SNP2GO: Functional Analysis of Genome-Wide Association Studies

被引：26

作者：

Szkiba, David ^{[1
,2
]}

Kapun, Martin ^{[3
,4
]}

von Haeseler, Arndt ^{[1
,2
,5
]}

Gallach, Miguel ^{[1
,2
]}

机构：

[1] Univ Vienna, Ctr Integrat Bioinformat Vienna, Max F Perutz Labs, A-1030 Vienna, Austria

[2] Med Univ Vienna, A-1030 Vienna, Austria

[3] Univ Lausanne, Dept Ecol & Evolut, CH-1015 Lausanne, Switzerland

[4] Vetmeduni Vienna, Inst Populat Genet, A-1210 Vienna, Austria

[5] Univ Vienna, Fac Comp Sci, A-1090 Vienna, Austria

来源：

GENETICS | 2014年 / 197卷 / 01期

关键词：

GWAS; SNP; linkage disequilibrium; Gene Ontology; GENE SET ENRICHMENT; DROSOPHILA; EVOLUTION; PATTERNS; MELANOGASTER; POPULATIONS; ADAPTATION; CONTEXT; TRAITS;

D O I：

10.1534/genetics.113.160341

中图分类号：

Q3 [遗传学];

学科分类号：

071007 ; 090102 ;

摘要：

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.

引用

页码：285 / 289

页数：5

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