GWAMA: software for genome-wide association meta-analysis
Top Cited Papers
Open Access
- 28 May 2010
- journal article
- research article
- Published by Springer Nature in BMC Bioinformatics
- Vol. 11 (1) , 288
- https://doi.org/10.1186/1471-2105-11-288
Abstract
Despite the recent success of genome-wide association studies in identifying novel loci contributing effects to complex human traits, such as type 2 diabetes and obesity, much of the genetic component of variation in these phenotypes remains unexplained. One way to improving power to detect further novel loci is through meta-analysis of studies from the same population, increasing the sample size over any individual study. Although statistical software analysis packages incorporate routines for meta-analysis, they are ill equipped to meet the challenges of the scale and complexity of data generated in genome-wide association studies.Keywords
This publication has 15 references indexed in Scilit:
- Genome-Wide Association Scan Meta-Analysis Identifies Three Loci Influencing Adiposity and Fat DistributionPLoS Genetics, 2009
- Rapid and Accurate Haplotype Phasing and Missing-Data Inference for Whole-Genome Association Studies By Use of Localized Haplotype ClusteringAmerican Journal of Human Genetics, 2007
- A second generation human haplotype map of over 3.1 million SNPsNature, 2007
- Heterogeneity in Meta-Analyses of Genome-Wide Association InvestigationsPLOS ONE, 2007
- PLINK: A Tool Set for Whole-Genome Association and Population-Based Linkage AnalysesAmerican Journal of Human Genetics, 2007
- A new multipoint method for genome-wide association studies by imputation of genotypesNature Genetics, 2007
- Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controlsNature, 2007
- Assessing heterogeneity in meta-analysis: Q statistic or I² index?Psychological Methods, 2006
- Genomic Control for Association StudiesBiometrics, 1999
- Meta-analysis in clinical trialsControlled Clinical Trials, 1986