Denovo sequencing method and device

Abstract

The invention provides a denovo sequencing method. The method comprises the following steps: transforming a to-be-analyzed spectrogram into a mass spectrum connection diagram, counting the score of each path in the mass spectrum connection diagram, extracting a plurality of front normal paths with high path score and a modification path as a candidate peptide fragment, wherein the normal path is the path only formed by normal sides, and the modification path is the path formed by the normal side and a modification side, and only contains one modification side; performing peptide spectrum matching scoring on each candidate peptide fragments, and taking the candidate peptide fragment with the highest peptide spectrum matching scoring as the peptide fragment corresponding to the spectrogram. By use of the method disclosed by the invention, the discovery of thousands of accident modificaitons can be supported without greatly influencing the peptide fragment identification speed; furthermore, the similar peptide fragment sequences can be distinguished in finer granularity, and the accuracy rate of the peptide identification is improved.

Description

technical field [0001] The invention belongs to bioinformatics, and in particular relates to the identification of de novo sequencing peptides. Background technique [0002] Proteomics has developed rapidly in the past ten years. When researchers use mass spectrometry to analyze biological samples, peptide and protein identification methodology has become a very critical link. Currently, peptide identification methods based on tandem mass spectrometry data are mainly divided into two categories: database search methods and de novo sequencing methods. The database search method finds all candidate peptides from the database for each spectrum and scores the matches. However, if the correct peptide is not in the database, such as a new species or a species whose genome has not been sequenced, de novo sequencing is usually used. The de novo sequencing method does not depend on the database, and obtains the peptide sequence directly from the spectrum. [0003] However, compare...

AI Technical Summary

Problems solved by technology

If the de novo sequencing algorithm is to support the discovery of thousands of unexpected modifications, the number of candidate peptides to be processed will increase by at least two orders of magnitude, which will undoubtedly greatly reduce the speed of peptide identification

Moreover, after considering thousands of accidental modifications, the sequence similarity between candidate peptides is very close and even the element composition is completely identical, making it difficult to distinguish similar peptide sequences

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