Evaluation of an algorithm of tagging SNPs selection by linkage disequilibrium.
BACKGROUND
Single nucleotide polymorphisms (SNPs) are the most abundant kind of genetic polymorphism in the human genome. They are important in both genetic research and genetic testing in a clinical setting, such as in the area of pharmacogenetics. In order to improve efficiency, tagging SNPs (tagSNPs) are selected in genes of interest to represent other co-related SNPs in linkage disequilibrium (LD) with the tagSNPs. Various algorithms have been proposed to identify a subset of single nucleotide polymorphisms as tagSNPs. Most algorithms of tagSNPs selection are haplotype-based, in which the spatial relationship between SNPs is considered. Currently, a more efficient cluster-based algorithm is proposed which clusters SNPs solely by a LD parameter, such as r(2). Here, we evaluated the sample distribution of r(2) and its effect on the cluster-based tagSNPs selection.


METHODS
The genotype data of 198 individual within a 500-kb region on 5q31 was used to evaluate the sample distribution of r(2) and its effect on the cluster-based tagSNPs selection.


RESULTS
It was found that the degree of variation of LD depends on the LD structure of genes.


CONCLUSIONS
As a cluster-based tagSNPs selection algorithm does not take into account the spatial position of SNPs, a more stringent r(2) threshold is required to achieve more reliable tagSNPs selection.
Tang
Nelson L S
NL
Department of Chemical Pathology, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong. nelsontang@cuhk.edu.hk
Pharoah
Paul D P
PD
Ma
Suk Ling
SL
Easton
Douglas F
DF
D000465:Algorithms; D016000:Cluster Analysis; D030541:Databases, Genetic; D006801:Humans; D015810:Linkage Disequilibrium / Q000235:genetics*; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*