GWAMA: software for genome-wide association meta-analysis

Background: 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 metaanalysis 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. Results: We have developed flexible, open-source software for the meta-analysis of genome-wide association studies. The software incorporates a variety of error trapping facilities, and provides a range of meta-analysis summary statistics. The software is distributed with scripts that allow simple formatting of files containing the results of e...

• Type: Journal
• Year: 2010
• Where: BMCBI
• Authors: Reedik Mägi, Andrew P. Morris
• Keywords: BMCBI 2010, Genome-wide Association, Genome-wide Association Studies, Meta-analysis