Metabolomics Data Preprocessing Using ADAP and MZmine 2.
Metabolomics Data Preprocessing Using ADAP and MZmine 2.
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DOI：
10.1007/978-1-0716-0239-3_3
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
Sumner S
中科院分区：
文献类型：
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作者：
Du X;Smirnov A;Pluskal T;Jia W;Sumner S
理解非目标 LC-MS 或 GC-MS 数据的信息学流程从预处理原始数据开始。数据预处理的结果经过统计分析，随后映射到代谢途径，以便将非目标代谢组学数据置于生物背景中。 ADAP 是一套专门为预处理 LC-MS 和 GC-MS 数据而开发的计算算法。它由两个独立的计算工作流程组成，分别从原始 LC-MS 和 GC-MS 数据中提取化合物相关信息。计算步骤包括构建提取的离子色谱图、检测色谱峰、光谱解卷积和对齐。这两个工作流程已合并到跨平台和图形 MZmine 2 框架中，并且开发了 ADAP 特定的图形用户界面，以便轻松使用 ADAP。本章总结了两个工作流程中关键步骤的算法原理，并说明了如何应用 ADAP 预处理 LC-MS 和 GC-MS 数据。
The informatics pipeline for making sense of untargeted LC–MS or GC–MS data starts with preprocessing the raw data. Results from data preprocessing undergo statistical analysis and subsequently mapped to metabolic pathways for placing untargeted metabolomics data in the biological context. ADAP is a suite of computational algorithms that has been developed specifically for preprocessing LC–MS and GC–MS data. It consists of two separate computational workflows that extract compound-relevant information from raw LC–MS and GC–MS data, respectively. Computational steps include construction of extracted ion chromatograms, detection of chromatographic peaks, spectral deconvolution, and alignment. The two workflows have been incorporated into the cross-platform and graphical MZmine 2 framework and ADAP-specific graphical user interfaces have been developed for using ADAP with ease. This chapter summarizes the algorithmic principles underlying key steps in the two workflows and illustrates how to apply ADAP to preprocess LC–MS and GC–MS data.