Tag SNP selection using clonal selection and majority voting algorithms

被引:3
|
作者
Ilhan, Ilhan [1 ]
Tezel, Gulay [2 ]
机构
[1] Necmettin Erbakan Univ, Fac Engn & Architecture, Dept Mechatron Engn, Konya, Turkey
[2] Selcuk Univ, Fac Engn & Architecture, Dept Comp Engn, Konya, Turkey
关键词
ABC; artificial bee colony algorithm; CLONALG; clonal selection algorithm; majority voting; SVM; support vector machine; tag SNPs; SINGLE-NUCLEOTIDE POLYMORPHISMS; VECTOR MACHINE METHOD; GENETIC ALGORITHM; EFFICIENT ALGORITHM; HAPLOTYPE STRUCTURE; ASSOCIATION; OPTIMIZATION; SET;
D O I
10.1504/IJDMB.2016.10003176
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Researchers should select a suitable subgroup that includes all SNPs and represents the rest of the SNPs with little error for very large-scale association studies. The SNPs included in the subgroup are tag SNPs or haplotype tag SNPs (htSNPs). When selecting the tag SNPs, it is critical to accurately predict and identify the smallest number of tag SNPs with minimum error. This study used the Clonal Selection Algorithm (CLONALG) to decide on the tag SNPs to be included in the subgroup. In addition, the study proposed a new method called CSMV, which used the Majority Voting (MV) method to predict the rest of the SNPs. This method was compared with the BPSO method and the CLONTagger with parameter optimisation method using datasets of different sizes. According to the experimental results of the study, the CSMV method could determine the tag SNPs with significantly higher accuracy than the other two methods.
引用
收藏
页码:290 / 311
页数:22
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