Background: Meta-analysis is increasingly used as a key source of evidence synthesis to inform clinical practice. The theory and statistical foundations of meta-analysis continually evolve, providing solutions to many new and challenging problems. Objectives: To combine the strengths of general statistical packages (flexibility) and dedicated meta-analysis programs (ease-of-use) for performing meta-analyses in a stand-alone, cross-platform, open-source meta-analysis program. To this end, we are developing a new R package that contains both basic and advanced meta-analytic methods, including an interface to OpenBugs to fit Bayesian models, with a consistent Application Programming Interface (API), and a Graphical User Interface (GUI) that allows novice analysts (who may not speak R) to easily use this package. Methods: All analytic methods in OpenMeta are written and executed in the R programming language; this allows us to leverage previously written meta-analysis code, including Bayesian applications such as network meta-analysis written in BUGS Moreover, researchers can implement their own methods in R and plug them into the software. However, the underlying use of R is transparent to end-users; OpenMeta is a stand-alone program, with a spreadsheet-based graphical user interface (GUI) written in the Python programming language. Both R and Python are themselves open-source and cross-platform. Results & Conclusions: We introduce OpenMeta; a new, cross-platform, entirely open-source version of our Meta-Analyst software. OpenMeta has been designed to handle complex data structures, including multiple treatment groups, multiple follow-ups (network meta-analysis) and multiple outcomes. It provides many advanced meta-analytic routines and features an intuitive GUI. Moreover, OpenMeta features flexible plotting functionality through R.