Software tool for meta analysis of whole genome association data
Genome-wide association (GWA) studies have proved to be extremely successful in identifying moderate genetic effects contributing to complex human phenotypes. However, to gain insights into increasingly more modest signals of association, samples of many thousands of individuals are required. One approach to overcome this problem is to combine the results of GWA studies from closely related populations via meta-analysis, without direct exchange of genotype and phenotype data.
We have developed the GWAMA (Genome-Wide Association Meta Analysis) software to perform meta-analysis of the results of GWA studies of binary or quantitative phenotypes. Fixed- and random-effect meta-analyses are performed for both directly genotyped and imputed SNPs using estimates of the allelic odds ratio and 95% confidence interval for binary traits, and estimates of the allelic effect size and standard error for quantitative phenotypes. GWAMA can be used for analysing the results of all different genetic models (multiplicative, additive, dominant, recessive). The software incorporates error trapping facilities to identify strand alignment errors and allele flipping, and performs tests of heterogeneity of effects between studies.
Magi R, Morris AP: GWAMA: software for genome-wide association meta-analysis. BMC Bioinformatics 2010, 11:288. (link)
SEX-SPECIFIC ANALYSIS METHOD:
Magi R, Lindgren CM, Morris AP: Meta-analysis of sex-specific genome-wide association studies. Genetic Epidemiology 2010, 34(8):846-853. (link)