Self-loop Bidirectional Edge Recognition and Removal Method for Bidirectional Multi-step de Bruijn Graph

Abstract

The invention discloses a method for identifying and removing self-loop bidirectional edges of a bidirectional multistep De Bruijn graph, which comprises the following steps of: S1, reading a sequencing data source file and constructing the bidirectional multistep De Bruijn graph; S2, setting a data structure of each vertex u in the bidirectional multistep De Bruijn graph and identifying the self-loop bidirectional edges of the bidirectional multistep De Bruijn graph; and S3, removing the self-loop bidirectional edges of the bidirectional multistep De Bruijn graph. The method has the technical effects that (1) the method faces the bidirectional multistep De Bruijn graph; (2) according to target nodes of the self-loop bidirectional edges and target node directions of the self-loop bidirectional edges, the self-loop bidirectional edges are identified and distinguished; (3) according to the target node directions of the self-loop bidirectional edges, different self-loop bidirectional edge removal methods are adopted; and (4) error bidirectional edges can be effectively found and damage to correct bidirectional edges is avoided, so that the length of contigs is prolonged and more importantly, quality of contigs can be synchronously improved.

Description

technical field [0001] The invention relates to the field of gene sequencing, in particular to a self-loop bidirectional edge recognition and removal method of a bidirectional multi-step De Bruijn graph. Background technique [0002] Gene sequence analysis takes algorithms and mathematical models as the core, including: storage and acquisition of genetic data, sequence comparison, sequencing and splicing, gene prediction, biological evolution and phylogenetic analysis, protein structure prediction, RNA structure prediction, molecular design and drugs Design, metabolic network analysis, gene chip, DNA computing, etc. The close combination of biotechnology and computer information processing technology has accelerated the speed of processing biological information data, making accurate interpretation of biology in the shortest possible time and accelerating the development of bioinformatics. [0003] Gene sequence analysis is the analysis of massive gene sequence data to extr...

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Problems solved by technology

[0014] However, the above strategies for error correction and error removal are all based on the premise of uniform abundance, but in actual sequencing, some vertices are mistaken for error vertices due to the relatively low sequencing abundance, while SNPs or mutations in repetitive sequences are not. Possibly due to high deabundance, considered correct apex

In addition, the above-mentioned strategies are all for classifying and correcting the vertices of the De Bruijn graph, but for the identification and removal of self-loop bidirectional edges in the bidirectional multi-step De Bruijn graph, but none of them are involved.

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