GWAMA: Software for Genome-wide Association Meta-analysis

Overview

Journal BMC Bioinformatics

Publisher Biomed Central

Specialty Biology

Date 2010 Jun 1

PMID 20509871

Citations 356

Authors

Reedik Magi

Andrew P Morris

Affiliations

Soon will be listed here.

Abstract

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.

Citing Articles

Atlas of genetic and phenotypic associations across 42 female reproductive health diagnoses.

Pujol Gualdo N, Dzigurski J, Rukins V, Pajuste F, Wolford B, Vosa M Nat Med. 2025; .

PMID: 40069456 DOI: 10.1038/s41591-025-03543-8.

Genome-wide association analysis using multiple Atlantic salmon populations.

Ajasa A, Gjoen H, Boison S, Lillehammer M Genet Sel Evol. 2025; 57(1):9.

PMID: 40016680 PMC: 11869457. DOI: 10.1186/s12711-025-00959-1.

A systematic analysis of the contribution of genetics to multimorbidity and comparisons with primary care data.

Murrin O, Mounier N, Voller B, Tata L, Gallego-Moll C, Roso-Llorach A EBioMedicine. 2025; 113:105584.

PMID: 39919332 PMC: 11848100. DOI: 10.1016/j.ebiom.2025.105584.

Trans-ancestry genome-wide association study of childhood body mass index identifies novel loci and age-specific effects.

Downie C, Shrestha P, Okello S, Yaser M, Lee H, Wang Y HGG Adv. 2025; 6(2):100411.

PMID: 39885687 PMC: 11875162. DOI: 10.1016/j.xhgg.2025.100411.

Associations of maternal night shift work during pregnancy with DNA methylation in offspring: a meta-analysis in the PACE consortium.

Marques I, Domenech-Panicello C, Geurtsen M, Hoang T, Richmond R, Polinski K Clin Epigenetics. 2025; 17(1):12.

PMID: 39844285 PMC: 11756212. DOI: 10.1186/s13148-024-01810-y.

References

DerSimonian R, Laird N . Meta-analysis in clinical trials. Control Clin Trials. 1986; 7(3):177-88. DOI: 10.1016/0197-2456(86)90046-2. View

Higgins J, Thompson S . Quantifying heterogeneity in a meta-analysis. Stat Med. 2002; 21(11):1539-58. DOI: 10.1002/sim.1186. View

Browning S, Browning B . Rapid and accurate haplotype phasing and missing-data inference for whole-genome association studies by use of localized haplotype clustering. Am J Hum Genet. 2007; 81(5):1084-97. PMC: 2265661. DOI: 10.1086/521987. View

Zeggini E, Scott L, Saxena R, Voight B, Marchini J, Hu T . Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes. Nat Genet. 2008; 40(5):638-45. PMC: 2672416. DOI: 10.1038/ng.120. View

Prokopenko I, Langenberg C, Florez J, Saxena R, Soranzo N, Thorleifsson G . Variants in MTNR1B influence fasting glucose levels. Nat Genet. 2008; 41(1):77-81. PMC: 2682768. DOI: 10.1038/ng.290. View

Lindgren C, Heid I, Randall J, Lamina C, Steinthorsdottir V, Qi L . Genome-wide association scan meta-analysis identifies three Loci influencing adiposity and fat distribution. PLoS Genet. 2009; 5(6):e1000508. PMC: 2695778. DOI: 10.1371/journal.pgen.1000508. View

Willer C, Speliotes E, Loos R, Li S, Lindgren C, Heid I . Six new loci associated with body mass index highlight a neuronal influence on body weight regulation. Nat Genet. 2008; 41(1):25-34. PMC: 2695662. DOI: 10.1038/ng.287. View

Huedo-Medina T, Sanchez-Meca J, Marin-Martinez F, Botella J . Assessing heterogeneity in meta-analysis: Q statistic or I2 index?. Psychol Methods. 2006; 11(2):193-206. DOI: 10.1037/1082-989X.11.2.193. View

de Bakker P, Ferreira M, Jia X, Neale B, Raychaudhuri S, Voight B . Practical aspects of imputation-driven meta-analysis of genome-wide association studies. Hum Mol Genet. 2008; 17(R2):R122-8. PMC: 2782358. DOI: 10.1093/hmg/ddn288. View

10.

Marchini J, Howie B, Myers S, McVean G, Donnelly P . A new multipoint method for genome-wide association studies by imputation of genotypes. Nat Genet. 2007; 39(7):906-13. DOI: 10.1038/ng2088. View

11.

Devlin B, Roeder K . Genomic control for association studies. Biometrics. 2001; 55(4):997-1004. DOI: 10.1111/j.0006-341x.1999.00997.x. View

12.

. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature. 2007; 447(7145):661-78. PMC: 2719288. DOI: 10.1038/nature05911. View

13.

Frazer K, Ballinger D, Cox D, Hinds D, Stuve L, Boudreau A . A second generation human haplotype map of over 3.1 million SNPs. Nature. 2007; 449(7164):851-61. PMC: 2689609. DOI: 10.1038/nature06258. View

14.

Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira M, Bender D . PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet. 2007; 81(3):559-75. PMC: 1950838. DOI: 10.1086/519795. View

15.

Ioannidis J, Patsopoulos N, Evangelou E . Heterogeneity in meta-analyses of genome-wide association investigations. PLoS One. 2007; 2(9):e841. PMC: 1950790. DOI: 10.1371/journal.pone.0000841. View