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A SNP Prioritization Method Using Linkage Disequilibrium Network for Disease Association Study

机译:一种利用疾病协会研究的联系不平衡网络的SNP优先化方法

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The problem of identifying and prioritizing various types of genetic markers including single nucleotide polymorphisms (SNPs), which are involved in human diseases such as cancer, is a one of primary challenge in current disease association studies. In this work, we propose a prioritization method, SNPRank that employs linkage disequilibrium (LD) network to improve the prioritization of candidate SNPs in disease association study. For the construction of LD network structure, we defined mutual links between SNPs based on r~2 > 0.6, and prioritized such SNPs that are linked to other highly ranked SNPs. For experiments, we applied our method to identify SNP markers associated with prostate cancers. The results showed that the proposed method can improve upon existing approaches by newly finding disease-related SNPs which could not be identified by existing approaches.
机译:鉴定和优先考虑各种类型的遗传标记,包括涉及癌症如癌症的单核苷酸多态性(SNP)的各种遗传标记,是目前疾病协会研究中的主要挑战之一。在这项工作中,我们提出了一种优先化方法,采用联动不平衡(LD)网络的Snprank,以改善疾病协会研究中候选SNP的优先级。对于LD网络结构的构建,我们基于R〜2> 0.6的SNP之间定义了相互链路,并优先考虑与其他高度排名的SNP相关的SNP。对于实验,我们应用了我们的方法来鉴定与前列腺癌相关的SNP标记。结果表明,该方法可以通过新发现疾病相关的SNP来改善现有方法,这不能通过现有方法来识别。

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