Tumor somatic cell mutation site detection method and device

Abstract

The invention provides a tumor somatic cell mutation site detection method and a tumor somatic cell mutation site detection device. The method comprises the following steps: sequencing a tumor somaticcell sample and a leukocyte sample taken from the same tumor patient, and comparing a sequencing result with a reference genome sequence to generate a corresponding bam file; removing deviation caused by PCR amplification in the bam file to obtain a corrected bam file; comparing the corrected tumor somatic cell sample bam file with the corrected leukocyte sample bam file to generate a vcf file ofall mutation detection information of the tumor somatic cell sample, and annotating the vcf file; and filtering the variation detection information of the tumor somatic cell sample according to a preset filtering condition to obtain a real tumor somatic cell mutation site information result. According to the method, one-step filtering operation is realized, so that the filtering accuracy is ensured, and tumor somatic cell mutation site information can be rapidly obtained; the result is real and reliable; and an important basis is provided for accurate treatment of tumor patients.

Description

technical field [0001] The invention relates to bioinformatics, in particular to a method and a device for detecting tumor somatic cell mutation sites. Background technique [0002] Somatic mutations refer to mutations that occur in somatic cells other than sex cells and are generally not passed on to offspring. Genome instability promotes the accumulation of somatic mutations in cells, some of which further drive cancer development. Detection of somatic mutations in tumor cells, especially tumor driver mutations, is an important means to analyze the occurrence and development of tumors, and can provide an important basis for precise treatment of tumor patients. [0003] At present, commonly used software for finding tumor somatic mutations, such as Varscan, GATK, SomaticSniper and other software, generates a large number of false positive mutations in the vcf file. How to filter out false positive sites from the original vcf file has always been a challenge. Challenges th...

AI Technical Summary

Problems solved by technology

At present, most researchers use the specific information of the site, such as the mutation frequency of the site, the number of reads, the strand bias, the average quality of the base, etc., write programs or even manually filter the sites based on experience, and do not fully consider the detection The situation of the site and surrounding sites, the average error rate of the reads bases, the average distance of the mutated bases on the reads, complex mutations, the frequency of the site population, etc., cannot achieve one-step filtering operation, and it is difficult to guarantee the accuracy of the filtering

Also, the software runs slowly when samples are poorly sequenced