CAJ | 학술논문

探讨基于基因水平的主成分logistic回归模型分析方法及其在全基因组关联研究中的应用.以全基因组关联研究基因型模拟数据为例,介绍基于主成分的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.模拟结果表明致病位点所在基因假设检验的P值在所有基因检验结果中为最小.研究结果提示在全基因组关联研究中,采用基于基因水平的主成分logistic回归模型一方面能够降低检验的自由度,另一方面能够处理单核苷酸多态性之间相关性问题,在检测致病基因与疾病关联时具有一定的效能.
탐토기우기인수평적주성분logistic회귀모형분석방법급기재전기인조관련연구중적응용.이전기인조관련연구기인형모의수거위례,개소기우주성분적logistic회귀모형재기인수평검측유전변이여복잡성질병지간관련적분석책략.모의결과표명치병위점소재기인가설검험적P치재소유기인검험결과중위최소.연구결과제시재전기인조관련연구중,채용기우기인수평적주성분logistic회귀모형일방면능구강저검험적자유도,령일방면능구처리단핵감산다태성지간상관성문제,재검측치병기인여질병관련시구유일정적효능.
To explore the gene-based principal component logistic regression model and its application in genome-wide association study.Using the simulated genome-wide single nucleotide polymorphism (SNPs) genotypes data,we proposed a practical statistical analysis strategy-'the principal component logistic regression model',based on the gene levels to assess the association between genetic variations and complex diseases.The simulation results showed that the P value of genes in related diseases was the smallest among the results from all the genes.The results of simulation indicated that not only it could reduce the degree of freedom through hypothesis testing but could also better understand the correlations between SNPs.The gene-based principal component logistic regression model seemed to have certain statistical power for testing the association between genetic genes and diseases in the genome-wide association studies.