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An EM method based on entropy LD block partition for haplotype inference

机译:基于熵LD块划分的单倍型推断EM方法

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Genetic diseases have attracted much attention to the genetic research which depends on the data named haplotypes. Because of most haplotypes are generated from genotypes, haplotype inference (HI) problem becomes very popular. To solve this problem, we propose a new method based on EM and partition-ligation (PL) strategy. Compared to the previous methods, our algorithm uses the PL strategy based on multilocus linkage disequilibrium (LD), which has an advantage over the uniform block partition and pairwise LD. Considering the scale of data and the missing alleles, we also change the ligation strategy to control the complexity of time and space. The experimental results on the real data and the simulated data show that the algorithm in this paper has better performance than previous ones.
机译:遗传疾病引起了人们对遗传研究的极大关注,遗传研究依赖于称为单倍型的数据。由于大多数单倍型是从基因型生成的,因此单倍型推断(HI)问题变得非常普遍。为了解决这个问题,我们提出了一种基于EM和分区连接策略的新方法。与以前的方法相比,我们的算法使用基于多位点连锁不平衡(LD)的PL策略,与统一块划分和成对LD相比具有优势。考虑到数据规模和缺失的等位基因,我们还更改了连接策略以控制时间和空间的复杂性。在真实数据和仿真数据上的实验结果表明,本文算法比以前的算法具有更好的性能。

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