A method for detecting copy number variation and deletion types based on a single tumor sample

Abstract

The invention belongs to the technical field of copy number variation detection, and discloses a method for detecting copy number variation and deletion types based on a single tumor sample, and a computer to establish a dynamic balance mechanism for copy number expansion and copy number deletion range, and to continuously correct the number of reads during the iterative detection process The benchmark, correct the parameters of the statistical test distribution, objectively detect significant copy number variation and weakly significant copy number variation; build a Bayesian inference model, and correctly detect the copy number variation status and copy number deletion type. The invention correctly detects the state of copy number variation and the type of copy number deletion, and provides the information of heterozygote deletion and homologous deletion. Considering the comparison quality and errors, the invention rationally corrects the GC content of the whole genome; establishes a dynamic balance mechanism of copy number expansion and copy number deletion range to accurately locate the copy number benchmark and accurately detect the variation state of the copy number.

Description

technical field [0001] The invention belongs to the technical field of copy number variation detection, and in particular relates to a single tumor sample-based copy number variation and deletion type detection method and a computer. Background technique [0002] At present, experts at home and abroad have proposed a variety of copy number variation detection methods, which can be roughly divided into three types: copy number variation detection based on multiple tumor samples, the first type focuses on the detection of consistent copies in multiple samples The number variation pattern is used to discover the common variation pattern for the same type of cancer and provide a scientific basis for the discovery and research of disease-causing genes; the second and third types of detection methods focus on the copy number variation of a patient's genome Detection to observe whether the disease-causing gene or potential disease-causing gene is mutated, and provide a scientific b...

AI Technical Summary

Problems solved by technology

[0003] In summary, the problems existing in the existing technology are: it is difficult to locate the benchmark for the number of genome reads; the existing method based on a single tumor sample does not consider the purity of the tumor tissue and does not consider the copy number variation detection process. The detection of multiple deletion types reduces the accuracy of copy number variation and cannot provide information on heterozygous deletions and homologous deletions

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