Hybrid methods for correcting sequencing errors in third-generation sequencing data under heterozygous variation

Abstract

The invention discloses a hybrid method for correcting sequencing errors in third-generation sequencing data under heterozygous variation. The input data are second-generation sequencing data and third-generation sequencing data, and the input The data is processed, and the heterozygosity of the gene locus is judged based on the Bayesian classifier principle, and the reads in the third-generation sequencing data are corrected based on the results of the heterozygosity judgment, which solves the problem of existing correction algorithms in processing heterozygosity. Problems of low accuracy and invalidity when combining mutations. The present invention considers heterozygous variation when correcting sequencing errors, designs a series of probability models to judge and classify heterozygosity, and then adopts different correction strategies for different heterozygosity classifications, solving problems encountered by existing correction methods. Problems with correction errors occur when heterozygous variants are present.

Description

technical field [0001] The invention belongs to the technical field of third-generation sequencing, and in particular relates to a hybrid method for correcting sequencing errors in third-generation sequencing data under heterozygous variation. Background technique [0002] Genome sequencing technology, especially single-molecule long-read sequencing technology, also known as third-generation sequencing (English name: Third Generation Sequence, English abbreviation: TGS), has revolutionized genomics research. TGS technology not only continues the high-throughput advantages of Next Generation Sequencing (English name: Next Generation Sequence, English abbreviation: NGS) technology, but also generates longer read lengths, up to 10kbp. Therefore, TGS technology has brought great impetus to many fields, such as the detection of structural variations, the identification of methylation, and the diagnosis of diseases. Although TGS is in the leading position in terms of read length ...

AI Technical Summary

Problems solved by technology

[0006] The technical problem to be solved by the present invention is to provide a hybrid method for correcting sequencing errors in the third-generation sequencing data under heterozygous variation to solve the problems caused by the single voting mechanism of the existing correction algorithm and other algorithm structures. Miscorrection of heterozygous variants caused by the problem, breaking through the negative impact of the read length and coverage of sequencing data on the accuracy of the correction algorithm, especially the correction accuracy of heterozygous variants, and realizing the correction of heterozygous variants in low-coverage sequencing data The increased accuracy of

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