Biomolecular omics mass spectrometric data structure based on data independent acquisition technology and implementation method thereof

Abstract

The invention relates to the technical field of biomolecular omics mass spectrometric data, especially to a biomolecular omics mass spectrometric data structure based on data independent acquisition mass spectrometry and an implementation method thereof. The mass spectrometric data structure is data independent acquisition tensor (DIAT) data generated by original mass spectrometric data and has attributes of three dimensions, wherein the first dimension is a cycle index, the second dimension is a fragment ion mass-to-charge ratio, and the third dimension is a precursor ion window index corresponding to fragment ions. According to a scheme in the invention, the DIAT data is high in integrity, convenient to read and high in reading; the size of a DIAT file is only one tenth of the size of amzXML file; DIA mass spectrometric data can be directly observed through a visualized pooled DIAT file image; DIAT can be analyzed by directly using a visual processing algorithm; the large-calculation-amount operation of extracting ion chromatographic peaks is avoided; and a computer deep learning model for clinical sample classification can be directly established according to the file.

Description

technical field [0001] The invention relates to the technical field of biomolecular omics mass spectrometry data, in particular to a biomolecular omics mass spectrometry data structure based on data-independent acquisition of mass spectra and an implementation method thereof. Background technique [0002] Omics based on mass spectrometry (Mass Spectrum, abbreviated as MS) has been developed for decades, and has developed applications that can use it to perform spectral analysis of thousands of biomolecules in complex biological samples within hours . Biomolecules are separated by liquid chromatography (liquid chromatography, abbreviated as LC) and identified and quantified by tandem mass spectrometry (MS / MS) fragment ion spectrum, and thus identify and quantify biomolecules. Applications include proteomics, metabolomics and lipidomics. [0003] Mass spectrometry-based omics currently has the following acquisition modes: [0004] 1. Data-dependent acquisition (DDA for shor...

AI Technical Summary

Problems solved by technology

In addition, due to the loss of the relationship between precursor ions and fragment ions in DIA, the co-eluting precursor ions will co-fragment in the same window, resulting in highly complex fragment mass spectra, which requires prior knowledge of the target molecule in DDA. information, including the mass-to-charge ratio of the precursor, the mass-to-charge ratio of its fragment ions, and the corresponding relative intensities and retention times, etc., and then extract ion chromatogram peaks (XIC) to deduce the peak groups belonging to the target molecule, which consumes a lot of computing resources and time, and often leads to data distortion

Although a variety of existing DIA analysis software, such as OpenSWATH software, Skyline software, Spectronaut software, PeakView software, etc., can realize the functions of identifying and quantifying biomolecules, these programs are not easy to operate and consume time and computing resources, and only Part of the MS / MS spectrum is used for peak group inference, which will produce unpredictable effects (for example: inevitable missing value problem), which will affect the downstream statistical classification analysis

[0008] Therefore, the existing mass spectrometry data structure is not suitable for storing and analyzing the large-scale data generated by the new independent mass spectrometry acquisition method

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