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METAINTER is a tool to perform meta-analysis of summary statistics obtained from a series of related studies. The special feature of METAINTER is the ability to meta-analyze the results of multiple linear and logistic regression models, broadly used in genome-wide association studies (GWAS). The tool assumes that a unique pre-defined model is used in multiple studies to test for association of SNP tuples with a particular phenotype. SNPs coding and parameters coding in regression models have to follow the standards specified in [H.J. Cordell, D.G. Clayton, 2002], see also Manual.
                Analysis results of the individual studies have to be provided in tabulated format. METAINTER supports the output format of the genetic interaction analysis software INTERSNP, as well as any freely defined format.
                The main meta-analysis method implemented in METAINTER is

suggested in [B.J. Becker, M.-J. Wu, 2007]. MSRS requires, in addition to model parameters estimates and their standard error, the availability of the covariance matrix. The covariance matrix of model parameters is provided, for instance, by INTERSNP tool. We note that in case of tests with just one parameter, MSRS is equivalent to the standard fixed effects meta-analysis method. Within MSRS framework, METAINTER can be used to test the homogeneity of studies results, and to obtain the common parameter estimates of multiple regression models in the joint sample.
                Since the covariance matrix of model parameters is not always available, METAINTER provides three further
meta-analysis methods:

Thereby, METAINTER enables meta-analysis of single-marker association tests, global haplotype tests and tests for and under gene-gene interaction.

Vaitsiakhovich T, Drichel D, Herold C, Lacour A, Becker T (2015). METAINTER: meta-analysis of multiple regression models in genome-wide association studies. Bioinformatics. 2015 Jan 15;31(2):151-7.