Haplotype pattern mining & classification for detecting disease associated site

被引:2
作者
Kido, T [1 ]
Baba, M [1 ]
Matsumine, H [1 ]
Higashi, Y [1 ]
Higuchi, H [1 ]
Muramatsu, M [1 ]
机构
[1] HuBit Genomix Inc, Tokyo, Japan
来源
PROCEEDINGS OF THE 2003 IEEE BIOINFORMATICS CONFERENCE | 2003年
关键词
D O I
10.1109/CSB.2003.1227369
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Finding the causative genes for common diseases using SNP (Single Nucleotide Polymorphism) markers is now becoming a real challenge. Although traditional statistical SNP association tests exist, these tests could not explain the effects of SNP combinations or probable recombination histories from ancestral chromosomes. Haplotype analysis of disease associated site provides more powerful markers than individual SNP analysis, and can help identify probable causative mutations. In this paper, we introduce a new method for effective haplotype pattern mining to detect disease associated mutations. Using this procedure, we can discover some of the new disease associated SNPs, which can not be detected by traditional methods. We will introduce a powerful tool for implementing this procedure with some worked examples.
引用
收藏
页码:452 / 453
页数:2
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