Large scale association analysis for drug addiction: results from SNP to gene.
Large scale association analysis for drug addiction: results from SNP to gene.
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DOI：
10.1100/2012/939584
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发表时间：
2012
影响因子：
--
通讯作者：
Zhang H
中科院分区：
文献类型：
--
作者：
Guo X;Liu Z;Wang X;Zhang H
许多遗传关联研究使用单核苷酸多态性 (SNP) 数据来识别复杂疾病的遗传变异。尽管基于 SNP 的关联在全基因组关联研究 (GWAS) 中最常见，但基于基因的关联分析在了解复杂疾病的遗传病因方面受到越来越多的关注。虽然这两种方法都用于分析相同的数据，但很少有全基因组关联研究比较结果或观察它们之间的联系。我们对成瘾研究：遗传学与环境 (SAGE) 的数据进行了全面分析，并比较了基于 SNP 和基于基因的分析结果。我们的结果表明，基于基因的方法补充了基于单核苷酸多态性（SNP）的个体分析，并且从概念上讲它们是密切相关的。就基因发现而言，我们的结果验证了许多基因，这些基因要么是从同一数据集的分析中报告的，要么是基于物质依赖性动物研究报告的。
Many genetic association studies used single nucleotide polymorphisms (SNPs) data to identify genetic variants for complex diseases. Although SNP-based associations are most common in genome-wide association studies (GWAS), gene-based association analysis has received increasing attention in understanding genetic etiologies for complex diseases. While both methods have been used to analyze the same data, few genome-wide association studies compare the results or observe the connection between them. We performed a comprehensive analysis of the data from the Study of Addiction: Genetics and Environment (SAGE) and compared the results from the SNP-based and gene-based analyses. Our results suggest that the gene-based method complements the individual SNP-based analysis, and conceptually they are closely related. In terms of gene findings, our results validate many genes that were either reported from the analysis of the same dataset or based on animal studies for substance dependence.
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通讯作者：
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