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metabCombiner 2.0:对LC-MS代谢学进行不一致的多数据集特征对齐

Hani Habra¹, Jennifer L Meijer², Tong Shen³

¹Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI 48109, USA.

|February 23, 2024

概括

这项研究增强了metabCombiner,用于调整来自多重液态染色学高分辨率质谱 (LC-HRMS) 实验的非目标代谢学数据. 升级的工具通过使复杂的数据集逐步对齐,提高了实验室间的可重复性.

科学领域:

分析化学分析化学
代谢学代谢学代谢学
生物信息学是一种生物信息学.

背景情况:

使用液体染色学-高分辨率质谱学 (LC-HRMS) 的非目标代谢学产生了复杂的数据集,需要强大的数据处理.
数据对齐对于整合来自多个LC-MS实验的特征至关重要,特别是在不同的实验室或批量中.
分析因子的变化使对齐变得复杂,阻碍了实验室间的可重复性和大规模研究的整合.

研究的目的:

显著升级metabCombiner软件,以加强对多个非目标LC-MS代谢学数据集的对齐.
通过逐步调整不同获得的数据来促进实验室间可重复性研究.
在 metabCombiner 框架内引入 batchCombine,用于对齐包含多个批次的实验.

主要方法:

使用"主"特征列表作为匹配"目标"特征列表的模板进行逐步对齐工作流程的开发.
应用升级的metabCombiner来调整来自不同核心实验室的四个脂质组学数据集,使用不同的LC-MS仪器和方法.
实施batchCombine,利用metaBcombiner框架进行多批次实验对齐.

主要成果:

在四个脂管组学数据集中逐步对齐的成功演示,验证了增强的metaboCombiner的能力.
升级的metabCombiner有效地促进了在不同实验室条件下获得的LC-HRMS数据的集成.
批量组合 (batchCombine) 提供了一个强大的解决方案,用于与多个分析批量对齐实验.

结论:

增强的metabCombiner显著改善了非目标LC-HRMS代谢学数据的对齐,提高了实验室间的可重复性.
新的工作流和batchCombine应用程序解决了处理复杂,多批和多实验室代谢学研究的关键挑战.
metabCombiner现在以R包和在线R闪亮应用程序的形式提供,为研究社区提高了可访问性.

关键词:

这就是LC-MS.一个R包一个R包调整对齐的情况染色体学染色体学染色体学代谢生物组的代谢生物组软件软件软件软件软件

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