Identification of polymorphisms explaining a linkage signal: application to the GAW14 simulated data.
We applied three approaches for the identification of polymorphisms explaining the linkage evidence to the Genetic Analysis Workshop 14 simulated data: 1) the genotype-IBD sharing test (GIST); 2) an approach suggested by Horikawa and colleagues; and 3) the homozygote sharing test (HST). These tests were compared with a family-based association test. Two linked regions with highest nonparametric linkage scores were selected to apply these methods. In the first region, Horikawa's method identified the most SNPs within the region containing the disease susceptibility locus, while HST performed best in the second region. However, Horikawa's method also had the most type I errors. These methods show potential as additional tools to complement family-based association tests for the identification of disease susceptibility variants.
Chen
Ming-Huei
MH
Department of Mathematics and Statistics, Boston University, Boston, MA, USA. mhchen@bu.edu
Van Eerdewegh
Paul
P
Dupuis
Josée
J
D002878:Chromosomes, Human, Pair 1 / Q000235:genetics; D002899:Chromosomes, Human, Pair 9 / Q000235:genetics; D003198:Computer Simulation; D003226:Congresses as Topic; D030541:Databases, Genetic; D008040:Genetic Linkage; D005828:Genetics, Population; D055106:Genome-Wide Association Study; D006801:Humans; D015810:Linkage Disequilibrium / Q000235:genetics; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*