CAUSALdb: a database for disease/trait causal variants identified using summary statistics of genome-wide association studies

被引:55
|
作者
Wang, Jianhua [1 ,2 ]
Huang, Dandan [1 ,2 ]
Zhou, Yao [1 ,2 ]
Yao, Hongcheng [3 ]
Liu, Huanhuan [2 ]
Zhai, Sinan [4 ]
Wu, Chengwei [4 ]
Zheng, Zhanye [2 ]
Zhao, Ke [2 ]
Wang, Zhao [2 ]
Yi, Xianfu [4 ]
Zhang, Shijie [2 ]
Liu, Xiaorong [5 ]
Liu, Zipeng [6 ]
Chen, Kexin [7 ]
Yu, Ying [2 ]
Sham, Pak Chung [6 ]
Li, Mulin Jun [1 ,2 ,7 ]
机构
[1] Tianjin Med Univ, Canc Inst & Hosp, Natl Clin Res Ctr Canc, Collaborat Innovat Ctr Tianjin Med Epigenet 2011, Tianjin, Peoples R China
[2] Tianjin Med Univ, Sch Basic Med Sci, Dept Pharmacol, Tianjin Key Lab Inflammat Biol, Tianjin, Peoples R China
[3] Univ Hong Kong, LKS Fac Med, Sch Biomed Sci, Hong Kong, Peoples R China
[4] Tianjin Med Univ, Sch Biomed Engn, Tianjin, Peoples R China
[5] Shenzhen Childrens Hosp, Inst Pediat, Clin Lab, Shenzhen, Peoples R China
[6] Univ Hong Kong, LKS Fac Med, Ctr Genom Sci, State Key Lab Brain & Cognit Sci, Hong Kong, Peoples R China
[7] Tianjin Med Univ, Canc Inst & Hosp, Natl Clin Res Ctr Canc, Tianjin Key Lab Mol Canc Epidemiol,Dept Epidemiol, Tianjin, Peoples R China
基金
中国国家自然科学基金;
关键词
COMPLEX TRAITS; VISUALIZATION; LOCI;
D O I
10.1093/nar/gkz1026
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 studies (GWASs) have revolutionized the field of complex trait genetics over the past decade, yet for most of the significant genotype-phenotype associations the true causal variants remain unknown. Identifying and interpreting how causal genetic variants confer disease susceptibility is still a big challenge. Herein we introduce a new database, CAUSALdb, to integrate the most comprehensive GWAS summary statistics to date and identify credible sets of potential causal variants using uniformly processed fine-mapping. The database has six major features: it (i) curates 3052 high-quality, fine-mappable GWAS summary statistics across five human super-populations and 2629 unique traits; (ii) estimates causal probabilities of all genetic variants in GWAS si1nificant loci using three state-of-the-art fine-mapping tools; (iii) maps the reported traits to a powerful ontology MeSH, making it simple for users to browse studies on the trait tree; (iv) incorporates highly interactive Manhattan and LocusZoom-like plots to allow visualization of credible sets in a single web page more efficiently; (v) enables online comparison of causal relations on variant-, gene- and trait-levels among studies with different sample sizes or populations and (vi) offers comprehensive variant annotations by integrating massive base-wise and allele-specific functional annotations. CAUSALdb is freely available at http://mulinlab.org/causaldb.
引用
收藏
页码:D807 / D816
页数:10
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