With the rise of genome-wide association studies (GWAS), the analysis of typical GWAS data sets with thousands of single-nucleotide polymorphisms (SNPs) has become crucial in biomedicine research. Here, we propose a new method to identify SNPs related to disease in case-control studies. The method, based on genetic distances between individuals, takes into account the possible population substructure, and avoids the issues of multiple testing. The method provides two ordered lists of SNPs; one with SNPs which minor alleles can be considered risk alleles for the disease, and another one with SNPs which minor alleles can be considered as protective. These two lists provide a useful tool to help the researcher to decide where to focus attention in a first stage.

中文翻译：

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全基因组关联研究基于距离的新方法


随着全基因组关联研究（GWAS）的兴起，对具有数千个单核苷酸多态性（SNP）的典型 GWAS 数据集的分析已成为生物医学研究中的关键。在这里，我们提出了一种在病例对照研究中识别与疾病相关的 SNP 的新方法。该方法基于个体之间的遗传距离，考虑了可能的群体子结构，避免了多重测试的问题。该方法提供了两个 SNP 有序列表；一种具有SNP，其次要等位基因可被视为该疾病的风险等位基因，而另一种具有SNP，其次要等位基因可被视为具有保护性。这两个列表提供了一个有用的工具，可以帮助研究人员决定在第一阶段将注意力集中在哪里。