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Ruby is a dynamic interpreted, open source, object-oriented programming language with an elegant syntax and a focus on simplicity and productivity. One factor that may hinder the dissemination of Ruby, among academic and technological communities, is that it does not contain built in methods for statistical analysis and graph creation. Statistical analysis with numerical data generated by Ruby scripts is traditionally performed by storing data into a file, which is read in another software environment for statistical analysis, such as R. In order to circumvent this limitation, libraries have been created to perform statistical analysis with Ruby. They have not gained popularity, possibly due to the limitations of statistical methods and relative complex usage. In this paper we describe a simple and dynamic procedure to connect Ruby and R scripts. We show that this approach can be used for large scale genome data processing and statistical analysis. Its usage is simpler than interface libraries, since it does not require the creation of methods or routines other than the already existing in R and Ruby.

Large scale statistical analysis of genome data with Ruby and R: skipping interface libraries