CAJ | 학술논문

[导读]探讨基于基因水平的核函数logistic回归模型及其在全基因组关联研究中的应用.以全基因组关联研究模拟数据为例,介绍核函数logistic回归模型在基因水平检测遗传变异与复杂性疾病之间关联的分析策略.模拟结果表明,在所有已知基因检验结果中致病位点所在基因假设检验的P值最小.结果提示基于基因水平的核函数logistic回归模型能够充分提取和综合基因中多个遗传突变位点信息,降低统计学检验的自由度,同时还能够控制多种协变量因素和交互作用,在检测致病基因与疾病关联时具有一定的效能.
[도독]탐토기우기인수평적핵함수logistic회귀모형급기재전기인조관련연구중적응용.이전기인조관련연구모의수거위례,개소핵함수logistic회귀모형재기인수평검측유전변이여복잡성질병지간관련적분석책략.모의결과표명,재소유이지기인검험결과중치병위점소재기인가설검험적P치최소.결과제시기우기인수평적핵함수logistic회귀모형능구충분제취화종합기인중다개유전돌변위점신식,강저통계학검험적자유도,동시환능구공제다충협변량인소화교호작용,재검측치병기인여질병관련시구유일정적효능.
[Introduction] To explore the gene-based logistic kemel-machine regression model and its application in genome-wide association study (GWAS).Using the simulated genome-wide singlenucleotide polymorphism (SNPs) genotypes data,we proposed a practical statistical analysis strategynamed ‘ the logistic kernel-machine regression model',based on the gene levels to assess the association between genetic variations and complex diseases.The results from simulation showed that the P value of genes in related diseases was the smallest among all the genes.The results of simulation indicated that not only it could borrow information from different SNPs that were grouped in genes and reducing the degree of freedom through hypothesis testing,but could also incorporate the covariate effects and the complex SNPs interactions.The gene-based logistic kernel-machine regression model seemed to have certain statistical power for testing the association between genetic genes and diseases in GWAS.