title: Choosing SNPs using feature selection.
abstract: A major challenge for genomewide disease association studies is the high cost of genotyping large number of single nucleotide polymorphisms (SNP). The correlations between SNPs, however, make it possible to select a parsimonious set of informative SNPs, known as "tagging" SNPs, able to capture most variation in a population. Considerable research interest has recently focused on the development of methods for finding such SNPs. In this paper, we present an efficient method for finding tagging SNPs. The method does not involve computation-intensive search for SNP subsets but discards redundant SNPs using a feature selection algorithm. In contrast to most existing methods, the method presented here does not limit itself to using only correlations between SNPs in local groups. By using correlations that occur across different chromosomal regions, the method can reduce the number of globally redundant SNPs. Experimental results show that the number of tagging SNPs selected by our method is smaller than by using block-based methods.
authors.affiliation: Department of Information Technology, Post & Telecom. Institute of Technology, Hanoi, Vietnam. phuongtm@fpt.com.vn
authors.forename: Tu Minh
authors.initials: TM
authors.lastname: Phuong
authors.forename: Zhen
authors.initials: Z
authors.lastname: Lin
authors.forename: Russ B
authors.initials: RB
authors.lastname: Altman
mesh_terms: D001185:Artificial Intelligence; D001483:Base Sequence; D002869:Chromosome Aberrations; D002874:Chromosome Mapping / Q000379:methods*; D002891:Chromosomes, Human, Pair 21 / Q000235:genetics*; D004252:DNA Mutational Analysis / Q000379:methods*; D006801:Humans; D015810:Linkage Disequilibrium / Q000235:genetics*; D008969:Molecular Sequence Data; D010363:Pattern Recognition, Automated / Q000379:methods; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*; D016415:Sequence Alignment / Q000379:methods; D017422:Sequence Analysis, DNA / Q000379:methods*