SNP pathogenic factors and disease association model establishment method

Abstract

The invention belongs to the technical field of data processing, and discloses a method for establishing a correlation model between SNP pathogenic factors and diseases, collecting sample data sets corresponding to current SNP pathogenic factors; absolutely dividing the sample data sets according to initial values; based on machine learning Methods SNP pathogenic factors and disease association modeling; modeling results accuracy evaluation; determine the SNP pathogenic factors and disease association model. The present invention reduces the degree of interaction among various SNP pathogenic factors through the method of absolute division, so that the established correlation model between each SNP pathogenic factor and the disease is more accurate. The present invention is simple to operate, only needs to input the original SNP data and all SNP pathogenic factors, and can obtain a more accurate correlation model between each SNP pathogenic factor and the disease.

Description

technical field [0001] The invention belongs to the technical field of data processing, and in particular relates to a method for establishing a correlation model between SNP pathogenic factors and diseases. Background technique [0002] Currently, the closest existing technology: [0003] SNP: Single Nucleotide Polymorphism (SingleNucleotidePolymorphisms), refers to the polymorphism caused by a single nucleotide (A, T, C, G) variation in the genome. More and more research evidence shows that SNPs are closely related to diseases, and this relationship is the basis for understanding the causes of diseases, medical prevention and diagnosis. An in-depth understanding of the association between SNPs and diseases can provide the possibility to understand the pathogenesis of diseases, and can also take a step forward on the road of treating and defeating complex diseases. [0004] Studies on the association between SNPs and diseases can be divided into two categories: SNP-level ...

AI Technical Summary

Problems solved by technology

[0016] 1. The accuracy of the model established by the existing method is low;

[0017] 2. SNP data has small sample characteristics, and the small sample size makes modeling difficult and affects accuracy;

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