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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
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| 2020 | |
| Source Publication | JOURNAL OF CHROMATOGRAPHY A
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| ISSN | 0021-9673 |
| Volume | 1620 |
| Abstract | Gas 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. |
| Keyword | QPMASS GC-MS Metabolomics Data analysis Parallel computing |
| Subject Area | Biochemical Research Methods ; Chemistry, Analytical |
| DOI | 10.1016/j.chroma.2020.460999 |
| Indexed By | SCI |
| Language | 英语 |
| WOS Keyword | GC/TOF-MS DATA ; DECONVOLUTION ; TOOL ; IDENTIFICATION ; METABOLITES ; EXTRACTION ; RNA |
| WOS Research Area | Biochemistry & Molecular Biology ; Chemistry |
| WOS ID | WOS:000530686600023 |
| Publisher | ELSEVIER |
| Subtype | Article |
| Publication Place | AMSTERDAM |
| EISSN | 1873-3778 |
| Funding Organization | National 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 Email | xqi@ibcas.ac.cn |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.ibcas.ac.cn/handle/2S10CLM1/21769 |
| Collection | 中科院植物分子生理学重点实验室 |
| Affiliation | 1.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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| File Name/Size | DocType | Version | Access | License | ||
| 1-s2.0-S002196732030（1910KB） | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | View Application Full Text | |
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