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GWAMA: software for genome-wide association meta-analysis
Open accessAbstract
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 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. 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 each association study and generate graphical summaries of genome-wide meta-analysis results. CONCLUSIONS: The GWAMA (Genome-Wide Association Meta-Analysis) software has been developed to perform meta-analysis of summary statistics generated from genome-wide association studies of dichotomous phenotypes or quantitative traits. Software with source files, documentation and example data files are freely available online at http://www.well.ox.ac.uk/GWAMA.
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“2.2) 46 with SEldsc to correct for inflation.”
Influential
Metadata
- Authors
- Mägi, R., & Morris, A. P.
- Venue
- BMC Bioinformatics
- Published
- 2010-05-28
- Volume
- 11
- Issue
- 1
- Pages
- 288-288
- ISSN
- 1471-2105 (ISSN-L)
- OpenAlex
- W1970560511
- Cited by
- 603
- References
- 9
- FWCI
- 10.73
- Type
- journal article
- Language
- en
- Open access
- gold
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