Mononucleotide variation detecting method based on blood circulation tumor DNA, device and storage medium

Abstract

The invention provides a mononucleotide variation detecting method based on blood circulation tumor DNA, a device and a storage medium. The method comprises the steps of acquiring mutation data of each site of the blood circulation tumor DNA of a testing sample, wherein the mutation data comprises a site mutation frequency; acquiring a confidence range of each site background mutation frequency ofthe training sample, wherein the confidence range is obtained through performing learning modeling on all three-base mutation frequency and site mutation frequency in each training sample and training the model by means of an in-place updated list; comparing the site mutation frequency of each site of the testing sample with the confidence range of the background mutation frequency of each site in the model, and outputting the mononucleotide variation wherein the site mutation frequency of the testing sample is not in the confidence range. The mononucleotide variation detecting method, the device and the storage medium have advantages of greatly optimizing a calculation resource requirement and a detecting speed, improving sensitivity and accuracy in detecting ctDNA mononucleotide mutation, and satisfying a requirement for ctDNA mononucleotide mutation detecting reliability in clinical tumor detection.

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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