Genetic Locus Analysis Based on Fusion Model
ZHANG Jirong
KOU Lei
Abstract：In order to solve the relationship between human genetic diseases and traits and genomic loci,a fusion model is pro?posed to establish the association analysis between single Nucleotide Polymorphisms(SNPs)and diseases through genome-wide as?sociation analysis. Firstly,the 16-dimensional data is transformed into coding mode to obtain the dimensionality reduction data. Next,the SNP correlation analysis model based on the two-stage ant colony algorithm is established by using the chi-squared statis?tic between locus set and class standard as the evaluation function. Then,the most similar site to the pathogenic site is selected, which as well as other sites constitutes a new set of loci and establishes a binary logistic regression model,and the association be?tween genetic diseases and new locus sets is analyzed. Finally,the random forest algorithm is used to verify the accuracy of the mod?el. The experimental results show that this fusion model,whose recognition rate reaches 85.8%,is significantly enhanced compared with the recognition ability of the traditional method,and it can effectively carry out genetic disease,gene and site multi-level corre?lation analysis.
Keywords：genetic locustwo-stage ant colony algorithmrandom forestlogistic regression analysischi-square test
Publication Date：2019-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 2165-2169,2175 )