A method, device and storage medium for detecting copy number variation

Abstract

The present application discloses a method, device and storage medium for detecting copy number variation. The detection method of the present application includes the steps of obtaining the DNA sequencing data of the sample to be tested and the comparison data of each position on the human reference genome; the step of counting the depth of the DNA of the sample to be tested in the fixed window area; extracting the abnormal data sequence, As a step of supporting the first dimension result of copy number variation; a step of extracting the window in which the depth of the DNA window of the sample to be tested differs from the distribution statistical model; a step of judging whether the difference window is significant and whether it can be supported by the first dimension result; and Test result output step. The detection method of this application can accurately distinguish true and false copy number variation through the distribution statistical model of DNA in healthy people, and combine with another dimension of results to ensure the accuracy of copy number variation detection results from different angles. The detection method of the present application does not require a kinship control sample, and can detect copy number variation of a single sample.

Description

technical field [0001] The present application relates to the field of copy number variation detection, and in particular, to a method, device and storage medium for detecting copy number variation. Background technique [0002] Copy number variation (CNV) is caused by the rearrangement of the genome, which generally refers to the increase or decrease of the copy number of large genomic fragments with a length of more than 1 kb, mainly manifested as deletions and duplications at the submicroscopic level. CNV is an important part of genome structural variation (SV). The mutation rate of CNV loci is much higher than that of SNP (Single nucleotide polymorphism), which is one of the important pathogenic factors of human diseases. [0003] With the rapid development of next-generation sequencing technology, it is gradually applied to the scientific research and clinical detection of cancer and genetic diseases, giving us a new understanding of the occurrence and development, cli...

AI Technical Summary

Problems solved by technology

This method has the following inevitable inherent limitations: 1. Breakpoint information cannot be found clearly; 2. The throughput is low, and only a small number of areas can be detected at a time, so high-throughput experiments cannot be carried out; 3. Only for Designing probes for target regions for detection cannot achieve the purpose of genome-wide screening

However, the copy number variation detection method based on next-generation sequencing also has inevitable limitations: 1. Due to the existence of homologous sequences in the genome, alignment errors are caused; 2. The PCR process of the experiment will have different DNA templates. 3. Chromosomal copy number variation detection based on next-generation sequencing (abbreviated as CNV-seq) relies on the parental / maternal normal control samples of the samples to be detected , it is difficult to detect in the case of a single sample

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