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

Research output: Contribution to journalReview articlepeer-review

248 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 languageEnglish (US)
Pages (from-to)1045-1051
Number of pages7
JournalNature genetics
Volume39
Issue number9
DOIs
StatePublished - Sep 2007
Externally publishedYes

ASJC Scopus subject areas

  • Genetics

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