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Maximum Likelihood Resolution of Multi-block Genotypes

机译:多嵌段基因型的最大可能性分辨率

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摘要

We present a new algorithm for the problems of genotype phasing and block partitioning. Our algorithm is based on a new stochastic model, and on the novel concept of probabilistic common haplotypes. We formulate the goals of genotype resolving and block partitioning as a maximum likelihood problem, and solve it by an EM algorithm. When applied to real biological SNP data, our algorithm outperforms two state of the art phasing algorithms. Our algorithm is also considerably more sensitive and accuratethan a previous method in predicting and identifying disease association.
机译:我们提出了一种新的基因型序列和块分区问题的新算法。我们的算法基于新的随机模型,并在概率普通单倍型的新颖概念上。我们制定基因型解析和块分区作为最大可能性问题的目标,并通过EM算法解决。当应用于真实的生物SNP数据时,我们的算法优于缩放算法的两个状态。我们的算法在预测和识别疾病协会的预测和识别疾病协会方面也相当敏感和准确。

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