Garcia-Aloy Mar, Rainer Johannes, Franceschi Pietro
Research and Innovation Centre, Fondazione E. Mach, Trento, Italy.
Institute for Biomedicine, Eurac Research, Bolzano, Italy.
Methods Mol Biol. 2025;2891:91-108. doi: 10.1007/978-1-0716-4334-1_5.
Liquid Chromatography-Mass Spectrometry (LC-MS) untargeted experiments require complex bioinformatic strategies to extract information from the experimental data. Here we discuss the "data preprocessing," the set of procedures performed on the raw data to produce a data matrix which will be the starting point for the subsequent statistical analysis. Data preprocessing is a crucial step on the path to knowledge extraction, which should be carefully controlled and optimized in order to maximize the output of any untargeted metabolomics investigation.
液相色谱 - 质谱联用（LC-MS）非靶向实验需要复杂的生物信息学策略从实验数据中提取信息。在此，我们讨论“数据预处理”，即在原始数据上执行的一系列程序，以生成一个数据矩阵，该矩阵将作为后续统计分析的起点。数据预处理是知识提取过程中的关键步骤，应仔细控制和优化，以最大限度地提高任何非靶向代谢组学研究的产出。
