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Epistasy Search in Population-Based Gene Mapping Using Mutual Information

机译:使用相互信息的基于人口的基因映射的Epistasy搜索

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Gene mapping intends to identify the causal genetic regions of a specific phenotype mostly a complex disease. These diseases are believed to have multiple contributing loci that are potentially unknown and often have subtle patterns making them hard to find. Shannon's mutual information figure is used as a criterion. Algorithms based on this criterion as presented and discussed. Furthermore, an algorithm is proposed to form relevance chains. The proposed algorithms are especially in favor of diseases having almost equally contributing regions known as being epistatic and is applied to both simulated and real data. AMD disease results are included. Some highly associated markers are found in AMD. C# source files for relevance-chains are freely available at https://www.sharemation.com/amanzour.
机译:基因映射旨在鉴定特定表型的因果遗传区域主要是复杂的疾病。这些疾病被认为有多个贡献的基因座,可能是潜在的未知,并且通常具有微妙的模式使它们很难找到。 Shannon的互信息形象用作标准。基于此标准的算法如呈现和讨论的。此外,提出了一种算法来形成相关性链。所提出的算法尤其有利于具有已知是认证的几乎贡献区域的疾病,并且应用于模拟和实际数据。包括AMD疾病结果。在AMD中发现了一些高度相关的标记。 C#相关链的源文件在https://www.sharemation.com/amanzour中自由使用。

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