SNP2GO: Functional Analysis of Genome-Wide Association Studies | Zendy

David Szkiba | Zendy; Martin Kapun | Zendy; Arndt von Haeseler | Zendy; Miguel Gallach | Zendy

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SNP2GO: Functional Analysis of Genome-Wide Association Studies

Author(s) -

David Szkiba,

Martin Kapun,

Arndt von Haeseler,

Miguel Gallach

Publication year - 2014

Publication title -

genetics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 2.792

H-Index - 246

eISSN - 1943-2631

pISSN - 0016-6731

DOI - 10.1534/genetics.113.160341

Subject(s) - biology , genetics , genome wide association study , association (psychology) , genetic association , genome , computational biology , evolutionary biology , gene , single nucleotide polymorphism , genotype , philosophy , epistemology

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.

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