SNP2GO：全基因组关联研究的功能分析
SNP2GO: functional analysis of genome-wide association studies.
作者信息
Szkiba David, Kapun Martin, von Haeseler Arndt, Gallach Miguel
机构信息
Center for Integrative Bioinformatics Vienna, Max F. Perutz Laboratories, University of Vienna and Medical University of Vienna, A-1030 Vienna, Austria.
出版信息
Genetics. 2014 May;197(1):285-9. doi: 10.1534/genetics.113.160341. Epub 2014 Feb 21.
Abstract
Genome-wide association studies (GWAS) are designed to identify the portion of single-nucleotide polymorphisms (SNPs) in genome sequences associated with a complex trait. Strategies based on the gene list enrichment concept are currently applied for the functional analysis of GWAS, according to which a significant overrepresentation of candidate genes associated with a biological pathway is used as a proxy to infer overrepresentation of candidate SNPs in the pathway. Here we show that such inference is not always valid and introduce the program SNP2GO, which implements a new method to properly test for the overrepresentation of candidate SNPs in biological pathways.
摘要
全基因组关联研究（GWAS）旨在识别基因组序列中与复杂性状相关的单核苷酸多态性（SNP）部分。基于基因列表富集概念的策略目前应用于GWAS的功能分析，据此，与生物途径相关的候选基因的显著过度代表性被用作推断该途径中候选SNP过度代表性的代理。在这里，我们表明这种推断并不总是有效的，并介绍了程序SNP2GO，它实现了一种新方法来正确测试生物途径中候选SNP的过度代表性。
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