Next-generation genotype imputation service and methods

被引：2354

作者：

Das, Sayantan ^{[1
]}

Forer, Lukas ^{[2
]}

Schoenherr, Sebastian ^{[2
]}

Sidore, Carlo ^{[1
,3
,4
]}

Locke, Adam E. ^{[1
]}

Kwong, Alan ^{[1
]}

Vrieze, Scott I. ^{[5
]}

Chew, Emily Y. ^{[6
]}

Levy, Shawn ^{[7
]}

McGue, Matt ^{[8
]}

Schlessinger, David ^{[9
]}

Stambolian, Dwight ^{[10
]}

Loh, Po-Ru ^{[11
,12
]}

Iacono, William G. ^{[8
]}

Swaroop, Anand ^{[13
]}

Scott, Laura J. ^{[1
]}

Cucca, Francesco ^{[3
,4
]}

Kronenberg, Florian ^{[2
]}

Boehnke, Michael ^{[1
]}

Abecasis, Goncalo R. ^{[1
]}

Fuchsberger, Christian ^{[1
,2
,14
]}

机构：

[1] Univ Michigan, Ctr Stat Genet, Dept Biostat, Ann Arbor, MI 48109 USA

[2] Med Univ Innsbruck, Dept Med Genet Mol & Clin Pharmacol, Div Genet Epidemiol, Innsbruck, Austria

[3] CNR, Ist Ric Genet & Biomed, Cagliari, Italy

[4] Univ Sassari, Dipartimento Sci Biomed, Sassari, Italy

[5] Univ Colorado, Inst Behav Sci, Boulder, CO 80309 USA

[6] NEI, Clin Trials Branch, Div Epidemiol & Clin Applicat, US Natl Inst Hlth, Bethesda, MD 20892 USA

[7] HudsonAlpha Inst Biotechnol, Huntsville, AL USA

[8] Univ Minnesota, Dept Psychol, Minneapolis, MN USA

[9] NIA, Genet Lab, US Natl Inst Hlth, Baltimore, MD 21224 USA

[10] Univ Penn, Dept Genet, Philadelphia, PA USA

[11] Harvard TH Chan Sch Publ Hlth, Dept Epidemiol, Boston, MA USA

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

[13] NEI, Neurobiol Neurodegenerat & Repair Lab, US Natl Inst Hlth, Bethesda, MD 20892 USA

[14] Univ Lubeck, European Acad Bolzano Bozen EURAC, Ctr Biomed, Bolzano, Italy

来源：

NATURE GENETICS | 2016年 / 48卷 / 10期

基金：

奥地利科学基金会; 美国国家卫生研究院;

关键词：

ASSOCIATION; PROTECTION; THOUSANDS; MAPREDUCE;

D O I：

10.1038/ng.3656

中图分类号：

Q3 [遗传学];

学科分类号：

071007 ; 090102 ;

摘要：

Genotype imputation is a key component of genetic association studies, where it increases power, facilitates meta-analysis, and aids interpretation of signals. Genotype imputation is computationally demanding and, with current tools, typically requires access to a high-performance computing cluster and to a reference panel of sequenced genomes. Here we describe improvements to imputation machinery that reduce computational requirements by more than an order of magnitude with no loss of accuracy in comparison to standard imputation tools. We also describe a new web-based service for imputation that facilitates access to new reference panels and greatly improves user experience and productivity.

引用

页码：1284 / 1287

页数：4

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