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Chunk #1 — Introduction

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GPA: a statistical approach to prioritizing GWAS results by integrating pleiotropy and annotation.
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Identifying the source of this missing heritability has drawn much attention from researchers, and progress has been made towards explaining the apparent discrepancy. The role of a much greater-than-expected set of common variants (minor allele frequency (MAF)0.01) has been shown to be critical in explaining the phenotypic variance [8]. Instead of only using genome-wide significant SNPs, Yang et al. [9] reported that, by using all genotyped common SNPs, 45% of the variance for human height can be explained. This result suggests that a large proportion of the heritability is not actually missing: given the limited sample size, many individual effects of genetic markers are too weak to pass the genome-wide significance, and thus those variants remain undiscovered. So far, people have found similar genetic architectures for many other complex traits [10], such as metabolic syndrome traits [11] and psychiatric disorders [12]–[14]. That is, the phenotype is affected by many genetic variants with small or modest effects effects that cannot be confirmed individually via statistical significance, which is usually referred to as “polygenicity”. The polygenicity of complex traits is further supported