Analysis commons, a team approach to discovery in a big-data environment for genetic epidemiology

被引：70

作者：

Brody, Jennifer A. ^{[1
]}

Morrison, Alanna C. ^{[2
]}

Bis, Joshua C. ^{[1
]}

O'Connell, Jeffrey R. ^{[3
]}

Brown, Michael R. ^{[2
]}

Huffman, Jennifer E. ^{[4
,5
]}

Ames, Darren C. ^{[6
]}

Carroll, Andrew ^{[6
]}

Conomos, Matthew P. ^{[7
]}

Gabriel, Stacey ^{[8
]}

Gibbs, Richard A. ^{[9
]}

Gogarten, Stephanie M. ^{[7
]}

Gupta, Namrata ^{[8
]}

Jaquish, Cashell E. ^{[10
]}

Johnson, Andrew D. ^{[4
,5
]}

Lewis, Joshua P. ^{[3
]}

Liu, Xiaoming ^{[2
]}

Manning, Alisa K. ^{[11
,12
,13
,14
]}

Papanicolaou, George J. ^{[10
]}

Pitsillides, Achilleas N. ^{[4
,5
]}

Rice, Kenneth M. ^{[7
]}

Salerno, William ^{[9
]}

Sitlani, Colleen M. ^{[1
]}

Smith, Nicholas L. ^{[1
,15
,16
,17
]}

Heckbert, Susan R. ^{[1
,17
]}

Laurie, Cathy C. ^{[7
]}

Mitchell, Braxton D. ^{[3
,18
]}

Vasan, Ramachandran S. ^{[4
,5
,19
,20
,21
]}

Rich, Stephen S. ^{[22
]}

Rotter, Jerome I. ^{[23
,24
]}

Wilson, James G. ^{[25
]}

Boerwinkle, Eric ^{[2
,9
]}

Psaty, Bruce M. ^{[1
,15
,26
,27
]}

Cupples, L. Adrienne ^{[4
,5
,28
]}

机构：

[1] Univ Washington, Dept Med, Cardiovasc Hlth Res Unit, Seattle, WA 98195 USA

[2] Univ Texas Hlth Sci Ctr Houston, Sch Publ Hlth, Dept Epidemiol Human Genet & Environm Sci, Ctr Human Genet, Houston, TX 77030 USA

[3] Univ Maryland, Dept Med, Div Endocrinol Diabet & Nutr, Baltimore, MD 21201 USA

[4] NHLBI, Framingham Heart Study, Framingham, MA USA

[5] Boston Univ, Framingham, MA USA

[6] DNAnexus Inc, Mountain View, CA USA

[7] Univ Washington, Dept Biostat, Seattle, WA 98195 USA

[8] Broad Inst, Program Med & Populat Genet, Cambridge, MA USA

[9] Baylor Coll Med, Human Genome Sequencing Ctr, Houston, TX 77030 USA

[10] NHLBI, Div Cardiovasc Sci, Bldg 10, Bethesda, MD 20892 USA

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

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

[13] MIT, 77 Massachusetts Ave, Cambridge, MA 02139 USA

[14] Harvard Med Sch, Dept Med, Boston, MA USA

[15] Kaiser Permanente Washington Hlth Res Inst, Seattle, WA USA

[16] Seattle Epidemiol Res & Informat Ctr, Dept Vet Affairs, Off Res & Dev, Seattle, WA USA

[17] Univ Washington, Dept Epidemiol, Seattle, WA 98195 USA

[18] Baltimore Vet Adm Med Ctr, Geriatr Res & Educ Clin Ctr, Baltimore, MD USA

[19] Boston Univ, Sch Med, Dept Med, Prevent Med & Epidemiol Sect, Boston, MA 02118 USA

[20] Boston Univ, Sch Med, Dept Med, Cardiol Sect, Boston, MA 02118 USA

[21] Boston Univ, Sch Publ Hlth, Dept Epidemiol, Boston, MA USA

[22] Univ Virginia, Ctr Publ Hlth Genom, Charlottesville, VA USA

[23] Univ Calif Los Angeles, Med Ctr, Inst Translat Genom & Populat Sci, Dept Pediat,LABioMed Harbor, Torrance, CA 90509 USA

[24] Univ Calif Los Angeles, Med Ctr, Inst Translat Genom & Populat Sci, Dept Med,LABioMed Harbor, Torrance, CA 90509 USA

[25] Univ Mississippi, Med Ctr, Dept Physiol & Biophys, Jackson, MS 39216 USA

[26] Univ Washington, Dept Med, Seattle, WA USA

[27] Univ Washington, Dept Epidemiol & Hlth Serv, Seattle, WA 98195 USA

[28] Boston Univ, Sch Publ Hlth, Dept Biostat, Boston, MA USA

来源：

NATURE GENETICS | 2017年 / 49卷 / 11期

基金：

美国国家卫生研究院;

关键词：

ASSOCIATION; GENOME; VARIANTS; RARE;

D O I：

10.1038/ng.3968

中图分类号：

Q3 [遗传学];

学科分类号：

071007 ; 090102 ;

摘要：

The increasing volume of whole-genome sequence (WGS) and multi-omics data requires new approaches for analysis. As one solution, we have created the cloud-based Analysis Commons, which brings together genotype and phenotype data from multiple studies in a setting that is accessible by multiple investigators. This framework addresses many of the challenges of multicenter WGS analyses, including data-sharing mechanisms, phenotype harmonization, integrated multi-omics analyses, annotation and computational flexibility. In this setting, the computational pipeline facilitates a sequence-to-discovery analysis workflow illustrated here by an analysis of plasma fibrinogen levels in 3,996 individuals from the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) WGS program. The Analysis Commons represents a novel model for translating WGS resources from a massive quantity of phenotypic and genomic data into knowledge of the determinants of health and disease risk in diverse human populations.

引用

页码：1560 / 1563

页数：4

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