PeakClimber:使用指数高斯函数分析生物 HPLC 数据的软件工具

Joshua T. Derrick, Steven A. Farber, William B. Ludington
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引用次数: 0

摘要

高效液相色谱法(HPLC)是分析代谢样本的常用中通量技术。然而,高效液相色谱数据的分析却因缺乏工具而受到阻碍,因为没有工具能在与质谱方法相当的精度水平上准确确定分析物的精确数量。为了解决这个问题,我们开发了一种称为 PeakClimber 的工具,它使用指数高斯函数之和来精确量化 HPLC 曲线中的峰值。在本文中,我们通过分析表明,高效液相色谱峰与指数高斯函数拟合良好,PeakClimber 比标准工业软件更能准确量化已知峰面积,并利用 PeakClimber 实现了脂质生物学的新发现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PeakClimber: A software tool for analyzing biological HPLC data using the exponential Gaussian function
High-performance liquid chromatography (HPLC) is a common medium-throughput technique to analyze metabolic samples. However, analysis of HPLC data is hampered by a lack of tools to accurately determine the precise analyte quantities on a level of precision equivalent to mass-spectrometry approaches. To combat this problem, we developed a tool we call PeakClimber, that uses a sum of exponential Gaussian functions to accurately quantify the peaks in HPLC traces. In this paper we analytically show that HPLC peaks are well-fit by an exponential Gaussian function, that PeakClimber more accurately quantifies known peak areas than standard industry software and utilize PeakClimber to make new discoveries about lipid biology.
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