QPMASS: A parallel peak alignment and quantification software for the analysis of large-scale gas chromatography-mass spectrometry (GC-MS)-based metabolomics datasets
QPMASS: A parallel peak alignment and quantification software for the analysis of large-scale gas chromatography-mass spectrometry (GC-MS)-based metabolomics datasets
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QPMASS：并行峰对齐和定量软件，用于分析基于气相色谱-质谱 (GC-MS) 的大规模代谢组学数据集
DOI：
10.1016/j.chroma.2020.460999
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发表时间：
2020-06-07
影响因子：
4.1
通讯作者：
Qi, Xiaoquan
中科院分区：
文献类型：
--
作者：
Duan, Lixin;Ma, Aimin;Qi, Xiaoquan
气相色谱-质谱 (GC-MS) 是用于分析小分子的强大分析平台。最近，它被广泛用于大规模代谢组学研究，其中同时分析数百甚至数千个样本，产生非常大且复杂的GC-MS数据集。目前有许多软件可用于处理 GC-MS 数据，但计算量太大，无法高效、准确地对齐数千个样品的色谱峰。在这里，我们报告了一种新开发的软件 QPMASS，用于分析大规模 GC-MS 数据。 QPMASS 中采用先进的动态编程方法进行并行计算，根据保留时间和质谱来对齐多个样品的峰，从而能够快速处理大规模数据集。此外，程序中引入了缺失值过滤和回填，大大降低了误报和误报错误，使其低于5%。我们证明，使用个人计算机（3.70 GHz CPU、16 GB 内存和 > 100 GB 硬盘）仅需 8 小时即可对齐和量化 300 个水稻叶片样本的 GC-TOF-MS 数据集，并需要 17 小时处理 1000 个水稻种子样本的 GC-qMS 数据集。 QPMASS采用C++编程语言编写，能够运行在Windows操作系统下，具有友好的用户界面。 (C) 2020 Elsevier B.V. 保留所有权利。
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.