Genome‐wide expression quantitative trait loci (eQTLs) mapping explores the relationship between gene expression and DNA variants, such as single‐nucleotide polymorphism (SNPs), to understand genetic basis of human diseases. Due to the large number of genes and SNPs that need to be assessed, current methods for eQTL mapping often suffer from low detection power, especially for identifying trans‐eQTLs. In this paper, we propose the idea of performing SNP ranking based on the higher criticism statistic, a summary statistic developed in large‐scale signal detection. We illustrate how the HC‐based SNP ranking can effectively prioritize eQTL signals over noise, greatly reduce the burden of joint modeling, and improve the power for eQTL mapping. Numerical results in simulation studies demonstrate the superior performance of our method compared to existing methods. The proposed method is also evaluated in HapMap eQTL data analysis and the results are compared to a database of known eQTLs.

中文翻译：

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有效的 SNP 排序提高了 eQTL 映射的性能。

全基因组表达数量性状位点 (eQTL) 作图探索基因表达与 DNA 变异之间的关系，例如单核苷酸多态性 (SNP)，以了解人类疾病的遗传基础。由于需要评估的基因和 SNP 数量众多，当前的 eQTL 定位方法往往检测能力低，尤其是在识别反式-eQTL。在本文中，我们提出了基于更高批评统计量执行 SNP 排名的想法，该统计量是在大规模信号检测中开发的汇总统计量。我们说明了基于 HC 的 SNP 排名如何有效地将 eQTL 信号优先于噪声，大大减少联合建模的负担，并提高 eQTL 映射的能力。模拟研究中的数值结果表明，与现有方法相比，我们的方法具有优越的性能。所提出的方法还在 HapMap eQTL 数据分析中进行了评估，并将结果与​​已知 eQTL 的数据库进行了比较。