首页> 外文会议>2011 IEEE International Conference on Bioinformatics and Biomedicine >Efficient and Fast Analysis for Detecting High Order Gene-by-Gene Interactions in a Genome-Wide Association Study
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Efficient and Fast Analysis for Detecting High Order Gene-by-Gene Interactions in a Genome-Wide Association Study

机译:在全基因组关联研究中检测高阶基因间相互作用的高效快速分析

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Most common complex traits are affected by multiple genes and/or environmental factors. To understand genetic architecture of complex traits, the investigation of gene-gene and gene-environment interactions can be essential. However, conducting gene-gene interaction using genome-wide data requires exploring a huge search space and suffers from a computation burden due to high dimensionality of genetic data. To identify gene-gene interaction more efficiently, we propose a gene-based reduction method which first summarizes the gene effect by combining multiple single nucleotide polymorphism (SNP) and then performs the gene-gene interaction via the summarized gene effect. By reducing the search space from SNPs to gene, our gene-based method becomes efficient and fast for identifying gene-gene interaction in genome wide association studies. The gene-based reduction method is illustrated by hypertension data from a Korean population.
机译:最常见的复杂性状受多种基因和/或环境因素的影响。为了理解复杂性状的遗传结构,对基因-基因和基因-环境相互作用的研究可能是必不可少的。然而,使用全基因组数据进行基因-基因相互作用需要探索巨大的搜索空间,并且由于遗传数据的高维度而遭受了计算负担。为了更有效地识别基因-基因相互作用,我们提出了一种基于基因的还原方法,该方法首先通过结合多个单核苷酸多态性(SNP)总结基因效应,然后通过总结的基因效应进行基因-基因相互作用。通过减少从SNPs到基因的搜索空间,我们的基于基因的方法可以高效,快速地识别全基因组关联研究中的基因与基因之间的相互作用。韩国人群的高血压数据说明了基于基因的还原方法。

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