Big-data-based fusion gene data detection method, computer program, terminal

Abstract

The invention belongs to the field of gene technology and discloses a fusion gene data detection method based on big data, a computer program and a terminal. The known fusion gene breakpoint, N sequences in front of the breakpoint and M sequences behind the breakpoint are combined to form a seed, and the seeds are assembled to form a fusion gene database. The RNA of the gene to be detected is extracted by a kit; cDNA of the gene to be detected is obtained by reverse transcription of the extracted RNA by using a reverse transcription kit. The fusion gene is amplified by polymerase chain reaction using cDNA as template. Gene information to be detect is obtained by detect a gene fragment to be detected by a gene detection technology. The invention can effectively improve the gene sequence alignment efficiency and the user experience by comparing the sequences to be aligned according to the judgment result.

Description

technical field [0001] The invention belongs to the field of gene technology, and in particular relates to a method for detecting fusion gene data based on big data, a computer program, and a terminal. Background technique [0002] A gene (genetic element) is the entire nucleotide sequence required to produce a polypeptide chain or functional RNA. Genes support the basic structure and performance of life. It stores all the information about race, blood type, conception, growth, apoptosis and other processes of life. The interdependence of environment and heredity plays an important role in the reproduction of life, cell division and protein synthesis and other important physiological processes. All life phenomena such as birth, growth, decline, disease, old age, and death of organisms are related to genes. It is also an internal factor that determines the health of life. Therefore, genes have dual attributes: materiality (way of existence) and informationality (fundament...

AI Technical Summary

Problems solved by technology

[0007] In the existing technology, fusion gene detection is cumbersome. Facing a huge comparative gene database, the detection speed is extremely slow and time-consuming when comparing gene sequences, which affects work efficiency and wastes manpower;

[0008] In the prior art, because the comparison gene database is too large, there are often misjudgments, which affect the work progress and waste human, material and financial resources

[0009] In the existing technology, the authenticity of the fusion genetic data detection data is low, and the robustness of the detection method is poor

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