GSA-SNP: a general approach for gene set analysis of polymorphisms

被引:107
作者
Nam, Dougu [2 ]
Kim, Jin [3 ]
Kim, Seon-Young [4 ]
Kim, Sangsoo [1 ]
机构
[1] Soongsil Univ, Dept Bioinformat & Life Sci, Seoul 156743, South Korea
[2] Ulsan Natl Inst Sci & Technol, Sch Nanobiotech & Chem Engn, Ulsan 689798, South Korea
[3] Seoul Natl Univ, Sch Comp Sci & Engn, Seoul 151742, South Korea
[4] Korea Res Inst Biosci & Biotechnol, Med Genom Res Ctr, Taejon 305806, South Korea
关键词
GENOME-WIDE ASSOCIATION; ENRICHMENT ANALYSIS; ADULT HEIGHT; TRAITS; VARIANTS; PATHWAYS; DISEASES; LINKAGE; LOCI;
D O I
10.1093/nar/gkq428
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Genome-wide association (GWA) study aims to identify the genetic factors associated with the traits of interest. However, the power of GWA analysis has been seriously limited by the enormous number of markers tested. Recently, the gene set analysis (GSA) methods were introduced to GWA studies to address the association of gene sets that share common biological functions. GSA considerably increased the power of association analysis and successfully identified coordinated association patterns of gene sets. There have been several approaches in this direction with some limitations. Here, we present a general approach for GSA in GWA analysis and a stand-alone software GSA-SNP that implements three widely used GSA methods. GSA-SNP provides a fast computation and an easy-to-use interface. The software and test datasets are freely available at http://gsa.muldas.org. We provide an exemplary analysis on adult heights in a Korean population.
引用
收藏
页码:W749 / W754
页数:6
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