A method for automatic analysis of non-targeted metabolic profile data in uplc-hrms Profile mode

Abstract

The invention discloses a method for automatically analyzing non-target metabolic profile data in UPLC-HRMS Profile mode, which analyzes the non-target metabolic profile of the sample UPLC-HRMS to obtain chemical composition information in the sample. In this method, the UPLC-HRMS Profile mode data is first adaptively converted into Centroid mode data according to different instruments; on the basis of the converted chromatographic signal, clustering is performed according to the preset m / z accuracy, and the ion with the highest intensity is selected as the seed. Estimate the EIC range and calculate the ion density to realize the construction of EIC; use the local minimum value for all m / z corresponding EICs to achieve baseline correction; after baseline correction, use the multi-scale smooth convolution operation combined with the window expansion strategy to obtain the According to the position of the chromatographic peak, the corresponding chromatographic peak is extracted; the peak annotation is realized according to the similarity of the retention time and the shape of the chromatographic peak and the m / z difference of the fragment ions; and the identification of the fragment ions is realized according to the similarity of the peak height, and finally Realize automatic analysis of sample data.

Description

technical field [0001] The invention belongs to the technical field of ultra-high performance liquid chromatography-high resolution mass spectrometry data analysis, and in particular relates to a method for automatic analysis of non-target metabolic profile data in UPLC-HRMS Profile mode. Background technique [0002] In recent years, UPLC-HRMS (Ultra High Performance Liquid Chromatography-High Resolution Mass Spectrometry) has been widely used in the study of plant non-targeted metabolic profiling because it can conduct a more comprehensive analysis of the chemical components in the sample. Instruments from most manufacturers can provide two data acquisition modes: Centroid and Profile. However, a variety of data analysis methods are currently developed for the Centroid mode. In view of the possible loss of compound information and information redundancy in the current Centroid mode data, how can we directly perform rapid analysis and processing of the original Profile mode...

AI Technical Summary

Problems solved by technology

Although the methods and principles adopted by these tools have their own strengths, there are still many problems in these methods themselves, such as the inability to fully meet the analysis requirements for multiple instruments, and the poor quality of data conversion results may cause redundant results or Loss of compound information, etc.

Moreover, the problem of false positive and false negative chromatographic peaks still exists. The existence of false positive chromatographic peaks will interfere with the determination of substance components, leading to wrong judgments. The problem of false negatives is that the incomplete extraction of compound information will lead to serious loss of compound information.

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