Abstract
An efficient, cost-effective and open-source approach is described for high-throughput genotyping of large fixed panels of diploid individuals.
Highlights
Understanding the genetic architecture of complex polygenic traits is a fundamental goal of modern biological and medical research, and the currently favored experimental paradigm is association mapping
Association studies genotype a dense set of single nucleotide polymorphisms (SNPs) in a large panel of individuals and test each SNP, or set of local haplotypes constructed from the SNP data, for a phenotype/disease association
Even with some a priori knowledge of a candidate gene region contributing to a disease phenotype, a large number of SNPs need to be genotyped in an association mapping study to ensure one of the genotyped SNPs is causative or is in strong linkage disequilibrium with the causative site
Summary
Understanding the genetic architecture of complex polygenic traits is a fundamental goal of modern biological and medical research, and the currently favored experimental paradigm is association mapping (reviewed by Carlson et al [1]). A significant association at a query SNP suggests it is the causal polymorphism, or is in strong linkage disequilibrium with the causal site [24]. Even with some a priori knowledge of a candidate gene region contributing to a disease phenotype, a large number of SNPs need to be genotyped in an association mapping study to ensure one of the genotyped SNPs is causative or is in strong linkage disequilibrium with the causative site. It is important that SNPs are genotyped in a very large panel of individuals to provide sufficient power to detect variants that may have only subtle phenotypic effects. Studies suggest panel sizes of much larger than 1,000 individuals are required to achieve modest power to detect associations if they are present [4,6,7]
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