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Simulating Linkage Disequilibrium Structures in a Human Population for SNP Association Studies

机译:模拟人群中的连锁不平衡结构,用于SNP关联研究

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摘要

Existing simulation methods usually simulate linkage disequilibrium (LD) structures starting with an initial population that is randomly generated according to specified allele frequencies. These at random based methods might be unstable because the LD level of the initial population is generally extremely low. This study presents a new algorithm, SIMLD, to simulate genome populations with real LD structures. SIMLD begins from an initial population with possibly the highest LD level, and then the LD decays to fit the desired level through processes of mating and recombination over generations. SIMLD can produce case–control samples according to various disease models. Using empirical SNP marker information from three populations of HapMap data, we implement the proposed algorithm and demonstrate a set of experimental results.
机译:现有的仿真方法通常从初始种群开始模拟连锁不平衡(LD)结构,该种群根据指定的等位基因频率随机产生。这些基于随机的方法可能不稳定,因为初始种群的LD水平通常非常低。这项研究提出了一种新的算法SIMLD,用于模拟具有真实LD结构的基因组种群。 SIMLD从可能具有最高LD水平的初始种群开始,然后经过几代的交配和重组过程,LD衰减至适合所需水平。 SIMLD可以根据各种疾病模型生成病例对照样品。利用来自三个HapMap数据的经验SNP标记信息,我们实现了所提出的算法并演示了一组实验结果。

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