A method for identifying intra-individual SNPs in Sanger sequencing of diploid PCR products

Abstract

The invention discloses a method for identifying SNPs in individuals in Sanger sequencing of diploid PCR products. First, the adenine A, guanine G, cytosine C and thymine T contained in the chromatogram are separately isolated. Fluorescence data of different bases; use wavelet multi-scale analysis method to filter and denoise the separated fluorescence data respectively; then analyze the waveform characteristics of the fluorescence data of four bases, detect the first peak and the second peak of the waveform, select The three waveform features of peak distance, height ratio and fluctuation ratio are used as the elements of SNP site discrimination; the BP neural network with a structure of 3‑10‑1 is selected as the classifier for SNP site detection, and the Levenberg Marquardt algorithm is used to Train the BP neural network; use piecewise linear transformation to map the output to the SNP evaluation score of 0-100, define the category of the SNP site as 1-5 according to the evaluation score, and judge the SNP confidence of the site accordingly Spend. The invention can effectively detect the SNP site in the individual of the sequencing file.

Description

technical field [0001] The invention belongs to the field of computer automatic recognition, relates to bioinformatics, pattern recognition, statistics, signal processing and computer software technology, and in particular relates to a method for targeting diploid polymerase chains when there is no reference sequence and only a few samples. A method for identifying single nucleotide polymorphisms (Single nucleotide polymorphisms, SNPs) within individuals in Sanger sequencing of Polymerase chain reaction (PCR) products. Background technique [0002] SNP refers to the variation (or polymorphism) caused by the substitution of a single nucleotide at the level of genetic material DNA. SNP has the characteristics of universality, representativeness, heredity, stability, etc., and reflects rich genetic information. The most common heritable variation, SNPs have also become widely used genetic markers. SNPs may lead to differences in individual phenotypes. For example, SNPs may be ...

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Problems solved by technology

However, none of these software can analyze a single sequencing file. For example, novoSNP and Mutation Surveyor require a reference sequence, which is not feasible when the reference gene sequence is sequenced and the measured sequence contains introns (not in the gene sequence); PolyPhred 5.0 The comparison of more than 8 sequencing files is required to accurately interpret the SNP, which is not suitable for sequencing of a single or a small number of samples

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