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Wednesday, July 5 • 11:18am - 11:36am
Ensemble packages with user friendly interface: an added value for the R community

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Keywords: Ensemble package, user-friendly interface, gene expression analysis, biclustering
Webpages: https://r-forge.r-project.org/R/?group_id=589, https://github.com/ewouddt/RcmdrPlugin.BiclustGUI
The increasing amount of R packages makes it difficult to any newcomer to orientate himself/herself in the large amount of option available for topics such as modeling, clustering, variable selection, optimization, sample size estimation etc. The quality of the packages, the associated help files, error reporting system and continuity of support vary significantly and methods may be duplicated across multiple packages if the packages focus on a specific application within a particular field only.
Ensemble packages can be seen as another type of contribution to the R community. Careful revision of packages that approach the same topic from different perspectives may be very useful for increasing the overall quality of the CRAN repository. The revision should not be limited to the technical part, but should also cover methodological aspects. A necessary condition for success of the ensemble package is of course that this revision happens in close collaboration with the authors of the original package.
An additional benefit of ensemble packages lies in leveraging many graphical options of the traditional R framework. Starting from a simple Graphical User Interface, over an R Commander plugins, to Shiny applications, R provides wide range of visualization options. By combining visualization with the content of original packages, the ensemble package can provide different user experience. Such a property extends added value of ensemble beyond a simple review library. Necessarily, the flexibility of the package is reduced by transformation into point and click interface, but the user requiring a fully flexible environment can be referred to the original packages.
We present two case studies of such ensemble packages: IsoGeneGUI and BiclustGUI. IsoGeneGUI is implemented in the Graphical User Interface (GUI) and combines the original IsoGene package for dose-response analysis of high dimensional data with other packages such as orQA, ORIClust, goric and ORCME, that offer methods to analyze different perspectives of gene expression based data sets. IsoGeneGUI thus provides a wide range of methods methods (and the most complete data analysis tool for order restricted analysis) in a user friendly fashion. Hence analyzes can be implemented by users with only limited knowledge of R programming. The RcmdrPlugin.BiclustGUI is a GUI plugin for R Commander that combines various biclustering packages, bringing multiple algorithms, visualizations and diagnostics tools into one unified framework. Additionally, the package allows for simple inclusion of potential future biclustering methods.
The collaboration with the authors of the original packages on implementation of their methods within an ensemble package was extremely important for both case studies. Indeed, in that way, the link with the original packages could be retained. The ensemble package allowed for careful evaluation of the methods, their overlap and differences, and for presenting them as a concise framework in a user friendly environment.


Wednesday July 5, 2017 11:18am - 11:36am
3.02 Wild Gallery

Attendees (105)