GWAMA 2.2.2

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.

GWAMA (Genome-Wide Association Meta Analysis) software has been developed 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.

Accessing the software

To load the module:

$ module load apps/gwama/2.2.2

To view a list of command-line options, run the following command:

$ GWAMA --help

Accessing Previous Versions

Wherever possible, previous versions of this application will be retained for continuity, especially for research projects that require a consistent version of the software throughout the project. Such versions, however, may be unsupported by IT Services or the applications vendor, and may be withdrawn at short or no notice if they can no longer run on the cluster - for example, essential operating system upgrades may be incompatible with old versions.

At present there are no previous versions of this application on the BlueBEAR service.

Known Problems & Limitations

None.

Other Information

The Support Level for this application is An.

Visit the GWAMA website for more information regarding this application.


Last modified: 11 September 2017