MADAM - An open source meta-analysis toolbox for R and Bioconductor

The presented package enables the carrying out of meta-analysis either by providing functions directly or by wrapping them to existing implementations. Overall, five different meta-analysis methods are now usable through MADAM, along with another three methods for combining the corresponding results. Visualizing the results is eased by three included functions. For developing and testing meta-analysis methods, a mock up data generator is integrated.The use of MADAM enables a user to focus on one package, in turn enabling them to work with the same data types across a set of methods. By making use of the snow package, MADAM can be made compatible with an existing parallel computing infrastructure. MADAM is open source and freely available within CRAN http://cran.r-project.org webcite.R http://www.r-project.org webcite and the associated Bioconductor [1] project have become one of the most widespread tools for bioinformatics in recent years. At approximately the same time, dozens of newly developed meta-analysis methods have been published [2-6]. For most of these methods, an implementation exists, but some still lack publicly available implementions in R. In the present paper, we present the MADAM package, which provides new implementations of two methods [5,6]. In addition, we also implemented wrappers to the existing meta-analysis methods [2,4].Since new methods and algorithms need to be tested and validated as well, we integrated a validation model for generating simulated data. For integrating results of different meta-analysis methods using an ensemble approach, three of these methods are also implemented in MADAM. For visualizing the meta-analysis results, we implemented three further methods.The Meta-Analysis Data Aggregation Methods (MADAM) toolbox is helpful to both developers of meta-analysis methods as well as to biologists, physicians, and bioinformaticians who conduct research across studies. Here, we present version 1.0 of the package, in turn describin