GA 和 GWAS：使用遗传算法搜索多基因座关联。
The GA and the GWAS: using genetic algorithms to search for multilocus associations.
机构信息
Oregon Health & Science University, Portland.
出版信息
IEEE/ACM Trans Comput Biol Bioinform. 2012 May-Jun;9(3):899-910. doi: 10.1109/TCBB.2011.145. Epub 2011 Oct 19.
Abstract
Enormous data collection efforts and improvements in technology have made large genome-wide association studies a promising approach for better understanding the genetics of common diseases. Still, the knowledge gained from these studies may be extended even further by testing the hypothesis that genetic susceptibility is due to the combined effect of multiple variants or interactions between variants. Here we explore and evaluate the use of a genetic algorithm to discover groups of SNPs (of size 2, 3, or 4) that are jointly associated with bipolar disorder. The algorithm is guided by the structure of a gene interaction network, and is able to find groups of SNPs that are strongly associated with the disease, while performing far fewer statistical tests than other methods.
摘要
大量的数据收集工作和技术的改进使得全基因组关联研究成为一种很有前途的方法，可以更好地了解常见疾病的遗传学。不过，通过检验遗传易感性是由多个变体或变体之间的相互作用共同作用的假设，从这些研究中获得的知识可能会得到进一步扩展。在这里，我们探索并评估了使用遗传算法来发现与双相情感障碍共同相关的 SNP 组（大小为 2、3 或 4）的方法。该算法以基因相互作用网络的结构为指导，能够找到与疾病强烈相关的 SNP 组，同时比其他方法进行的统计检验要少得多。
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