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Improved methods for multi-trait fine mapping of pleiotropic risk loci

机译:改进的多个特征型风险基因座的微观测绘方法

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Motivation: Genome-wide association studies (GWAS) have identified thousands of regions in the genome that contain genetic variants that increase risk for complex traits and diseases. However, the variants uncovered in GWAS are typically not biologically causal, but rather, correlated to the true causal variant through linkage disequilibrium (LD). To discern the true causal variant(s), a variety of statistical fine-mapping methods have been proposed to prioritize variants for functional validation.
机译:动机:基因组 - 范围基因组合研究(GWAs)鉴定了含有遗传变异的基因组中的数千个地区,这增加了复杂性状和疾病的风险。 然而,GWA中未发现的变体通常不是生物学上的因果,而是通过连杆不平衡(LD)与真正的因果变体相关。 为了辨别真正的因果变量,已经提出了各种统计细映射方法,以优先考虑功能验证的变体。

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