title: Genome-wide selection of tag SNPs using multiple-marker correlation.
abstract: BACKGROUND
  The tag SNP approach is a valuable tool in whole genome association studies, and a variety of algorithms have been proposed to identify the optimal tag SNP set. Currently, most tag SNP selection is based on two-marker (pairwise) linkage disequilibrium (LD). Recent literature has shown that multiple-marker LD also contains useful information that can further increase the genetic coverage of the tag SNP set. Thus, tag SNP selection methods that incorporate multiple-marker LD are expected to have advantages in terms of genetic coverage and statistical power.
  
  
  RESULTS
  We propose a novel algorithm to select tag SNPs in an iterative procedure. In each iteration loop, the SNP that captures the most neighboring SNPs (through pair-wise and multiple-marker LD) is selected as a tag SNP. We optimize the algorithm and computer program to make our approach feasible on today's typical workstations. Benchmarked using HapMap release 21, our algorithm outperforms standard pair-wise LD approach in several aspects. (i) It improves genetic coverage (e.g. by 7.2% for 200 K tag SNPs in HapMap CEU) compared to its conventional pair-wise counterpart, when conditioning on a fixed tag SNP number. (ii) It saves genotyping costs substantially when conditioning on fixed genetic coverage (e.g. 34.1% saving in HapMap CEU at 90% coverage). (iii) Tag SNPs identified using multiple-marker LD have good portability across closely related ethnic groups and (iv) show higher statistical power in association tests than those selected using conventional methods.
  
  
  BACKGROUND
  A computer software suite, multiTag, has been developed based on this novel algorithm. The program is freely available by written request to the author at ke_hao@merck.com
authors.affiliation: Algorithm and Data Analysis, Affymetrix, Inc., 3420 Central Expressway, Santa Clara, California, USA. ke_hao@163.com
authors.forename: K
authors.initials: K
authors.lastname: Hao
mesh_terms: D000465:Algorithms; D001483:Base Sequence; D002874:Chromosome Mapping / Q000379:methods*; D020224:Expressed Sequence Tags; D005819:Genetic Markers / Q000235:genetics*; D015810:Linkage Disequilibrium / Q000235:genetics*; D008969:Molecular Sequence Data; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*; D017422:Sequence Analysis, DNA / Q000379:methods*; D013223:Statistics as Topic
chemical_list: D005819:Genetic Markers