1 Section for Metabolic Genetics, Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, Københavns Universitet2 Department of Genetic Epidemiology, Institute of Epidemiology and Preventive Medicine, University of Regensburg3 Medical Research Council (MRC) Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK.4 Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, USA.5 Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, UK.6 Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, USA.7 Tartu Uelikool (University of Tartu)8 Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK.9 Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University10 Department of Epidemiology, University of North Carolina, Chapel Hill, North Carolina, USA.11 Wellcome Trust Sanger Institute, Cambridge, UK.12 Boston Children's Hospital, Divisions of Endocrinology and Genetics and Center for Basic and Translational Obesity Research13 Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts, USA.14 Institute for Medical Informatics, Biometry and Epidemiology (IMIBE), University Hospital of Essen, University of Duisburg-Essen15 Department of Medical Genetics, University of Lausanne16 The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai17 unknown18 Section for Metabolic Genetics, Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, Københavns Universitet
Rigorous organization and quality control (QC) are necessary to facilitate successful genome-wide association meta-analyses (GWAMAs) of statistics aggregated across multiple genome-wide association studies. This protocol provides guidelines for (i) organizational aspects of GWAMAs, and for (ii) QC at the study file level, the meta-level across studies and the meta-analysis output level. Real-world examples highlight issues experienced and solutions developed by the GIANT Consortium that has conducted meta-analyses including data from 125 studies comprising more than 330,000 individuals. We provide a general protocol for conducting GWAMAs and carrying out QC to minimize errors and to guarantee maximum use of the data. We also include details for the use of a powerful and flexible software package called EasyQC. Precise timings will be greatly influenced by consortium size. For consortia of comparable size to the GIANT Consortium, this protocol takes a minimum of about 10 months to complete.
Nature Protocols (online), 2014, Vol 9, Issue 5, p. 1192-1212
Genome-Wide Association Study; Meta-Analysis as Topic; Quality Control; Software