Center of Membrane Biochemistry and Lipid Research, Faculty of Medicine Carl Gustav Carus of TU Dresden, Dresden, Germany.
Systems Immunity Research Institute, School of Medicine, Cardiff University, Cardiff, UK.
Nat Methods. 2023 Feb;20(2):193-204. doi: 10.1038/s41592-022-01710-0. Epub 2022 Dec 21.
Progress in mass spectrometry lipidomics has led to a rapid proliferation of studies across biology and biomedicine. These generate extremely large raw datasets requiring sophisticated solutions to support automated data processing. To address this, numerous software tools have been developed and tailored for specific tasks. However, for researchers, deciding which approach best suits their application relies on ad hoc testing, which is inefficient and time consuming. Here we first review the data processing pipeline, summarizing the scope of available tools. Next, to support researchers, LIPID MAPS provides an interactive online portal listing open-access tools with a graphical user interface. This guides users towards appropriate solutions within major areas in data processing, including (1) lipid-oriented databases, (2) mass spectrometry data repositories, (3) analysis of targeted lipidomics datasets, (4) lipid identification and (5) quantification from untargeted lipidomics datasets, (6) statistical analysis and visualization, and (7) data integration solutions. Detailed descriptions of functions and requirements are provided to guide customized data analysis workflows.
质谱脂质组学的进展使得生物学和生物医学领域的研究迅速增多。这些研究产生了极其庞大的原始数据集,需要复杂的解决方案来支持自动化数据处理。为此,已经开发了许多专门针对特定任务的软件工具。然而,对于研究人员来说,决定哪种方法最适合他们的应用需要进行特定的测试,这既低效又耗时。在这里,我们首先回顾了数据处理管道,总结了可用工具的范围。接下来,为了支持研究人员,LIPID MAPS 提供了一个交互式在线门户,列出了具有图形用户界面的开放访问工具。这引导用户在数据处理的主要领域内找到合适的解决方案,包括(1)面向脂质的数据库,(2)质谱数据存储库,(3)靶向脂质组学数据集的分析,(4)脂质鉴定和(5)非靶向脂质组学数据集的定量,(6)统计分析和可视化,以及(7)数据集成解决方案。提供了详细的功能和要求描述,以指导定制数据分析工作流程。