Practical aspects of imputation-driven meta-analysis of genome-wide association studies

被引：407

作者：

de Bakker, Paul I. W. ^{[1
,2
]}

Ferreira, Manuel A. R. ^{[2
,3
]}

Jia, Xiaoming ^{[4
]}

Neale, Benjamin M. ^{[2
,3
]}

Raychaudhuri, Soumya ^{[2
,3
,5
]}

Voight, Benjamin F. ^{[2
,3
]}

机构：

[1] Harvard Univ, Sch Med, Partners Healthcare Syst Ctr Genet & Genom, Div Genet,Dept Med,Brigham & Womens Hosp, Boston, MA 02115 USA

[2] Harvard & MIT, Broad Inst, Program Med & Populat Genet, Cambridge, MA 02142 USA

[3] Massachusetts Gen Hosp, Ctr Human Genet Res, Boston, MA 02114 USA

[4] Harvard Mit Div Hlth Sci & Technol, Boston, MA 02115 USA

[5] Brigham & Womens Hosp, Div Rheumatol Allergy & Immunol, Boston, MA 02115 USA

来源：

HUMAN MOLECULAR GENETICS | 2008年 / 17卷

关键词：

D O I：

10.1093/hmg/ddn288

中图分类号：

Q5 [生物化学]; Q7 [分子生物学];

学科分类号：

071010 [生物化学与分子生物学]; 081704 [应用化学];

摘要：

Motivated by the overwhelming success of genome-wide association studies, droves of researchers are working vigorously to exchange and to combine genetic data to expediently discover genetic risk factors for common human traits. The primary tools that fuel these new efforts are imputation, allowing researchers who have collected data on a diversity of genotype platforms to share data in a uniformly exchangeable format, and meta-analysis for pooling statistical support for a genotype-phenotype association. As many groups are forming collaborations to engage in these efforts, this review collects a series of guidelines, practical detail and learned experiences from a variety of individuals who have contributed to the subject.

引用

页码：R122 / R128

页数：7

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