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Fig 1 | BioData Mining

Fig 1

From: Label-free data standardization for clinical metabolomics

Fig 1

The concept for label-free standardization of metabolomics data. The actual concentrations of substances in the blood plasma sample cover several orders of magnitude (a). When the substances are plotted according to their decreasing peak intensity, their distribution obeys the power function (b). This function helps to find the knee point for this distribution, which is defined by the assemblage of substances that makes it tolerant to concentration fluctuations of separate substances. Moreover, the knee point is independent of the LOD of the method, which may affect only the lower tail of the curve presented on the plot. While the substances demonstrate a high concentration variation (e.g., average CV for biological variation of the blood plasma metabolites is equal to 46% [6]), the knee point demonstrates a relatively low CV (7.7%). So, since the knee point is stable, it may be used as a internal standard that is represented in all blood plasma samples. This artwork was prepared as an example using actual mass spectrometric data for human blood plasma metabolites in the m/z range of 225–275 (see details in Methods). R2, coefficient of determination for the substances arranged according to their decreasing peak intensities and the power function

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