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This article is part of the supplement: Genetic Analysis Workshop 17: Unraveling Human Exome Data

Open Access Proceedings

Identifying rare variants from exome scans: the GAW17 experience

Saurabh Ghosh1*, Heike Bickeböller2, Julia Bailey3, Joan E Bailey-Wilson4, Rita Cantor5, Robert Culverhouse6, Warwick Daw7, Anita L DeStefano8, Corinne D Engelman9, Anthony Hinrichs10, Jeanine Houwing-Duistermaat11, Inke R König12, Jack Kent13, Nan Laird14, Nathan Pankratz15, Andrew Paterson16, Elizabeth Pugh17, Brian Suarez10, Yan Sun18, Alun Thomas19, Nathan Tintle20, Xiaofeng Zhu21, Andreas Ziegler12, Jean W MacCluer13 and Laura Almasy13

Author Affiliations

1 Human Genetics Unit, Indian Statistical Institute, Kolkata 700018, India

2 University of Göttingen Medical School, Göttingen, 37073, Germany

3 Department of Epidemiology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095 USA; and Research Service, VA GLAHS Epilepsy Center of Excellence, Epilepsy Genetics/Genomics Laboratories, Los Angeles, CA, USA

4 National Human Genome Research Institute, National Institutes of Health, Baltimore, MD 21224, USA

5 Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA

6 Department of Internal Medicine, Washington University School of Medicine, St Louis, MO 63110, USA

7 Division of Statistical Genomics, Washington University School of Medicine, St Louis, MO 63110, USA

8 School of Public Health, Boston University, Boston, MA 02118, USA

9 School of Medicine and Public Health, University of Wisconsin, Madison, WI 53726, USA

10 Department of Psychiatry, Washington University School of Medicine, St Louis, MO 63110, USA

11 Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden 2300RC, The Netherlands

12 Institut für Medizinische Biometrie und Statistik, Universität zu Lübeck, Universitätsklinikum Schleswig-Holstein, Campus Lübeck, Lübeck, Germany

13 Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX 78245, USA

14 Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA

15 Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN 55104, USA

16 Division of Biostatistics, University of Toronto, Toronto, ON M5S 3G4, Canada

17 Center for Inherited Disease Research, Johns Hopkins University, Baltimore, MD 21202, USA

18 Department of Epidemiology, Emory University, Atlanta, GA 30322, USA

19 Department of Epidemiology, University of Utah, Salt Lake City, UT 84108, USA

20 Department of Math and Computer Science, Dordt College, Sioux Center, IA 51250, USA

21 Department of Epidemiology and Biostatistics, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA

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BMC Proceedings 2011, 5(Suppl 9):S1  doi:10.1186/1753-6561-5-S9-S1

Published: 29 November 2011

Abstract

Genetic Analysis Workshop 17 (GAW17) provided a platform for evaluating existing statistical genetic methods and for developing novel methods to analyze rare variants that modulate complex traits. In this article, we present an overview of the 1000 Genomes Project exome data and simulated phenotype data that were distributed to GAW17 participants for analyses, the different issues addressed by the participants, and the process of preparation of manuscripts resulting from the discussions during the workshop.