GWAMA: software for genome-wide association meta-analysis
<p style="text-align:justify;"> <b>Background:</b> 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 the...
| Glavni autori: | , |
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| Format: | Journal article |
| Jezik: | English |
| Izdano: |
BioMed Central
2010
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| _version_ | 1826269620502265856 |
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| author | Mägi, R Morris, A |
| author_facet | Mägi, R Morris, A |
| author_sort | Mägi, R |
| collection | OXFORD |
| description | <p style="text-align:justify;"> <b>Background:</b> 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.<br/><br/> <b>Results:</b> 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.<br/><br/> <b>Conclusions:</b> 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. </p> |
| first_indexed | 2024-03-06T21:27:55Z |
| format | Journal article |
| id | oxford-uuid:43b6a6a0-57c1-4d6b-b86b-784855cde1d0 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T21:27:55Z |
| publishDate | 2010 |
| publisher | BioMed Central |
| record_format | dspace |
| spelling | oxford-uuid:43b6a6a0-57c1-4d6b-b86b-784855cde1d02022-03-26T14:57:09ZGWAMA: software for genome-wide association meta-analysisJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:43b6a6a0-57c1-4d6b-b86b-784855cde1d0EnglishSymplectic Elements at OxfordBioMed Central2010Mägi, RMorris, A <p style="text-align:justify;"> <b>Background:</b> 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.<br/><br/> <b>Results:</b> 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.<br/><br/> <b>Conclusions:</b> 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. </p> |
| spellingShingle | Mägi, R Morris, A GWAMA: software for genome-wide association meta-analysis |
| title | GWAMA: software for genome-wide association meta-analysis |
| title_full | GWAMA: software for genome-wide association meta-analysis |
| title_fullStr | GWAMA: software for genome-wide association meta-analysis |
| title_full_unstemmed | GWAMA: software for genome-wide association meta-analysis |
| title_short | GWAMA: software for genome-wide association meta-analysis |
| title_sort | gwama software for genome wide association meta analysis |
| work_keys_str_mv | AT magir gwamasoftwareforgenomewideassociationmetaanalysis AT morrisa gwamasoftwareforgenomewideassociationmetaanalysis |