评估基于GC的代谢学标准化策略
Seo Lin Nam1,2, Ryland T Giebelhaus1,2, Kieran S Tarazona Carrillo1,2
1Department of Chemistry, University of Alberta, Edmonton, AB, T6G 2G2, Canada.
Metabolomics : Official journal of the Metabolomic Society
|February 12, 2024
概括
一种新的方法,总衍生峰值面积 (TDPA),改善了基于GC的代谢学中的数据正常化. TDPA和总有用峰值面积 (TUPA) 有效地分离样本类别,提高数据可靠性.
科学领域:
- 代谢学 代谢学 代谢学
- 分析化学 分析化学
- 气体染色学 是一种气体染色学.
背景情况:
- 基于GC的代谢学需要广泛的样本准备,包括衍生物化 (甲氧化和三甲基化/TMS).
- 准确的数据规范化对于纠正样本准备和分析中的变化和偏差至关重要.
- 有效的规范化提高了下游代谢学数据分析和解释的可靠性.
研究的目的:
- 引入和评估一种新的规范化方法,总衍生峰值面积 (TDPA),用于基于GC的代谢学.
- 将TDPA与现有方法比较,例如对样本质量和总峰值面积 (TPA) 的规范化.
- 评估不同规范化策略在分离样本类别中的有效性.
主要方法:
- 模拟的样本类别具有不同的氨基酸度和系统增量样本质量.
- 样品经过TMS衍生和分析,使用全面的二维气体染色学-飞行时间质谱法 (GC×GC-TOFMS).
- 评估了五种规范化策略:没有规范化,样本质量,TPA,总有用峰值面积 (TUPA) 和TDPA.
主要成果:
- 总有用峰值面积 (TUPA) 和总衍生峰值面积 (TDPA) 在测试方法中表现出最高的有效性.
- 无论是TUPA还是TDPA,都能够在主要组件分析 (PCA) 评分空间中清晰地分离样本类.
- 在所有样本中不需要峰值对齐,TDPA提供了一个优势.
结论:
- 与传统方法相比,TUPA和TDPA是基于GC的代谢学优越的正常化策略.
- TDPA提供了一个方便和有效的替代方案,克服了TUPA所需的样本范围峰值对齐的需要.
- 这些发现有助于解决代谢学中的数据规范化挑战,改善数据的可用性.
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