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A coalescent simulation of marker selection strategy for candidate gene association studies

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. © 2007 Wiley‐Liss, Inc. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png American Journal of Medical Genetics part B Wiley

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