Single nucleotide variation detection method, device and storage medium based on circulating tumor DNA

Abstract

A single nucleotide variation detection method, device, and storage medium based on blood circulating tumor DNA, the method comprising: obtaining mutation data of each site of blood circulating tumor DNA in a test sample, the mutation data including site mutation frequency; obtaining training The confidence range of the background mutation frequency of each site of the sample, which is obtained by learning and modeling all three base mutation frequencies and site mutation frequencies in each training sample, and using the list updated in place to model Obtained by training; compare the confidence range of the site mutation frequency of each site in the test sample with the background mutation frequency of each site in the model, and output the single nucleotides whose site mutation frequency of the test sample is not within the confidence range Acid variation was used as the detection result. The present invention improves the sensitivity and accuracy of detecting ctDNA single nucleotide mutations while greatly optimizing computing resource requirements and detection speed, and meets the reliability requirements of tumor clinical detection ctDNA single nucleotide mutations.

Description

technical field [0001] The invention relates to the technical field of tumor detection, in particular to a single nucleotide variation detection method, device and storage medium based on blood circulating tumor DNA. Background technique [0002] Circulating tumor DNA (ctDNA) refers to tumor DNA that is released into a patient's bloodstream when cancer cells die. Analysis of ctDNA helps determine the type of mutation in a tumor while monitoring its growth. Tumor-derived DNA may carry different mutations than normal DNA and thus be distinguished. However, sometimes the content of ctDNA in blood DNA is very small, and the accurate detection of mutant DNA poses challenges to the existing data analysis methods. [0003] In recent years, DNA sequencing technology has developed rapidly. The next-generation sequencing technology represented by Illumina's sequencing-by-synthesis (SBS) technology has become the first choice for cancer genome sequencing methods due to its low price...

AI Technical Summary

Problems solved by technology

TNER and iDES did not effectively distinguish the mutation frequency of background mutations and heterozygous SNPs in the sample when counting the background mutation frequency, resulting in an underestimation of the background mutation frequency and affecting the accuracy of mutation detection

In addition, the variation generated at the SNP locus of the population is usually covered by the higher variation frequency of the SNP in a part of the training samples, so that iDES and TNER cannot be effectively detected, which reduces the sensitivity of variation detection

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