title: A coalescent simulation of marker selection strategy for candidate gene association studies.
abstract: Recent efforts have focused on the challenges of finding alleles that contribute to health-related phenotypes in genome-wide association studies. However, in candidate gene studies, where the genomic region of interest is small and recombination is limited, factors that affect the ability to detect disease-susceptibility alleles remain poorly understood. In particular, it is unclear how varying the number of markers on a haplotype, the type of marker (e.g., single nucleotide polymorphism (SNP), short tandem repeat (STR)), including the causative site (cs) as a genetic marker, or population demographics influences the power to detect a candidate gene. We evaluated the power of association tests using coalescent-modeled computer simulations. Results show that an effective number of markers on a haplotype is dependent on whether the cs is included as a marker. When the analyses include the cs, highest power is achieved with a single-marker association test. However, when the cs is excluded from analyses, the addition of more nonfunctional SNPs on the haplotype increases power to a certain point under most scenarios. We find a rapidly expanding population always has lower power compared to a population of constant size; although utilizing markers with a frequency of at least 5% improves the chance of detecting an association. Comparing the mutational properties of a nonfunctional SNP versus an STR, multi-allelic STRs provide more or comparable power than a bi-allelic SNP unless SNP frequencies are constrained to 10% or more. Similarly, including an STR with SNPs on a haplotype improves power unless SNP frequencies are 5% or more.
authors.affiliation: Department of Human Genetics, University of Michigan, Ann Arbor, Michigan 48109-0618, USA.
authors.forename: Suzanne M
authors.initials: SM
authors.lastname: Cole
authors.forename: Jeffrey C
authors.initials: JC
authors.lastname: Long
mesh_terms: D003198:Computer Simulation; D008040:Genetic Linkage; D005819:Genetic Markers; D020022:Genetic Predisposition to Disease; D006239:Haplotypes; D006801:Humans; D015810:Linkage Disequilibrium; D018895:Microsatellite Repeats; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide
chemical_list: D005819:Genetic Markers