Method for distinguishing gene mutation type from individual tumor sample based on second-generation sequencing

A next-generation sequencing and sample technology, applied in the fields of genomics, sequence analysis, biochemical equipment and methods, etc., can solve the problem of not taking into account the positive and negative strand-biased germline mutation frequency characteristics of sequenced DNA fragments, and determine as somatic cells. Mutation, low specificity of differentiation and judgment, etc., to achieve the effect of saving detection costs, high specificity, and high detection efficiency

Active Publication Date: 2020-02-28
上海仁东医学检验所有限公司 +1
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However, the disadvantage of the above method is that the criteria for judging germline mutations and somatic mutations mainly rely on existing databases, and do not take into account the positive and negative strand preference of sequenced DNA fragments generated during the experimental detection process and the mutation frequency of germline mutations themselves. Some germline mutations that are not recorded in the database are not filtered and are judged as somatic mutations. At the same time, some somatic mutations are filtered out because the positions and mutated amino acids are consistent with dbSNP, and are judged as It is a germline mutation, which leads to a low specificity of discrimination, only 67% effect

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  • Method for distinguishing gene mutation type from individual tumor sample based on second-generation sequencing
  • Method for distinguishing gene mutation type from individual tumor sample based on second-generation sequencing
  • Method for distinguishing gene mutation type from individual tumor sample based on second-generation sequencing

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[0023] The present invention will be described in detail below in combination with specific embodiments and accompanying drawings.

[0024] See attached figure 1 , a method for distinguishing gene mutation types based on next-generation sequencing of individual tumor samples, specifically comprising the following steps:

[0025] S1. Select 189 target regions, extract DNA from 189 target regions in tumor tissue samples and normal tissue samples, and use the method of probe capture to build and sequence the DNA extracted from tumor tissue samples and normal tissue samples , to obtain the raw data of 189 target region sequencing;

[0026] S2. Use the BWA MEM algorithm to perform sequence comparison on the DNA sequencing data from tumor tissue samples and normal tissue samples respectively obtained through step S1, and simultaneously generate a comparison file Tumor.dup.bam belonging to tumor tissue samples and a comparison file belonging to normal tissues Sample comparison file...

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Abstract

The invention relates to a method for distinguishing gene mutation types an individual tumor sample based on second-generation sequencing. A tumor tissue sample and a normal tissue sample are used forlibrary construction and NGS sequencing respectively, strand bias and different types of base frequencies of mutation sites stored in an intermediate file BAM for biological information analysis of the tumor tissue sample are analyzed, the quality of base comparison and the frequency of noise are used as the training characteristics of machine learning, meanwhile, type information of corresponding mutation sites of the normal tissue sample is paired to serve as a prediction mutation type, a classification prediction model is constructed to distinguish somatic mutation from germline mutation,the model is used to distinguish somatic mutation from germline mutation, the detection efficiency is high, the specificity is high, and after the model is established, the individual tumor sample canbe used for NGS sequencing and mutation detection, the detection cost of a normal or cancer sample can be well saved, and meanwhile, the problem that normal tissues of tumor patients with specific types are difficult to obtain can be solved.

Description

technical field [0001] The invention belongs to the technical field of gene detection, and in particular relates to a method for distinguishing gene mutation types from individual tumor samples based on next-generation sequencing. Background technique [0002] High-throughput sequencing (NGS) is a large-scale parallel sequencing technology. By using high-throughput sequencing, the sequence covering all genes in the sample can be measured. Combined with related variation detection software, geneticists and oncologists can make a single The gene mutation information of multiple target regions on the genome can be obtained efficiently. Different types of gene mutations may occur in each cell of an individual. Gene mutations can be divided into hereditary mutations and somatic mutations according to their sources. Inherited mutations are inherited from parents. Because mutations exist in the germ cells of both parents , so genetic mutations are also called germline mutations or...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): C12Q1/6886G16B30/10G16B20/50
CPCC12Q1/6886C12Q2600/156G16B20/50G16B30/10
Inventor 赵国栋乔宗赟陈洁
Owner 上海仁东医学检验所有限公司
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