Optimized detection method for virus sequence integration

Abstract

The invention provides an optimized detection method for virus sequence integration. The method comprises the following steps: screening out a reference sequence of virus from a second-generation sequencing sequence; comparing the second-generation sequencing sequence by adopting a BWA-MEM algorithm to obtain an input file, wherein the sequence comparing result in the input file comprises a comparing result of a sequence completely matched to a host genome, a comparing result of a sequence completely matched to a virus genome and a comparing result of a sequence partially matched to the host genome and partially matched to the virus genome; extracting the integrated sequences from the input file, and performing quality control on the sequences to filter out any one sequence which does notmeet a preset condition; automatically identifying the type of each sequence passing the quality control; after identification of the type of the integrated sequence is completed, starting clustering,wherein clustering is conducted on each chromosome and each conformation of the host; and making a breakpoint decision for each class, and implementing different operations according to different conditions of the breakpoints of each class.

Description

technical field [0001] The invention relates to the technical field of viral sequence detection, in particular to an optimized detection method for viral sequence integration. Background technique [0002] Among human cancers, many cancers are associated with viral infections. For example, almost all cervical cancer patients are infected with human papillomavirus (HPV), and HPV can be detected in about 50% of cancers related to viral infection suffered by women. As another example, among liver cancer patients worldwide, 74% of the cases are infected with hepatitis B virus (hepatitis B virus, HBV) or (and) hepatitis C virus (hepatitis C virus, HCV). [0003] Currently, there are three main issues that hinder the development of integrated virus integration algorithms and processes. [0004] 1. Due to the high mutation rate of the virus during replication, virus quasi-strains containing different mutation lineages will be formed in the host. In this case, the reference seque...

AI Technical Summary

Problems solved by technology

Although both methods can solve this problem well, the corresponding integrated decision-making algorithms in the VERSE and ViFi processes do not make good use of the comparison results, resulting in poor sensitivity of the process

[0005] 2. The choice of comparison software

However, when dealing with such integration events, if not handled correctly, the synthetic sequence will be shorter, the coordinate range will be smaller, and the number of sequences will be reduced, which may even affect the subsequent conclusions

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