New models of collaboration in genome-wide association studies: The Genetic Association Information Network

Teri A. Manolio; Laura Lyman Rodriguez; Lisa Brooks; Gonçalo Abecasis; Dennis Ballinger; Mark Daly; Peter Donnelly; Stephen V. Faraone; Kelly Frazer; Stacey Gabriel; Pablo Gejman; Alan Guttmacher; Emily L. Harris; Thomas Insel; John R. Kelsoe; Eric Lander; Norma McCowin; Matthew D. Mailman; Elizabeth Nabel; James Ostell; Elizabeth Pugh; Stephen Sherry; Patrick F. Sullivan; John F. Thompson; James Warram; David Wholley; Patrice M. Milos; Francis S. Collins

doi:10.1038/ng2127

New models of collaboration in genome-wide association studies: The Genetic Association Information Network

Teri A. Manolio
, Laura Lyman Rodriguez
, Lisa Brooks
, Gonçalo Abecasis
, Dennis Ballinger
, Mark Daly
, Peter Donnelly
, Stephen V. Faraone
, Kelly Frazer
, Stacey Gabriel
, Pablo Gejman
, Alan Guttmacher
, Emily L. Harris
, Thomas Insel
, John R. Kelsoe
, Eric Lander
, Norma McCowin
, Matthew D. Mailman
, Elizabeth Nabel
, James Ostell

Elizabeth Pugh, Stephen Sherry, Patrick F. Sullivan, John F. Thompson, James Warram, David Wholley, Patrice M. Milos, Francis S. Collins

Psychiatry

Upstate Medical University

National Institutes of Health
University of Michigan, Ann Arbor
Perlegen Sciences, Inc.
Broad Institute
University of Oxford
Scripps Research Institute
Evanston Northwestern Healthcare
University of California at San Diego
Eli Lilly
Johns Hopkins University
University of North Carolina at Chapel Hill
Pfizer
Joslin Diabetes Center
Helicos BioSciences Corp.

Research output: Contribution to journal › Review article › peer-review

280 Scopus citations

Abstract

The Genetic Association Information Network (GAIN) is a public-private partnership established to investigate the genetic basis of common diseases through a series of collaborative genome-wide association studies. GAIN has used new approaches for project selection, data deposition and distribution, collaborative analysis, publication and protection from premature intellectual property claims. These demonstrate a new commitment to shared scientific knowledge that should facilitate rapid advances in understanding the genetics of complex diseases.

Original language	English
Pages (from-to)	1045-1051
Number of pages	7
Journal	Nature Genetics
Volume	39
Issue number	9
DOIs	https://doi.org/10.1038/ng2127
State	Published - Sep 2007

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Manolio, T. A., Rodriguez, L. L., Brooks, L., Abecasis, G., Ballinger, D., Daly, M., Donnelly, P., Faraone, S. V., Frazer, K., Gabriel, S., Gejman, P., Guttmacher, A., Harris, E. L., Insel, T., Kelsoe, J. R., Lander, E., McCowin, N., Mailman, M. D., Nabel, E., ... Collins, F. S. (2007). New models of collaboration in genome-wide association studies: The Genetic Association Information Network. Nature Genetics, 39(9), 1045-1051. https://doi.org/10.1038/ng2127

@article{5cd645e136d142ef9b844119579a2308,

title = "New models of collaboration in genome-wide association studies: The Genetic Association Information Network",

abstract = "The Genetic Association Information Network (GAIN) is a public-private partnership established to investigate the genetic basis of common diseases through a series of collaborative genome-wide association studies. GAIN has used new approaches for project selection, data deposition and distribution, collaborative analysis, publication and protection from premature intellectual property claims. These demonstrate a new commitment to shared scientific knowledge that should facilitate rapid advances in understanding the genetics of complex diseases.",

author = "Manolio, \{Teri A.\} and Rodriguez, \{Laura Lyman\} and Lisa Brooks and Gon{\c c}alo Abecasis and Dennis Ballinger and Mark Daly and Peter Donnelly and Faraone, \{Stephen V.\} and Kelly Frazer and Stacey Gabriel and Pablo Gejman and Alan Guttmacher and Harris, \{Emily L.\} and Thomas Insel and Kelsoe, \{John R.\} and Eric Lander and Norma McCowin and Mailman, \{Matthew D.\} and Elizabeth Nabel and James Ostell and Elizabeth Pugh and Stephen Sherry and Sullivan, \{Patrick F.\} and Thompson, \{John F.\} and James Warram and David Wholley and Milos, \{Patrice M.\} and Collins, \{Francis S.\}",

year = "2007",

month = sep,

doi = "10.1038/ng2127",

language = "English",

volume = "39",

pages = "1045--1051",

journal = "Nature Genetics",

issn = "1061-4036",

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Manolio, TA, Rodriguez, LL, Brooks, L, Abecasis, G, Ballinger, D, Daly, M, Donnelly, P, Faraone, SV, Frazer, K, Gabriel, S, Gejman, P, Guttmacher, A, Harris, EL, Insel, T, Kelsoe, JR, Lander, E, McCowin, N, Mailman, MD, Nabel, E, Ostell, J, Pugh, E, Sherry, S, Sullivan, PF, Thompson, JF, Warram, J, Wholley, D, Milos, PM & Collins, FS 2007, 'New models of collaboration in genome-wide association studies: The Genetic Association Information Network', Nature Genetics, vol. 39, no. 9, pp. 1045-1051. https://doi.org/10.1038/ng2127

TY - JOUR

T1 - New models of collaboration in genome-wide association studies

T2 - The Genetic Association Information Network

AU - Manolio, Teri A.

AU - Rodriguez, Laura Lyman

AU - Brooks, Lisa

AU - Abecasis, Gonçalo

AU - Ballinger, Dennis

AU - Daly, Mark

AU - Donnelly, Peter

AU - Faraone, Stephen V.

AU - Frazer, Kelly

AU - Gabriel, Stacey

AU - Gejman, Pablo

AU - Guttmacher, Alan

AU - Harris, Emily L.

AU - Insel, Thomas

AU - Kelsoe, John R.

AU - Lander, Eric

AU - McCowin, Norma

AU - Mailman, Matthew D.

AU - Nabel, Elizabeth

AU - Ostell, James

AU - Pugh, Elizabeth

AU - Sherry, Stephen

AU - Sullivan, Patrick F.

AU - Thompson, John F.

AU - Warram, James

AU - Wholley, David

AU - Milos, Patrice M.

AU - Collins, Francis S.

PY - 2007/9

Y1 - 2007/9

N2 - The Genetic Association Information Network (GAIN) is a public-private partnership established to investigate the genetic basis of common diseases through a series of collaborative genome-wide association studies. GAIN has used new approaches for project selection, data deposition and distribution, collaborative analysis, publication and protection from premature intellectual property claims. These demonstrate a new commitment to shared scientific knowledge that should facilitate rapid advances in understanding the genetics of complex diseases.

AB - The Genetic Association Information Network (GAIN) is a public-private partnership established to investigate the genetic basis of common diseases through a series of collaborative genome-wide association studies. GAIN has used new approaches for project selection, data deposition and distribution, collaborative analysis, publication and protection from premature intellectual property claims. These demonstrate a new commitment to shared scientific knowledge that should facilitate rapid advances in understanding the genetics of complex diseases.

UR - https://www.scopus.com/pages/publications/34548340684

U2 - 10.1038/ng2127

DO - 10.1038/ng2127

M3 - Review article

C2 - 17728769

SN - 1061-4036

VL - 39

SP - 1045

EP - 1051

JO - Nature Genetics

JF - Nature Genetics

IS - 9

ER -

New models of collaboration in genome-wide association studies: The Genetic Association Information Network

Abstract

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