xiaoquan.(2020).QPMASS: A parallel peak alignment and quantification software for the analysis of large-scale gas chromatography-mass spectrometry (GC-MS)-based metabolomics datasets.JOURNAL OF CHROMATOGRAPHY A,1620.
MLA Duan, Lixin,et al."QPMASS: A parallel peak alignment and quantification software for the analysis of large-scale gas chromatography-mass spectrometry (GC-MS)-based metabolomics datasets".JOURNAL OF CHROMATOGRAPHY A 1620(2020).
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