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首页> 外文期刊>Journal of Bioinformatics and Computational Biology >New multilocus linkage disequilibrium measure for tag SNP selection
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New multilocus linkage disequilibrium measure for tag SNP selection

机译：标签SNP选择的新多点连锁不平衡措施

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Numerous approaches have been proposed for selecting an optimal tag single-nucleotide polymorphism (SNP) set. Most of these approaches are based on linkage disequilibrium (LD). Classical LD measures, such as D' and r2, are frequently used to quantify the relationship between two marker (pairwise) linkage disequilibria. Despite of their successful use in many applications, these measures cannot be used to measure the LD between multiple- marker. These LD measures need information about the frequencies of alleles collected from haplotype dataset. In this study, a cluster algorithm is proposed to cluster SNPs according to multilocus LD measure which is based on information theory. After that, tag SNPs are selected in each cluster optimized by the number of tag SNPs, prediction accuracy and so on. The experimental results show that this new LD measure can be directly applied to genotype dataset collected from the HapMap project, so that it saves the cost of haplotyping. More importantly, the proposed method significantly improves the efficiency and prediction accuracy of tag SNP selection.
机译：人们提出了许多方法来选择最佳标签单核苷酸多态性（SNP）集。这些方法大多基于连锁不平衡（LD）。经典的LD度量，如D'和r2，经常用于量化两个标记（成对）连锁不平衡之间的关系。尽管它们在许多应用中得到了成功的应用，但这些测量方法不能用于测量多个标记之间的LD。这些LD测量需要有关从单倍型数据集中收集的等位基因频率的信息。本研究提出了一种基于信息论的多位点LD测度的SNP聚类算法。然后，根据标记SNPs的数量、预测精度等因素，在每个聚类中选择标记SNPs。实验结果表明，这种新的LD测度可以直接应用于从HapMap项目收集的基因型数据集，从而节省了单倍型分析的成本。更重要的是，该方法显著提高了标签SNP选择的效率和预测精度。

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