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, 18 (1), 563

MetaGenyo: A Web Tool for Meta-Analysis of Genetic Association Studies


MetaGenyo: A Web Tool for Meta-Analysis of Genetic Association Studies

Jordi Martorell-Marugan et al. BMC Bioinformatics.


Background: Genetic association studies (GAS) aims to evaluate the association between genetic variants and phenotypes. In the last few years, the number of this type of study has increased exponentially, but the results are not always reproducible due to experimental designs, low sample sizes and other methodological errors. In this field, meta-analysis techniques are becoming very popular tools to combine results across studies to increase statistical power and to resolve discrepancies in genetic association studies. A meta-analysis summarizes research findings, increases statistical power and enables the identification of genuine associations between genotypes and phenotypes. Meta-analysis techniques are increasingly used in GAS, but it is also increasing the amount of published meta-analysis containing different errors. Although there are several software packages that implement meta-analysis, none of them are specifically designed for genetic association studies and in most cases their use requires advanced programming or scripting expertise.

Results: We have developed MetaGenyo, a web tool for meta-analysis in GAS. MetaGenyo implements a complete and comprehensive workflow that can be executed in an easy-to-use environment without programming knowledge. MetaGenyo has been developed to guide users through the main steps of a GAS meta-analysis, covering Hardy-Weinberg test, statistical association for different genetic models, analysis of heterogeneity, testing for publication bias, subgroup analysis and robustness testing of the results.

Conclusions: MetaGenyo is a useful tool to conduct comprehensive genetic association meta-analysis. The application is freely available at .

Keywords: Genetic association study; Meta-analysis; Shiny; Web tool.

Conflict of interest statement

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Competing interests

The authors declare that they have no competing interests.

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Fig. 1
Fig. 1
Overview of MetaGenyo. The scheme represents the tool’s workflow. First, data is uploaded by the user and it can be reviewed. Secondly, HWE P-values are calculated, so users can decide to exclude some bad-quality samples and reupload their data. In Association tests, Forest plots, Publication bias and Subgroup analysis tabs users can download the meta-analysis results. Finally, users can check the sensitivity analysis
Fig. 2
Fig. 2
Forest plot of esophageal cancer data generated with MetaGenyo. The tested comparison is AG vs. AA + AG (overdominant model) and FEM was used

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