摘要
探讨将基于惩罚函数的变量选择方法应用到遗传位点分析。以2016年9月16日的全国研究生数学建模竞赛B题的数据为例,首先对每个位点的碱基对(A、T、C、G)编码方式数值化处理,最后用数值化后的数据进行建模,并将单变量选择LogisticSCAD、组变量选择LogisticGroupSCAD模型和双层变量选择LogisticcMCP模型定位到与遗传性疾病显著相关的遗传位点,分别与出题者提供的标准答案进行对比,结果显示双层变量选择LogisticcMCP模型能够准确的定位到与遗传性疾病显著相关的遗传位点。因此将其运用到具有遗传性疾病和性状的遗传位点分析是值得研究的。
Discuss the application of the penalty function based variable selection method in genetic locus analysis.Taking the data of question B of the National Graduate Mathematical Modeling Competition on September 16,2016 as an example,the base pair(A,T,C,G)coding method of each site is numerically processed,and modeling with final numerically processed data,the univariate selection Logistic SCAD,the group variable selection Logistic Group SCAD model,and the two-layer variable selection Logistic cMCP model are located to genetic sites that are significantly related to genetic diseases,and compare with the standard answers provided by the questioner.The results show that the two-layer variable selection Logistic cMCP model can accurately locate genetic sites that are significantly related to genetic diseases.Therefore,applying it to the analysis of genetic locus with genetic diseases and traits is worth studying.
作者
庄虹莉
Zhuang Hongli(JINSHAN College of Fujian Agriculture and Forestry University,Fuzhou,Fujian 350002,China)
出处
《计算机时代》
2021年第11期9-12,共4页
Computer Era
基金
福建省中青年教师教育科研项目(科技)“基于Cox风险比例回归模型的变量选择”(JAT201004)。
