Genome copy number variation detection method and device

Abstract

The invention provides a genome copy number variation detection method. The method comprises the following steps: acquiring a genome sequencing sequence of a to-be-detected sample; aligning the sequencing sequence to a human genome reference sequence, and determining the position of the unique alignment to the genome reference sequence; dividing the genome reference sequence into equal-length windows, and counting the number of sequencing sequences which fall into each window and are uniquely compared to obtain the effective data volume of each window; performing dynamic data correction on theeffective data volume of each window to obtain the corrected effective data volume of each window; standardizing the corrected effective data volume to obtain an effective depth value of each window;filtering noise by using a Fuded Lasso algorithm, and identifying a potential copy number variation region by constraining a differential item; and calculating a copy number value (SCN) in the potential copy number variation region, and comparing the copy number value (SCN) with the reference range of the copy number to obtain an accurate copy number variation detection result. The invention further provides a device and equipment for implementing the method. According to the method, a mathematical model for calculating the copy number SCN is established for the first time, and the referenceinterval of the copy number state of the genome region is determined. In addition, the noise in the sequencing data can be effectively processed, and the copy number variation region can be accuratelyidentified.

Description

technical field [0001] The invention relates to the fields of bioinformatics and genome mutation detection. More specifically, the present invention relates to a method and device for detecting genome copy number variation (Copy Number Variation, CNV). Background technique [0002] Copy number variation is a structural abnormality in the genome, which refers to the difference in the number of copies of a DNA segment in a certain region of the genome compared with the normal population. Common copy number variations include deletions, duplications, and chromosomal aneuploidies. [0003] At present, the most commonly used principle for detecting CNV through NGS data is based on the calculation depth (read-depth), that is, by calculating the relative level of the depth of a certain section and the depth of the corresponding section of the normal reference sample, and the relative level obtained by pre-calculation To judge whether there is CNV in this segment by comparing the ...

AI Technical Summary

Problems solved by technology

[0004] Therefore, current methods for identifying copy number variations still need to be improved

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