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Many genome‐wide association studies (GWAS) have signals with unknown etiology. This paper addresses the question—is such an association signal caused by rare or common variants that lead to increased disease risk? For a genomic region implicated by a GWAS, we use single nucleotide polymorphism (SNP) data in a case‐control setting to predict how many common or rare variants there are, using a Bayesian...
Despite the numerous and successful applications of genome‐wide association studies (GWASs), there has been a lot of difficulty in discovering disease susceptibility loci (DSLs). This is due to the fact that the GWAS approach is an indirect mapping technique, often identifying markers. For the identification of DSLs, which is required for the understanding of the genetic pathways for complex diseases,...
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