Genome sequence splicing method based on protein information

Abstract

The invention discloses a genome sequence splicing method based on protein information. The method comprises the steps: obtaining the comparison information between DNA sequences and protein sequencesto be spliced; determining the adjacent relationship between the corresponding DNA sequences on each protein sequence; constructing the connecting sides between the adjacent DNA sequences and obtaining the supporting information of the corresponding connecting sides of each DNA sequence on each protein sequence; denoising the supporting information of the connecting sides of each DNA sequence inturn; denoising the front and back nodes of each DNA sequence in turn based on the weight scoring function; calculating the connecting spacing of all the DNA sequence connecting sides in which the supporting information exists; and obtaining the genome sequence splicing path by series connection of the front and back nodes of each DNA sequence based on the connecting spacing between the connectingsides of all the DNA sequences. The sensitivity and the accuracy of the genome sequence splicing result can be improved by the method.

Description

technical field [0001] The invention belongs to the field of bioinformatics, and in particular relates to a genome sequence splicing method based on protein information. Background technique [0002] The low-cost development of new sequencing technologies has dramatically changed the whole-genome sequencing landscape, enabling scientists to launch numerous genome projects to decode the genomes of previously unsequenced organisms. Sequencing technologies enable deep sequencing of most species, including mammals, in just a few days. But DNA sequencing technologies cannot directly generate complete sequences at the chromosome level. Instead, they generate large numbers of reads, sampling contiguous bases ranging in length from tens to thousands of bases from different parts of the genome. Genome assembled long reads are assembled from millions or billions of short-length DNA sequence reads generated by sequencing technologies. [0003] Due to the lack of a reference genome fo...

AI Technical Summary

Problems solved by technology

[0008] The accuracy of the tool ESPRIT depends on the predicted gene set, and the extremely time-consuming nature of gene prediction limits the practical application of ESPRIT

Similarly, in order to improve the matching between sequences, SWiPS needs to compare protein sequences and genome sequences many times, which also takes a lot of time.

The tool PEP_scaffolder will directly delete the protein sequence with too large matching coverage, which will damage the sensitivity of the scaffolding results to a certain extent

Therefore, the existing scaffolding methods cannot meet the sensitivity and accuracy requirements

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