The invention relates to an oxidized
fatty acid large-scale qualitative method based on non-targeted metabonomics. The method comprises the following steps: firstly, enriching oxidized
fatty acid in a biological sample to obtain non-targeted metabonomics data; secondly, constructing a self-built
database which comprises an oxidized
fatty acid mass spectrum
library, an oxidized fatty acid structure
library and an
in silico oxidized fatty acid
virtual structure library; and then, carrying out self-established
virtual database search on data of an oxidized fatty acid extraction sample, and carrying out large-scale identification on the oxidized fatty acid by comparing a first-level
ion mass-to-charge ratio, a second-level
mass spectrum and / or second-level
ion characteristic fragments,
retention time and an in-source
cracking mode. And finally, co-constructing a
molecular network by the secondary mass spectra recorded in all the databases, the identified secondary mass spectra in the samples and the secondary mass spectra of all the unknown metabolites in the samples based on secondary similarity, and carrying out expansion
annotation on the unknown oxidized fatty acid through a metabolic reaction relationship.