一种新的信息论方法在病例对照研究中检测基因-基因相互作用

Xiangdong Zhou, Keith C. C. Chan
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引用次数: 0

摘要

基因-基因相互作用是在基因型数据或基因芯片表达数据中选择与疾病相关的基因时需要考虑的重要因素。然而,目前对基因-基因相互作用的定义并不十分明确和准确。本文证明了一个不等式,并根据这个不等式提出了基因-基因相互作用的一个新定义:基于条件独立和冗余的基因-基因相互作用的定义(CIR),以及相互作用群的定义。基于这些新的定义和定理,提出了一种新的基因-基因相互作用检测算法。实验结果表明了这些新定义的有效性和新算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A new information-theoretic approach to detect gene-gene interactions in case-control studies
Gene-gene interaction is an important factor to consider in selecting genes in genotype data or microarray expression data for association with diseases. However current definitions of gene-gene interaction are not very clear and accurate. An inequality is proved in this paper and a new definition of gene-gene interaction: conditional independence and redundancy based definition of gene-gene interaction (CIR), together with a definition of interaction group are proposed according to this inequality. A new algorithm to detect gene-gene interaction with order greater than two is also proposed based on these new definitions and a theorem. Experimental results show the usefulness of these new definitions and the effectiveness and efficiency of this new algorithm.
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