Shrunken Dissimilarity Measure for Genome-wide SNP Data Classification

摘要：

Recent development of high-resolution single-nucleotide polymorphism (SNP) arrays allows detailed assessment of genome-wide human genome variations. However, SNP data typically has a large number of SNPs (e,g., 400 thousand SNPs in genome-wide Parkinson disease SNP data) and a few hundred of samples. Conventional classification methods may not be effective when applied to such genome-wide SNP data. In this paper, we propose to develop and use shrunken dissimilarity measure to analyze and select relevant SNPs for classification problems. Examples for HapMap data and Parkinson data are given to demonstrate the effectiveness of the proposed method and illustrate it has the potential to become a useful analysis tool for SNP data sets. In particular, we find some SNPs in chromosome 2 that they contain in some genes which is relevant to Parkinson disease.

关键词： Shrinkage Dissimilarity measure Categorical centroids Single nucleotide polymorphism Genome-wide Classification

作者: Haiyong Liao Yang Liu Michael K.Ng

作者单位: Department of Mathematics,Hong Kong Baptist University,Kowloon Tong,Hong Kong

会议类型: 国际会议

会议名称: The 3rd International Symposium on Optimization and System Biology(第三届最优化与系统生物学国际会议 OSB09)

会议地点: 张家界

会议语种:英文

页码: 73-80

在线出版日期: 2009-09-20（万方平台首次上网日期，不代表论文的发表时间）