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基于气相色谱-质谱的非靶向发现分析:峰表、平铺和像素的 Fisher 比分析比较。

Non-targeted discovery-based analysis for gas chromatography with mass spectrometry: A comparison of peak table, tile, and pixel-based Fisher ratio analysis.

机构信息

Los Alamos National Laboratory, M-7, High Explosives Science and Technology, Los Alamos, NM, 87545, USA.

Los Alamos National Laboratory, M-7, High Explosives Science and Technology, Los Alamos, NM, 87545, USA.

出版信息

Talanta. 2020 May 1;211:120668. doi: 10.1016/j.talanta.2019.120668. Epub 2019 Dec 28.

Abstract

The ability to discover minute differences between samples or sample classes for gas chromatography coupled to mass spectrometry (GC-MS) can be a challenging endeavor, especially when those differences are not a priori. Fisher ratio (F-ratio) analysis is an apt technique to probe the differences between GC-MS chromatograms. F-ratio analysis is a supervised, non-targeted, discovery-based method that compares two different samples (or sample classes) to reduce the GC-MS dataset into a hit list composed of class distinguishing compounds. Three different F-ratio techniques, peak table, tile, and pixel-based were used to "discover" nine non-native analytes that were spiked into gasoline at four different nominal concentrations of 250, 85, 25, 5 parts-per-million (ppm). For the tile and pixel-based F-ratio calculations, a novel methodology is introduced to improve the sensitivity of the F-ratio calculations while reducing false positives. Furthermore, we use a combinatorial technique using null class comparisons, termed null distribution analysis, to determine a statistical F-ratio cutoff for analysis of the hit lists. The pixel-based algorithm was the most sensitive method and was able to "discover" all nine spiked analytes at a nominal concentration of 250 ppm albeit with one false positive interspersed towards the bottom of the hit list. The pixel-based software was also able to "discover" more of the spiked analytes at the lower concentrations with seven of the spiked analytes "discovered" at 85 ppm, four of the spiked analytes "discovered" at 25 ppm, and one analyte "discovered" at 5 ppm.

摘要

对于气相色谱-质谱联用(GC-MS)来说,发现样品或样品类别之间微小差异的能力可能是一项具有挑战性的任务,特别是当这些差异不是先验的。Fisher 比(F-ratio)分析是一种探测 GC-MS 色谱图差异的合适技术。F-ratio 分析是一种基于监督、非靶向、发现的方法,它比较两个不同的样品(或样品类别),将 GC-MS 数据集减少到一个由区分化合物组成的命中列表。使用三种不同的 F-ratio 技术,即峰表、平铺和基于像素的方法,“发现”了九种非天然分析物,这些分析物以四个不同的名义浓度(250、85、25、5 百万分率(ppm))被注入到汽油中。对于平铺和基于像素的 F-ratio 计算,引入了一种新的方法来提高 F-ratio 计算的灵敏度,同时减少假阳性。此外,我们使用一种组合技术,使用空类比较,称为空分布分析,来确定用于分析命中列表的统计 F-ratio 截止值。基于像素的算法是最敏感的方法,尽管在命中列表的底部有一个假阳性穿插,但能够以 250 ppm 的名义浓度“发现”所有九种注入的分析物。基于像素的软件还能够以 85 ppm 的浓度“发现”更多注入的分析物,其中七种注入的分析物“发现”,四种注入的分析物“发现”,一种分析物“发现”在 5 ppm 时。

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